Add VT2-examples: all 6 chapters of 'Visualize This' (110 files) — data scraping, ETL, trends, categorical, multivariate, spatial, distribution analysis
This commit is contained in:
neo committed
1 parent
088771a9cf
commit
b42b866a8c
110 files changed
+400895
No files matched your search
@@ -0,0 +1,35 @@
|
||||
import csv
|
||||
|
||||
fields = None
|
||||
with open('income-scraped.csv') as csvfile:
|
||||
|
||||
reader = csv.reader(csvfile, delimiter=",")
|
||||
for row in reader:
|
||||
|
||||
# Save header variables
|
||||
if fields == None:
|
||||
fields = row
|
||||
|
||||
else:
|
||||
|
||||
# Start JSON string
|
||||
if row[0] == "1":
|
||||
famunit = '['
|
||||
else:
|
||||
famunit = ''
|
||||
|
||||
# Add family unit
|
||||
famunit += '{'
|
||||
famunit += '"' + fields[0] + '":' + row[0] + ',' # famindex
|
||||
famunit += '"' + fields[1] + '":' + row[1] + ',' # AGE
|
||||
famunit += '"' + fields[2] + '":' + row[2] # FTOTINC
|
||||
famunit += '}'
|
||||
|
||||
# Close set if at end
|
||||
if (row[0] == "200"):
|
||||
famunit += ']'
|
||||
else:
|
||||
famunit += ','
|
||||
|
||||
# Print family unit
|
||||
print(famunit)
|
||||
@@ -0,0 +1,26 @@
|
||||
import csv
|
||||
|
||||
fields = None
|
||||
with open('income-scraped.csv') as csvfile:
|
||||
|
||||
reader = csv.reader(csvfile, delimiter=",")
|
||||
for row in reader:
|
||||
|
||||
# Save header variables
|
||||
if fields == None:
|
||||
fields = row
|
||||
print('<?xml version="1.0" encoding="UTF-8"?>')
|
||||
print("<rows>")
|
||||
else:
|
||||
|
||||
# Add family unit
|
||||
famunit = '<row>'
|
||||
famunit += '<' + fields[0] + '>' + row[0] + '</' + fields[0] + '>' # famindex
|
||||
famunit += '<' + fields[1] + '>' + row[1] + '</' + fields[1] + '>' # AGE
|
||||
famunit += '<' + fields[2] + '>' + row[2] + '</' + fields[2] + '>' # FTOTINC
|
||||
famunit += '</row>'
|
||||
|
||||
# Print family unit
|
||||
print(famunit)
|
||||
|
||||
print("</rows>")
|
||||
@@ -0,0 +1,20 @@
|
||||
from bs4 import BeautifulSoup
|
||||
|
||||
fields = None
|
||||
with open('income-scraped-to-xml.xml') as xmlfile:
|
||||
|
||||
xmlread = xmlfile.read()
|
||||
|
||||
soup = BeautifulSoup(xmlread, features='xml')
|
||||
|
||||
# Start file
|
||||
f = open('xml-back-to-csv.csv', 'w')
|
||||
|
||||
# Write rows to file
|
||||
f.write(",".join(['famindex', 'AGE', 'FTOTINC'])+'\n')
|
||||
rows = soup.findAll('row')
|
||||
for row in rows:
|
||||
f.write(','.join([row.famindex.string, row.AGE.string, row.FTOTINC.string])+'\n')
|
||||
|
||||
# Close file
|
||||
f.close()
|
||||
@@ -0,0 +1,200 @@
|
||||
[{"famindex":1,"AGE":45,"FTOTINC":114000},
|
||||
{"famindex":2,"AGE":37,"FTOTINC":280000},
|
||||
{"famindex":3,"AGE":60,"FTOTINC":184000},
|
||||
{"famindex":4,"AGE":70,"FTOTINC":250100},
|
||||
{"famindex":5,"AGE":79,"FTOTINC":33040},
|
||||
{"famindex":6,"AGE":60,"FTOTINC":168000},
|
||||
{"famindex":7,"AGE":56,"FTOTINC":557000},
|
||||
{"famindex":8,"AGE":69,"FTOTINC":84500},
|
||||
{"famindex":9,"AGE":54,"FTOTINC":128800},
|
||||
{"famindex":10,"AGE":72,"FTOTINC":28500},
|
||||
{"famindex":11,"AGE":26,"FTOTINC":85000},
|
||||
{"famindex":12,"AGE":60,"FTOTINC":52000},
|
||||
{"famindex":13,"AGE":54,"FTOTINC":24000},
|
||||
{"famindex":14,"AGE":51,"FTOTINC":316600},
|
||||
{"famindex":15,"AGE":35,"FTOTINC":261590},
|
||||
{"famindex":16,"AGE":62,"FTOTINC":41200},
|
||||
{"famindex":17,"AGE":28,"FTOTINC":11000},
|
||||
{"famindex":18,"AGE":66,"FTOTINC":15500},
|
||||
{"famindex":19,"AGE":75,"FTOTINC":37100},
|
||||
{"famindex":20,"AGE":57,"FTOTINC":137000},
|
||||
{"famindex":21,"AGE":69,"FTOTINC":80000},
|
||||
{"famindex":22,"AGE":78,"FTOTINC":376100},
|
||||
{"famindex":23,"AGE":47,"FTOTINC":10000},
|
||||
{"famindex":24,"AGE":84,"FTOTINC":31400},
|
||||
{"famindex":25,"AGE":75,"FTOTINC":40000},
|
||||
{"famindex":26,"AGE":23,"FTOTINC":600},
|
||||
{"famindex":27,"AGE":43,"FTOTINC":59000},
|
||||
{"famindex":28,"AGE":87,"FTOTINC":26000},
|
||||
{"famindex":29,"AGE":66,"FTOTINC":22000},
|
||||
{"famindex":30,"AGE":62,"FTOTINC":103600},
|
||||
{"famindex":31,"AGE":25,"FTOTINC":18100},
|
||||
{"famindex":32,"AGE":45,"FTOTINC":25000},
|
||||
{"famindex":33,"AGE":65,"FTOTINC":106000},
|
||||
{"famindex":34,"AGE":63,"FTOTINC":111000},
|
||||
{"famindex":35,"AGE":68,"FTOTINC":13700},
|
||||
{"famindex":36,"AGE":28,"FTOTINC":160400},
|
||||
{"famindex":37,"AGE":49,"FTOTINC":206600},
|
||||
{"famindex":38,"AGE":58,"FTOTINC":67500},
|
||||
{"famindex":39,"AGE":74,"FTOTINC":115000},
|
||||
{"famindex":40,"AGE":70,"FTOTINC":107800},
|
||||
{"famindex":41,"AGE":79,"FTOTINC":28100},
|
||||
{"famindex":42,"AGE":22,"FTOTINC":36000},
|
||||
{"famindex":43,"AGE":69,"FTOTINC":92920},
|
||||
{"famindex":44,"AGE":27,"FTOTINC":91000},
|
||||
{"famindex":45,"AGE":60,"FTOTINC":89000},
|
||||
{"famindex":46,"AGE":69,"FTOTINC":309400},
|
||||
{"famindex":47,"AGE":34,"FTOTINC":151500},
|
||||
{"famindex":48,"AGE":35,"FTOTINC":71000},
|
||||
{"famindex":49,"AGE":42,"FTOTINC":94000},
|
||||
{"famindex":50,"AGE":64,"FTOTINC":94300},
|
||||
{"famindex":51,"AGE":40,"FTOTINC":148000},
|
||||
{"famindex":52,"AGE":95,"FTOTINC":1400},
|
||||
{"famindex":53,"AGE":39,"FTOTINC":75000},
|
||||
{"famindex":54,"AGE":63,"FTOTINC":89000},
|
||||
{"famindex":55,"AGE":54,"FTOTINC":317000},
|
||||
{"famindex":56,"AGE":53,"FTOTINC":57200},
|
||||
{"famindex":57,"AGE":57,"FTOTINC":49000},
|
||||
{"famindex":58,"AGE":44,"FTOTINC":7500},
|
||||
{"famindex":59,"AGE":87,"FTOTINC":50100},
|
||||
{"famindex":60,"AGE":60,"FTOTINC":8000},
|
||||
{"famindex":61,"AGE":55,"FTOTINC":48000},
|
||||
{"famindex":62,"AGE":32,"FTOTINC":24500},
|
||||
{"famindex":63,"AGE":87,"FTOTINC":25000},
|
||||
{"famindex":64,"AGE":67,"FTOTINC":68200},
|
||||
{"famindex":65,"AGE":90,"FTOTINC":32400},
|
||||
{"famindex":66,"AGE":23,"FTOTINC":41100},
|
||||
{"famindex":67,"AGE":64,"FTOTINC":77000},
|
||||
{"famindex":68,"AGE":32,"FTOTINC":86700},
|
||||
{"famindex":69,"AGE":49,"FTOTINC":15200},
|
||||
{"famindex":70,"AGE":54,"FTOTINC":573000},
|
||||
{"famindex":71,"AGE":69,"FTOTINC":69000},
|
||||
{"famindex":72,"AGE":64,"FTOTINC":147000},
|
||||
{"famindex":73,"AGE":57,"FTOTINC":111600},
|
||||
{"famindex":74,"AGE":53,"FTOTINC":31200},
|
||||
{"famindex":75,"AGE":40,"FTOTINC":151500},
|
||||
{"famindex":76,"AGE":58,"FTOTINC":52300},
|
||||
{"famindex":77,"AGE":42,"FTOTINC":13500},
|
||||
{"famindex":78,"AGE":75,"FTOTINC":20900},
|
||||
{"famindex":79,"AGE":33,"FTOTINC":133800},
|
||||
{"famindex":80,"AGE":39,"FTOTINC":83000},
|
||||
{"famindex":81,"AGE":24,"FTOTINC":80000},
|
||||
{"famindex":82,"AGE":59,"FTOTINC":16000},
|
||||
{"famindex":83,"AGE":48,"FTOTINC":60000},
|
||||
{"famindex":84,"AGE":45,"FTOTINC":162200},
|
||||
{"famindex":85,"AGE":83,"FTOTINC":3000},
|
||||
{"famindex":86,"AGE":76,"FTOTINC":147900},
|
||||
{"famindex":87,"AGE":40,"FTOTINC":78300},
|
||||
{"famindex":88,"AGE":61,"FTOTINC":240000},
|
||||
{"famindex":89,"AGE":35,"FTOTINC":85000},
|
||||
{"famindex":90,"AGE":46,"FTOTINC":80000},
|
||||
{"famindex":91,"AGE":46,"FTOTINC":112200},
|
||||
{"famindex":92,"AGE":30,"FTOTINC":130000},
|
||||
{"famindex":93,"AGE":25,"FTOTINC":19550},
|
||||
{"famindex":94,"AGE":65,"FTOTINC":148000},
|
||||
{"famindex":95,"AGE":57,"FTOTINC":129400},
|
||||
{"famindex":96,"AGE":39,"FTOTINC":94000},
|
||||
{"famindex":97,"AGE":21,"FTOTINC":31100},
|
||||
{"famindex":98,"AGE":56,"FTOTINC":100000},
|
||||
{"famindex":99,"AGE":38,"FTOTINC":40000},
|
||||
{"famindex":100,"AGE":76,"FTOTINC":63310},
|
||||
{"famindex":101,"AGE":59,"FTOTINC":128000},
|
||||
{"famindex":102,"AGE":25,"FTOTINC":45000},
|
||||
{"famindex":103,"AGE":43,"FTOTINC":136800},
|
||||
{"famindex":104,"AGE":62,"FTOTINC":125000},
|
||||
{"famindex":105,"AGE":59,"FTOTINC":94400},
|
||||
{"famindex":106,"AGE":81,"FTOTINC":86300},
|
||||
{"famindex":107,"AGE":39,"FTOTINC":150100},
|
||||
{"famindex":108,"AGE":28,"FTOTINC":34000},
|
||||
{"famindex":109,"AGE":34,"FTOTINC":79640},
|
||||
{"famindex":110,"AGE":60,"FTOTINC":35000},
|
||||
{"famindex":111,"AGE":45,"FTOTINC":337000},
|
||||
{"famindex":112,"AGE":31,"FTOTINC":100000},
|
||||
{"famindex":113,"AGE":67,"FTOTINC":63400},
|
||||
{"famindex":114,"AGE":64,"FTOTINC":141600},
|
||||
{"famindex":115,"AGE":86,"FTOTINC":30100},
|
||||
{"famindex":116,"AGE":83,"FTOTINC":44300},
|
||||
{"famindex":117,"AGE":61,"FTOTINC":122000},
|
||||
{"famindex":118,"AGE":58,"FTOTINC":43000},
|
||||
{"famindex":119,"AGE":79,"FTOTINC":104000},
|
||||
{"famindex":120,"AGE":61,"FTOTINC":9600},
|
||||
{"famindex":121,"AGE":44,"FTOTINC":66100},
|
||||
{"famindex":122,"AGE":26,"FTOTINC":38100},
|
||||
{"famindex":123,"AGE":32,"FTOTINC":103000},
|
||||
{"famindex":124,"AGE":22,"FTOTINC":59000},
|
||||
{"famindex":125,"AGE":36,"FTOTINC":56000},
|
||||
{"famindex":126,"AGE":84,"FTOTINC":114300},
|
||||
{"famindex":127,"AGE":24,"FTOTINC":68300},
|
||||
{"famindex":128,"AGE":76,"FTOTINC":84600},
|
||||
{"famindex":129,"AGE":57,"FTOTINC":161400},
|
||||
{"famindex":130,"AGE":46,"FTOTINC":18800},
|
||||
{"famindex":131,"AGE":53,"FTOTINC":45300},
|
||||
{"famindex":132,"AGE":26,"FTOTINC":85000},
|
||||
{"famindex":133,"AGE":67,"FTOTINC":40600},
|
||||
{"famindex":134,"AGE":36,"FTOTINC":88000},
|
||||
{"famindex":135,"AGE":57,"FTOTINC":134300},
|
||||
{"famindex":136,"AGE":30,"FTOTINC":54000},
|
||||
{"famindex":137,"AGE":41,"FTOTINC":45600},
|
||||
{"famindex":138,"AGE":74,"FTOTINC":43210},
|
||||
{"famindex":139,"AGE":22,"FTOTINC":10000},
|
||||
{"famindex":140,"AGE":51,"FTOTINC":160000},
|
||||
{"famindex":141,"AGE":51,"FTOTINC":130400},
|
||||
{"famindex":142,"AGE":47,"FTOTINC":45000},
|
||||
{"famindex":143,"AGE":25,"FTOTINC":34000},
|
||||
{"famindex":144,"AGE":37,"FTOTINC":78000},
|
||||
{"famindex":145,"AGE":62,"FTOTINC":18500},
|
||||
{"famindex":146,"AGE":44,"FTOTINC":169000},
|
||||
{"famindex":147,"AGE":41,"FTOTINC":86000},
|
||||
{"famindex":148,"AGE":66,"FTOTINC":446000},
|
||||
{"famindex":149,"AGE":40,"FTOTINC":55000},
|
||||
{"famindex":150,"AGE":63,"FTOTINC":41400},
|
||||
{"famindex":151,"AGE":41,"FTOTINC":29000},
|
||||
{"famindex":152,"AGE":22,"FTOTINC":38000},
|
||||
{"famindex":153,"AGE":50,"FTOTINC":83460},
|
||||
{"famindex":154,"AGE":69,"FTOTINC":16400},
|
||||
{"famindex":155,"AGE":29,"FTOTINC":181600},
|
||||
{"famindex":156,"AGE":70,"FTOTINC":23800},
|
||||
{"famindex":157,"AGE":65,"FTOTINC":132200},
|
||||
{"famindex":158,"AGE":32,"FTOTINC":217000},
|
||||
{"famindex":159,"AGE":48,"FTOTINC":32800},
|
||||
{"famindex":160,"AGE":47,"FTOTINC":55000},
|
||||
{"famindex":161,"AGE":60,"FTOTINC":88000},
|
||||
{"famindex":162,"AGE":75,"FTOTINC":46300},
|
||||
{"famindex":163,"AGE":55,"FTOTINC":31500},
|
||||
{"famindex":164,"AGE":73,"FTOTINC":8100},
|
||||
{"famindex":165,"AGE":40,"FTOTINC":45000},
|
||||
{"famindex":166,"AGE":65,"FTOTINC":47000},
|
||||
{"famindex":167,"AGE":84,"FTOTINC":11700},
|
||||
{"famindex":168,"AGE":71,"FTOTINC":9800},
|
||||
{"famindex":169,"AGE":83,"FTOTINC":55400},
|
||||
{"famindex":170,"AGE":51,"FTOTINC":77000},
|
||||
{"famindex":171,"AGE":40,"FTOTINC":34100},
|
||||
{"famindex":172,"AGE":39,"FTOTINC":130000},
|
||||
{"famindex":173,"AGE":27,"FTOTINC":82000},
|
||||
{"famindex":174,"AGE":36,"FTOTINC":54000},
|
||||
{"famindex":175,"AGE":81,"FTOTINC":29630},
|
||||
{"famindex":176,"AGE":35,"FTOTINC":93800},
|
||||
{"famindex":177,"AGE":59,"FTOTINC":122900},
|
||||
{"famindex":178,"AGE":26,"FTOTINC":65000},
|
||||
{"famindex":179,"AGE":66,"FTOTINC":108000},
|
||||
{"famindex":180,"AGE":46,"FTOTINC":2500},
|
||||
{"famindex":181,"AGE":28,"FTOTINC":42000},
|
||||
{"famindex":182,"AGE":25,"FTOTINC":77000},
|
||||
{"famindex":183,"AGE":66,"FTOTINC":9000},
|
||||
{"famindex":184,"AGE":58,"FTOTINC":80500},
|
||||
{"famindex":185,"AGE":56,"FTOTINC":84000},
|
||||
{"famindex":186,"AGE":61,"FTOTINC":85000},
|
||||
{"famindex":187,"AGE":32,"FTOTINC":156000},
|
||||
{"famindex":188,"AGE":86,"FTOTINC":359400},
|
||||
{"famindex":189,"AGE":60,"FTOTINC":99000},
|
||||
{"famindex":190,"AGE":26,"FTOTINC":42000},
|
||||
{"famindex":191,"AGE":62,"FTOTINC":56000},
|
||||
{"famindex":192,"AGE":32,"FTOTINC":78000},
|
||||
{"famindex":193,"AGE":26,"FTOTINC":35000},
|
||||
{"famindex":194,"AGE":50,"FTOTINC":27000},
|
||||
{"famindex":195,"AGE":28,"FTOTINC":70000},
|
||||
{"famindex":196,"AGE":32,"FTOTINC":38000},
|
||||
{"famindex":197,"AGE":59,"FTOTINC":120000},
|
||||
{"famindex":198,"AGE":64,"FTOTINC":9600},
|
||||
{"famindex":199,"AGE":33,"FTOTINC":107200},
|
||||
{"famindex":200,"AGE":60,"FTOTINC":70800}]
|
||||
@@ -0,0 +1,203 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<rows>
|
||||
<row><famindex>1</famindex><AGE>45</AGE><FTOTINC>114000</FTOTINC></row>
|
||||
<row><famindex>2</famindex><AGE>37</AGE><FTOTINC>280000</FTOTINC></row>
|
||||
<row><famindex>3</famindex><AGE>60</AGE><FTOTINC>184000</FTOTINC></row>
|
||||
<row><famindex>4</famindex><AGE>70</AGE><FTOTINC>250100</FTOTINC></row>
|
||||
<row><famindex>5</famindex><AGE>79</AGE><FTOTINC>33040</FTOTINC></row>
|
||||
<row><famindex>6</famindex><AGE>60</AGE><FTOTINC>168000</FTOTINC></row>
|
||||
<row><famindex>7</famindex><AGE>56</AGE><FTOTINC>557000</FTOTINC></row>
|
||||
<row><famindex>8</famindex><AGE>69</AGE><FTOTINC>84500</FTOTINC></row>
|
||||
<row><famindex>9</famindex><AGE>54</AGE><FTOTINC>128800</FTOTINC></row>
|
||||
<row><famindex>10</famindex><AGE>72</AGE><FTOTINC>28500</FTOTINC></row>
|
||||
<row><famindex>11</famindex><AGE>26</AGE><FTOTINC>85000</FTOTINC></row>
|
||||
<row><famindex>12</famindex><AGE>60</AGE><FTOTINC>52000</FTOTINC></row>
|
||||
<row><famindex>13</famindex><AGE>54</AGE><FTOTINC>24000</FTOTINC></row>
|
||||
<row><famindex>14</famindex><AGE>51</AGE><FTOTINC>316600</FTOTINC></row>
|
||||
<row><famindex>15</famindex><AGE>35</AGE><FTOTINC>261590</FTOTINC></row>
|
||||
<row><famindex>16</famindex><AGE>62</AGE><FTOTINC>41200</FTOTINC></row>
|
||||
<row><famindex>17</famindex><AGE>28</AGE><FTOTINC>11000</FTOTINC></row>
|
||||
<row><famindex>18</famindex><AGE>66</AGE><FTOTINC>15500</FTOTINC></row>
|
||||
<row><famindex>19</famindex><AGE>75</AGE><FTOTINC>37100</FTOTINC></row>
|
||||
<row><famindex>20</famindex><AGE>57</AGE><FTOTINC>137000</FTOTINC></row>
|
||||
<row><famindex>21</famindex><AGE>69</AGE><FTOTINC>80000</FTOTINC></row>
|
||||
<row><famindex>22</famindex><AGE>78</AGE><FTOTINC>376100</FTOTINC></row>
|
||||
<row><famindex>23</famindex><AGE>47</AGE><FTOTINC>10000</FTOTINC></row>
|
||||
<row><famindex>24</famindex><AGE>84</AGE><FTOTINC>31400</FTOTINC></row>
|
||||
<row><famindex>25</famindex><AGE>75</AGE><FTOTINC>40000</FTOTINC></row>
|
||||
<row><famindex>26</famindex><AGE>23</AGE><FTOTINC>600</FTOTINC></row>
|
||||
<row><famindex>27</famindex><AGE>43</AGE><FTOTINC>59000</FTOTINC></row>
|
||||
<row><famindex>28</famindex><AGE>87</AGE><FTOTINC>26000</FTOTINC></row>
|
||||
<row><famindex>29</famindex><AGE>66</AGE><FTOTINC>22000</FTOTINC></row>
|
||||
<row><famindex>30</famindex><AGE>62</AGE><FTOTINC>103600</FTOTINC></row>
|
||||
<row><famindex>31</famindex><AGE>25</AGE><FTOTINC>18100</FTOTINC></row>
|
||||
<row><famindex>32</famindex><AGE>45</AGE><FTOTINC>25000</FTOTINC></row>
|
||||
<row><famindex>33</famindex><AGE>65</AGE><FTOTINC>106000</FTOTINC></row>
|
||||
<row><famindex>34</famindex><AGE>63</AGE><FTOTINC>111000</FTOTINC></row>
|
||||
<row><famindex>35</famindex><AGE>68</AGE><FTOTINC>13700</FTOTINC></row>
|
||||
<row><famindex>36</famindex><AGE>28</AGE><FTOTINC>160400</FTOTINC></row>
|
||||
<row><famindex>37</famindex><AGE>49</AGE><FTOTINC>206600</FTOTINC></row>
|
||||
<row><famindex>38</famindex><AGE>58</AGE><FTOTINC>67500</FTOTINC></row>
|
||||
<row><famindex>39</famindex><AGE>74</AGE><FTOTINC>115000</FTOTINC></row>
|
||||
<row><famindex>40</famindex><AGE>70</AGE><FTOTINC>107800</FTOTINC></row>
|
||||
<row><famindex>41</famindex><AGE>79</AGE><FTOTINC>28100</FTOTINC></row>
|
||||
<row><famindex>42</famindex><AGE>22</AGE><FTOTINC>36000</FTOTINC></row>
|
||||
<row><famindex>43</famindex><AGE>69</AGE><FTOTINC>92920</FTOTINC></row>
|
||||
<row><famindex>44</famindex><AGE>27</AGE><FTOTINC>91000</FTOTINC></row>
|
||||
<row><famindex>45</famindex><AGE>60</AGE><FTOTINC>89000</FTOTINC></row>
|
||||
<row><famindex>46</famindex><AGE>69</AGE><FTOTINC>309400</FTOTINC></row>
|
||||
<row><famindex>47</famindex><AGE>34</AGE><FTOTINC>151500</FTOTINC></row>
|
||||
<row><famindex>48</famindex><AGE>35</AGE><FTOTINC>71000</FTOTINC></row>
|
||||
<row><famindex>49</famindex><AGE>42</AGE><FTOTINC>94000</FTOTINC></row>
|
||||
<row><famindex>50</famindex><AGE>64</AGE><FTOTINC>94300</FTOTINC></row>
|
||||
<row><famindex>51</famindex><AGE>40</AGE><FTOTINC>148000</FTOTINC></row>
|
||||
<row><famindex>52</famindex><AGE>95</AGE><FTOTINC>1400</FTOTINC></row>
|
||||
<row><famindex>53</famindex><AGE>39</AGE><FTOTINC>75000</FTOTINC></row>
|
||||
<row><famindex>54</famindex><AGE>63</AGE><FTOTINC>89000</FTOTINC></row>
|
||||
<row><famindex>55</famindex><AGE>54</AGE><FTOTINC>317000</FTOTINC></row>
|
||||
<row><famindex>56</famindex><AGE>53</AGE><FTOTINC>57200</FTOTINC></row>
|
||||
<row><famindex>57</famindex><AGE>57</AGE><FTOTINC>49000</FTOTINC></row>
|
||||
<row><famindex>58</famindex><AGE>44</AGE><FTOTINC>7500</FTOTINC></row>
|
||||
<row><famindex>59</famindex><AGE>87</AGE><FTOTINC>50100</FTOTINC></row>
|
||||
<row><famindex>60</famindex><AGE>60</AGE><FTOTINC>8000</FTOTINC></row>
|
||||
<row><famindex>61</famindex><AGE>55</AGE><FTOTINC>48000</FTOTINC></row>
|
||||
<row><famindex>62</famindex><AGE>32</AGE><FTOTINC>24500</FTOTINC></row>
|
||||
<row><famindex>63</famindex><AGE>87</AGE><FTOTINC>25000</FTOTINC></row>
|
||||
<row><famindex>64</famindex><AGE>67</AGE><FTOTINC>68200</FTOTINC></row>
|
||||
<row><famindex>65</famindex><AGE>90</AGE><FTOTINC>32400</FTOTINC></row>
|
||||
<row><famindex>66</famindex><AGE>23</AGE><FTOTINC>41100</FTOTINC></row>
|
||||
<row><famindex>67</famindex><AGE>64</AGE><FTOTINC>77000</FTOTINC></row>
|
||||
<row><famindex>68</famindex><AGE>32</AGE><FTOTINC>86700</FTOTINC></row>
|
||||
<row><famindex>69</famindex><AGE>49</AGE><FTOTINC>15200</FTOTINC></row>
|
||||
<row><famindex>70</famindex><AGE>54</AGE><FTOTINC>573000</FTOTINC></row>
|
||||
<row><famindex>71</famindex><AGE>69</AGE><FTOTINC>69000</FTOTINC></row>
|
||||
<row><famindex>72</famindex><AGE>64</AGE><FTOTINC>147000</FTOTINC></row>
|
||||
<row><famindex>73</famindex><AGE>57</AGE><FTOTINC>111600</FTOTINC></row>
|
||||
<row><famindex>74</famindex><AGE>53</AGE><FTOTINC>31200</FTOTINC></row>
|
||||
<row><famindex>75</famindex><AGE>40</AGE><FTOTINC>151500</FTOTINC></row>
|
||||
<row><famindex>76</famindex><AGE>58</AGE><FTOTINC>52300</FTOTINC></row>
|
||||
<row><famindex>77</famindex><AGE>42</AGE><FTOTINC>13500</FTOTINC></row>
|
||||
<row><famindex>78</famindex><AGE>75</AGE><FTOTINC>20900</FTOTINC></row>
|
||||
<row><famindex>79</famindex><AGE>33</AGE><FTOTINC>133800</FTOTINC></row>
|
||||
<row><famindex>80</famindex><AGE>39</AGE><FTOTINC>83000</FTOTINC></row>
|
||||
<row><famindex>81</famindex><AGE>24</AGE><FTOTINC>80000</FTOTINC></row>
|
||||
<row><famindex>82</famindex><AGE>59</AGE><FTOTINC>16000</FTOTINC></row>
|
||||
<row><famindex>83</famindex><AGE>48</AGE><FTOTINC>60000</FTOTINC></row>
|
||||
<row><famindex>84</famindex><AGE>45</AGE><FTOTINC>162200</FTOTINC></row>
|
||||
<row><famindex>85</famindex><AGE>83</AGE><FTOTINC>3000</FTOTINC></row>
|
||||
<row><famindex>86</famindex><AGE>76</AGE><FTOTINC>147900</FTOTINC></row>
|
||||
<row><famindex>87</famindex><AGE>40</AGE><FTOTINC>78300</FTOTINC></row>
|
||||
<row><famindex>88</famindex><AGE>61</AGE><FTOTINC>240000</FTOTINC></row>
|
||||
<row><famindex>89</famindex><AGE>35</AGE><FTOTINC>85000</FTOTINC></row>
|
||||
<row><famindex>90</famindex><AGE>46</AGE><FTOTINC>80000</FTOTINC></row>
|
||||
<row><famindex>91</famindex><AGE>46</AGE><FTOTINC>112200</FTOTINC></row>
|
||||
<row><famindex>92</famindex><AGE>30</AGE><FTOTINC>130000</FTOTINC></row>
|
||||
<row><famindex>93</famindex><AGE>25</AGE><FTOTINC>19550</FTOTINC></row>
|
||||
<row><famindex>94</famindex><AGE>65</AGE><FTOTINC>148000</FTOTINC></row>
|
||||
<row><famindex>95</famindex><AGE>57</AGE><FTOTINC>129400</FTOTINC></row>
|
||||
<row><famindex>96</famindex><AGE>39</AGE><FTOTINC>94000</FTOTINC></row>
|
||||
<row><famindex>97</famindex><AGE>21</AGE><FTOTINC>31100</FTOTINC></row>
|
||||
<row><famindex>98</famindex><AGE>56</AGE><FTOTINC>100000</FTOTINC></row>
|
||||
<row><famindex>99</famindex><AGE>38</AGE><FTOTINC>40000</FTOTINC></row>
|
||||
<row><famindex>100</famindex><AGE>76</AGE><FTOTINC>63310</FTOTINC></row>
|
||||
<row><famindex>101</famindex><AGE>59</AGE><FTOTINC>128000</FTOTINC></row>
|
||||
<row><famindex>102</famindex><AGE>25</AGE><FTOTINC>45000</FTOTINC></row>
|
||||
<row><famindex>103</famindex><AGE>43</AGE><FTOTINC>136800</FTOTINC></row>
|
||||
<row><famindex>104</famindex><AGE>62</AGE><FTOTINC>125000</FTOTINC></row>
|
||||
<row><famindex>105</famindex><AGE>59</AGE><FTOTINC>94400</FTOTINC></row>
|
||||
<row><famindex>106</famindex><AGE>81</AGE><FTOTINC>86300</FTOTINC></row>
|
||||
<row><famindex>107</famindex><AGE>39</AGE><FTOTINC>150100</FTOTINC></row>
|
||||
<row><famindex>108</famindex><AGE>28</AGE><FTOTINC>34000</FTOTINC></row>
|
||||
<row><famindex>109</famindex><AGE>34</AGE><FTOTINC>79640</FTOTINC></row>
|
||||
<row><famindex>110</famindex><AGE>60</AGE><FTOTINC>35000</FTOTINC></row>
|
||||
<row><famindex>111</famindex><AGE>45</AGE><FTOTINC>337000</FTOTINC></row>
|
||||
<row><famindex>112</famindex><AGE>31</AGE><FTOTINC>100000</FTOTINC></row>
|
||||
<row><famindex>113</famindex><AGE>67</AGE><FTOTINC>63400</FTOTINC></row>
|
||||
<row><famindex>114</famindex><AGE>64</AGE><FTOTINC>141600</FTOTINC></row>
|
||||
<row><famindex>115</famindex><AGE>86</AGE><FTOTINC>30100</FTOTINC></row>
|
||||
<row><famindex>116</famindex><AGE>83</AGE><FTOTINC>44300</FTOTINC></row>
|
||||
<row><famindex>117</famindex><AGE>61</AGE><FTOTINC>122000</FTOTINC></row>
|
||||
<row><famindex>118</famindex><AGE>58</AGE><FTOTINC>43000</FTOTINC></row>
|
||||
<row><famindex>119</famindex><AGE>79</AGE><FTOTINC>104000</FTOTINC></row>
|
||||
<row><famindex>120</famindex><AGE>61</AGE><FTOTINC>9600</FTOTINC></row>
|
||||
<row><famindex>121</famindex><AGE>44</AGE><FTOTINC>66100</FTOTINC></row>
|
||||
<row><famindex>122</famindex><AGE>26</AGE><FTOTINC>38100</FTOTINC></row>
|
||||
<row><famindex>123</famindex><AGE>32</AGE><FTOTINC>103000</FTOTINC></row>
|
||||
<row><famindex>124</famindex><AGE>22</AGE><FTOTINC>59000</FTOTINC></row>
|
||||
<row><famindex>125</famindex><AGE>36</AGE><FTOTINC>56000</FTOTINC></row>
|
||||
<row><famindex>126</famindex><AGE>84</AGE><FTOTINC>114300</FTOTINC></row>
|
||||
<row><famindex>127</famindex><AGE>24</AGE><FTOTINC>68300</FTOTINC></row>
|
||||
<row><famindex>128</famindex><AGE>76</AGE><FTOTINC>84600</FTOTINC></row>
|
||||
<row><famindex>129</famindex><AGE>57</AGE><FTOTINC>161400</FTOTINC></row>
|
||||
<row><famindex>130</famindex><AGE>46</AGE><FTOTINC>18800</FTOTINC></row>
|
||||
<row><famindex>131</famindex><AGE>53</AGE><FTOTINC>45300</FTOTINC></row>
|
||||
<row><famindex>132</famindex><AGE>26</AGE><FTOTINC>85000</FTOTINC></row>
|
||||
<row><famindex>133</famindex><AGE>67</AGE><FTOTINC>40600</FTOTINC></row>
|
||||
<row><famindex>134</famindex><AGE>36</AGE><FTOTINC>88000</FTOTINC></row>
|
||||
<row><famindex>135</famindex><AGE>57</AGE><FTOTINC>134300</FTOTINC></row>
|
||||
<row><famindex>136</famindex><AGE>30</AGE><FTOTINC>54000</FTOTINC></row>
|
||||
<row><famindex>137</famindex><AGE>41</AGE><FTOTINC>45600</FTOTINC></row>
|
||||
<row><famindex>138</famindex><AGE>74</AGE><FTOTINC>43210</FTOTINC></row>
|
||||
<row><famindex>139</famindex><AGE>22</AGE><FTOTINC>10000</FTOTINC></row>
|
||||
<row><famindex>140</famindex><AGE>51</AGE><FTOTINC>160000</FTOTINC></row>
|
||||
<row><famindex>141</famindex><AGE>51</AGE><FTOTINC>130400</FTOTINC></row>
|
||||
<row><famindex>142</famindex><AGE>47</AGE><FTOTINC>45000</FTOTINC></row>
|
||||
<row><famindex>143</famindex><AGE>25</AGE><FTOTINC>34000</FTOTINC></row>
|
||||
<row><famindex>144</famindex><AGE>37</AGE><FTOTINC>78000</FTOTINC></row>
|
||||
<row><famindex>145</famindex><AGE>62</AGE><FTOTINC>18500</FTOTINC></row>
|
||||
<row><famindex>146</famindex><AGE>44</AGE><FTOTINC>169000</FTOTINC></row>
|
||||
<row><famindex>147</famindex><AGE>41</AGE><FTOTINC>86000</FTOTINC></row>
|
||||
<row><famindex>148</famindex><AGE>66</AGE><FTOTINC>446000</FTOTINC></row>
|
||||
<row><famindex>149</famindex><AGE>40</AGE><FTOTINC>55000</FTOTINC></row>
|
||||
<row><famindex>150</famindex><AGE>63</AGE><FTOTINC>41400</FTOTINC></row>
|
||||
<row><famindex>151</famindex><AGE>41</AGE><FTOTINC>29000</FTOTINC></row>
|
||||
<row><famindex>152</famindex><AGE>22</AGE><FTOTINC>38000</FTOTINC></row>
|
||||
<row><famindex>153</famindex><AGE>50</AGE><FTOTINC>83460</FTOTINC></row>
|
||||
<row><famindex>154</famindex><AGE>69</AGE><FTOTINC>16400</FTOTINC></row>
|
||||
<row><famindex>155</famindex><AGE>29</AGE><FTOTINC>181600</FTOTINC></row>
|
||||
<row><famindex>156</famindex><AGE>70</AGE><FTOTINC>23800</FTOTINC></row>
|
||||
<row><famindex>157</famindex><AGE>65</AGE><FTOTINC>132200</FTOTINC></row>
|
||||
<row><famindex>158</famindex><AGE>32</AGE><FTOTINC>217000</FTOTINC></row>
|
||||
<row><famindex>159</famindex><AGE>48</AGE><FTOTINC>32800</FTOTINC></row>
|
||||
<row><famindex>160</famindex><AGE>47</AGE><FTOTINC>55000</FTOTINC></row>
|
||||
<row><famindex>161</famindex><AGE>60</AGE><FTOTINC>88000</FTOTINC></row>
|
||||
<row><famindex>162</famindex><AGE>75</AGE><FTOTINC>46300</FTOTINC></row>
|
||||
<row><famindex>163</famindex><AGE>55</AGE><FTOTINC>31500</FTOTINC></row>
|
||||
<row><famindex>164</famindex><AGE>73</AGE><FTOTINC>8100</FTOTINC></row>
|
||||
<row><famindex>165</famindex><AGE>40</AGE><FTOTINC>45000</FTOTINC></row>
|
||||
<row><famindex>166</famindex><AGE>65</AGE><FTOTINC>47000</FTOTINC></row>
|
||||
<row><famindex>167</famindex><AGE>84</AGE><FTOTINC>11700</FTOTINC></row>
|
||||
<row><famindex>168</famindex><AGE>71</AGE><FTOTINC>9800</FTOTINC></row>
|
||||
<row><famindex>169</famindex><AGE>83</AGE><FTOTINC>55400</FTOTINC></row>
|
||||
<row><famindex>170</famindex><AGE>51</AGE><FTOTINC>77000</FTOTINC></row>
|
||||
<row><famindex>171</famindex><AGE>40</AGE><FTOTINC>34100</FTOTINC></row>
|
||||
<row><famindex>172</famindex><AGE>39</AGE><FTOTINC>130000</FTOTINC></row>
|
||||
<row><famindex>173</famindex><AGE>27</AGE><FTOTINC>82000</FTOTINC></row>
|
||||
<row><famindex>174</famindex><AGE>36</AGE><FTOTINC>54000</FTOTINC></row>
|
||||
<row><famindex>175</famindex><AGE>81</AGE><FTOTINC>29630</FTOTINC></row>
|
||||
<row><famindex>176</famindex><AGE>35</AGE><FTOTINC>93800</FTOTINC></row>
|
||||
<row><famindex>177</famindex><AGE>59</AGE><FTOTINC>122900</FTOTINC></row>
|
||||
<row><famindex>178</famindex><AGE>26</AGE><FTOTINC>65000</FTOTINC></row>
|
||||
<row><famindex>179</famindex><AGE>66</AGE><FTOTINC>108000</FTOTINC></row>
|
||||
<row><famindex>180</famindex><AGE>46</AGE><FTOTINC>2500</FTOTINC></row>
|
||||
<row><famindex>181</famindex><AGE>28</AGE><FTOTINC>42000</FTOTINC></row>
|
||||
<row><famindex>182</famindex><AGE>25</AGE><FTOTINC>77000</FTOTINC></row>
|
||||
<row><famindex>183</famindex><AGE>66</AGE><FTOTINC>9000</FTOTINC></row>
|
||||
<row><famindex>184</famindex><AGE>58</AGE><FTOTINC>80500</FTOTINC></row>
|
||||
<row><famindex>185</famindex><AGE>56</AGE><FTOTINC>84000</FTOTINC></row>
|
||||
<row><famindex>186</famindex><AGE>61</AGE><FTOTINC>85000</FTOTINC></row>
|
||||
<row><famindex>187</famindex><AGE>32</AGE><FTOTINC>156000</FTOTINC></row>
|
||||
<row><famindex>188</famindex><AGE>86</AGE><FTOTINC>359400</FTOTINC></row>
|
||||
<row><famindex>189</famindex><AGE>60</AGE><FTOTINC>99000</FTOTINC></row>
|
||||
<row><famindex>190</famindex><AGE>26</AGE><FTOTINC>42000</FTOTINC></row>
|
||||
<row><famindex>191</famindex><AGE>62</AGE><FTOTINC>56000</FTOTINC></row>
|
||||
<row><famindex>192</famindex><AGE>32</AGE><FTOTINC>78000</FTOTINC></row>
|
||||
<row><famindex>193</famindex><AGE>26</AGE><FTOTINC>35000</FTOTINC></row>
|
||||
<row><famindex>194</famindex><AGE>50</AGE><FTOTINC>27000</FTOTINC></row>
|
||||
<row><famindex>195</famindex><AGE>28</AGE><FTOTINC>70000</FTOTINC></row>
|
||||
<row><famindex>196</famindex><AGE>32</AGE><FTOTINC>38000</FTOTINC></row>
|
||||
<row><famindex>197</famindex><AGE>59</AGE><FTOTINC>120000</FTOTINC></row>
|
||||
<row><famindex>198</famindex><AGE>64</AGE><FTOTINC>9600</FTOTINC></row>
|
||||
<row><famindex>199</famindex><AGE>33</AGE><FTOTINC>107200</FTOTINC></row>
|
||||
<row><famindex>200</famindex><AGE>60</AGE><FTOTINC>70800</FTOTINC></row>
|
||||
</rows>
|
||||
@@ -0,0 +1,201 @@
|
||||
famindex,AGE,FTOTINC
|
||||
1,45,114000
|
||||
2,37,280000
|
||||
3,60,184000
|
||||
4,70,250100
|
||||
5,79,33040
|
||||
6,60,168000
|
||||
7,56,557000
|
||||
8,69,84500
|
||||
9,54,128800
|
||||
10,72,28500
|
||||
11,26,85000
|
||||
12,60,52000
|
||||
13,54,24000
|
||||
14,51,316600
|
||||
15,35,261590
|
||||
16,62,41200
|
||||
17,28,11000
|
||||
18,66,15500
|
||||
19,75,37100
|
||||
20,57,137000
|
||||
21,69,80000
|
||||
22,78,376100
|
||||
23,47,10000
|
||||
24,84,31400
|
||||
25,75,40000
|
||||
26,23,600
|
||||
27,43,59000
|
||||
28,87,26000
|
||||
29,66,22000
|
||||
30,62,103600
|
||||
31,25,18100
|
||||
32,45,25000
|
||||
33,65,106000
|
||||
34,63,111000
|
||||
35,68,13700
|
||||
36,28,160400
|
||||
37,49,206600
|
||||
38,58,67500
|
||||
39,74,115000
|
||||
40,70,107800
|
||||
41,79,28100
|
||||
42,22,36000
|
||||
43,69,92920
|
||||
44,27,91000
|
||||
45,60,89000
|
||||
46,69,309400
|
||||
47,34,151500
|
||||
48,35,71000
|
||||
49,42,94000
|
||||
50,64,94300
|
||||
51,40,148000
|
||||
52,95,1400
|
||||
53,39,75000
|
||||
54,63,89000
|
||||
55,54,317000
|
||||
56,53,57200
|
||||
57,57,49000
|
||||
58,44,7500
|
||||
59,87,50100
|
||||
60,60,8000
|
||||
61,55,48000
|
||||
62,32,24500
|
||||
63,87,25000
|
||||
64,67,68200
|
||||
65,90,32400
|
||||
66,23,41100
|
||||
67,64,77000
|
||||
68,32,86700
|
||||
69,49,15200
|
||||
70,54,573000
|
||||
71,69,69000
|
||||
72,64,147000
|
||||
73,57,111600
|
||||
74,53,31200
|
||||
75,40,151500
|
||||
76,58,52300
|
||||
77,42,13500
|
||||
78,75,20900
|
||||
79,33,133800
|
||||
80,39,83000
|
||||
81,24,80000
|
||||
82,59,16000
|
||||
83,48,60000
|
||||
84,45,162200
|
||||
85,83,3000
|
||||
86,76,147900
|
||||
87,40,78300
|
||||
88,61,240000
|
||||
89,35,85000
|
||||
90,46,80000
|
||||
91,46,112200
|
||||
92,30,130000
|
||||
93,25,19550
|
||||
94,65,148000
|
||||
95,57,129400
|
||||
96,39,94000
|
||||
97,21,31100
|
||||
98,56,100000
|
||||
99,38,40000
|
||||
100,76,63310
|
||||
101,59,128000
|
||||
102,25,45000
|
||||
103,43,136800
|
||||
104,62,125000
|
||||
105,59,94400
|
||||
106,81,86300
|
||||
107,39,150100
|
||||
108,28,34000
|
||||
109,34,79640
|
||||
110,60,35000
|
||||
111,45,337000
|
||||
112,31,100000
|
||||
113,67,63400
|
||||
114,64,141600
|
||||
115,86,30100
|
||||
116,83,44300
|
||||
117,61,122000
|
||||
118,58,43000
|
||||
119,79,104000
|
||||
120,61,9600
|
||||
121,44,66100
|
||||
122,26,38100
|
||||
123,32,103000
|
||||
124,22,59000
|
||||
125,36,56000
|
||||
126,84,114300
|
||||
127,24,68300
|
||||
128,76,84600
|
||||
129,57,161400
|
||||
130,46,18800
|
||||
131,53,45300
|
||||
132,26,85000
|
||||
133,67,40600
|
||||
134,36,88000
|
||||
135,57,134300
|
||||
136,30,54000
|
||||
137,41,45600
|
||||
138,74,43210
|
||||
139,22,10000
|
||||
140,51,160000
|
||||
141,51,130400
|
||||
142,47,45000
|
||||
143,25,34000
|
||||
144,37,78000
|
||||
145,62,18500
|
||||
146,44,169000
|
||||
147,41,86000
|
||||
148,66,446000
|
||||
149,40,55000
|
||||
150,63,41400
|
||||
151,41,29000
|
||||
152,22,38000
|
||||
153,50,83460
|
||||
154,69,16400
|
||||
155,29,181600
|
||||
156,70,23800
|
||||
157,65,132200
|
||||
158,32,217000
|
||||
159,48,32800
|
||||
160,47,55000
|
||||
161,60,88000
|
||||
162,75,46300
|
||||
163,55,31500
|
||||
164,73,8100
|
||||
165,40,45000
|
||||
166,65,47000
|
||||
167,84,11700
|
||||
168,71,9800
|
||||
169,83,55400
|
||||
170,51,77000
|
||||
171,40,34100
|
||||
172,39,130000
|
||||
173,27,82000
|
||||
174,36,54000
|
||||
175,81,29630
|
||||
176,35,93800
|
||||
177,59,122900
|
||||
178,26,65000
|
||||
179,66,108000
|
||||
180,46,2500
|
||||
181,28,42000
|
||||
182,25,77000
|
||||
183,66,9000
|
||||
184,58,80500
|
||||
185,56,84000
|
||||
186,61,85000
|
||||
187,32,156000
|
||||
188,86,359400
|
||||
189,60,99000
|
||||
190,26,42000
|
||||
191,62,56000
|
||||
192,32,78000
|
||||
193,26,35000
|
||||
194,50,27000
|
||||
195,28,70000
|
||||
196,32,38000
|
||||
197,59,120000
|
||||
198,64,9600
|
||||
199,33,107200
|
||||
200,60,70800
|
||||
|
@@ -0,0 +1,26 @@
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
|
||||
|
||||
# Load CSV
|
||||
people = pd.read_csv('income-scraped.csv')
|
||||
|
||||
# See first rows.
|
||||
people.head()
|
||||
|
||||
# Subset.
|
||||
over40 = people[people.AGE > 40]
|
||||
over40.head()
|
||||
|
||||
# New column.
|
||||
people['isover40'] = people['AGE'] > 40
|
||||
people['agegrp'] = (people['AGE'] / 10).apply(np.floor) * 10
|
||||
|
||||
|
||||
# Median.
|
||||
people['FTOTINC'].median()
|
||||
|
||||
|
||||
# Grouped median.
|
||||
people.groupby(['isover40'])['FTOTINC'].median()
|
||||
people.groupby(['agegrp'])['FTOTINC'].median()
|
||||
@@ -0,0 +1,34 @@
|
||||
from bs4 import BeautifulSoup
|
||||
import urllib.request
|
||||
|
||||
base_url = 'http://book.flowingdata.com/vt2/ch3/scraping/'
|
||||
|
||||
# Header
|
||||
print("famindex,AGE,FTOTINC")
|
||||
|
||||
for i in range(1, 21):
|
||||
|
||||
# Page URL, based on page number
|
||||
page_url = base_url + 'family-income-page'+str(i)+'.html'
|
||||
|
||||
# Open the page
|
||||
req = urllib.request.Request(page_url)
|
||||
with urllib.request.urlopen(req) as response:
|
||||
|
||||
# Save page contents.
|
||||
the_page = response.read()
|
||||
|
||||
# Parse.
|
||||
soup = BeautifulSoup(the_page, features="html.parser")
|
||||
|
||||
# Get the table rows
|
||||
rows = soup.find_all("tr")
|
||||
|
||||
# Save each row of data
|
||||
for j in range(1, len(rows)):
|
||||
|
||||
# Get the cells in a row
|
||||
cells = rows[j].findAll("td")
|
||||
|
||||
# Comma-delimited row
|
||||
print(cells[0].string + "," + cells[1].string + "," + cells[2].string)
|
||||
@@ -0,0 +1,201 @@
|
||||
famindex,AGE,FTOTINC
|
||||
1,45,114000
|
||||
2,37,280000
|
||||
3,60,184000
|
||||
4,70,250100
|
||||
5,79,33040
|
||||
6,60,168000
|
||||
7,56,557000
|
||||
8,69,84500
|
||||
9,54,128800
|
||||
10,72,28500
|
||||
11,26,85000
|
||||
12,60,52000
|
||||
13,54,24000
|
||||
14,51,316600
|
||||
15,35,261590
|
||||
16,62,41200
|
||||
17,28,11000
|
||||
18,66,15500
|
||||
19,75,37100
|
||||
20,57,137000
|
||||
21,69,80000
|
||||
22,78,376100
|
||||
23,47,10000
|
||||
24,84,31400
|
||||
25,75,40000
|
||||
26,23,600
|
||||
27,43,59000
|
||||
28,87,26000
|
||||
29,66,22000
|
||||
30,62,103600
|
||||
31,25,18100
|
||||
32,45,25000
|
||||
33,65,106000
|
||||
34,63,111000
|
||||
35,68,13700
|
||||
36,28,160400
|
||||
37,49,206600
|
||||
38,58,67500
|
||||
39,74,115000
|
||||
40,70,107800
|
||||
41,79,28100
|
||||
42,22,36000
|
||||
43,69,92920
|
||||
44,27,91000
|
||||
45,60,89000
|
||||
46,69,309400
|
||||
47,34,151500
|
||||
48,35,71000
|
||||
49,42,94000
|
||||
50,64,94300
|
||||
51,40,148000
|
||||
52,95,1400
|
||||
53,39,75000
|
||||
54,63,89000
|
||||
55,54,317000
|
||||
56,53,57200
|
||||
57,57,49000
|
||||
58,44,7500
|
||||
59,87,50100
|
||||
60,60,8000
|
||||
61,55,48000
|
||||
62,32,24500
|
||||
63,87,25000
|
||||
64,67,68200
|
||||
65,90,32400
|
||||
66,23,41100
|
||||
67,64,77000
|
||||
68,32,86700
|
||||
69,49,15200
|
||||
70,54,573000
|
||||
71,69,69000
|
||||
72,64,147000
|
||||
73,57,111600
|
||||
74,53,31200
|
||||
75,40,151500
|
||||
76,58,52300
|
||||
77,42,13500
|
||||
78,75,20900
|
||||
79,33,133800
|
||||
80,39,83000
|
||||
81,24,80000
|
||||
82,59,16000
|
||||
83,48,60000
|
||||
84,45,162200
|
||||
85,83,3000
|
||||
86,76,147900
|
||||
87,40,78300
|
||||
88,61,240000
|
||||
89,35,85000
|
||||
90,46,80000
|
||||
91,46,112200
|
||||
92,30,130000
|
||||
93,25,19550
|
||||
94,65,148000
|
||||
95,57,129400
|
||||
96,39,94000
|
||||
97,21,31100
|
||||
98,56,100000
|
||||
99,38,40000
|
||||
100,76,63310
|
||||
101,59,128000
|
||||
102,25,45000
|
||||
103,43,136800
|
||||
104,62,125000
|
||||
105,59,94400
|
||||
106,81,86300
|
||||
107,39,150100
|
||||
108,28,34000
|
||||
109,34,79640
|
||||
110,60,35000
|
||||
111,45,337000
|
||||
112,31,100000
|
||||
113,67,63400
|
||||
114,64,141600
|
||||
115,86,30100
|
||||
116,83,44300
|
||||
117,61,122000
|
||||
118,58,43000
|
||||
119,79,104000
|
||||
120,61,9600
|
||||
121,44,66100
|
||||
122,26,38100
|
||||
123,32,103000
|
||||
124,22,59000
|
||||
125,36,56000
|
||||
126,84,114300
|
||||
127,24,68300
|
||||
128,76,84600
|
||||
129,57,161400
|
||||
130,46,18800
|
||||
131,53,45300
|
||||
132,26,85000
|
||||
133,67,40600
|
||||
134,36,88000
|
||||
135,57,134300
|
||||
136,30,54000
|
||||
137,41,45600
|
||||
138,74,43210
|
||||
139,22,10000
|
||||
140,51,160000
|
||||
141,51,130400
|
||||
142,47,45000
|
||||
143,25,34000
|
||||
144,37,78000
|
||||
145,62,18500
|
||||
146,44,169000
|
||||
147,41,86000
|
||||
148,66,446000
|
||||
149,40,55000
|
||||
150,63,41400
|
||||
151,41,29000
|
||||
152,22,38000
|
||||
153,50,83460
|
||||
154,69,16400
|
||||
155,29,181600
|
||||
156,70,23800
|
||||
157,65,132200
|
||||
158,32,217000
|
||||
159,48,32800
|
||||
160,47,55000
|
||||
161,60,88000
|
||||
162,75,46300
|
||||
163,55,31500
|
||||
164,73,8100
|
||||
165,40,45000
|
||||
166,65,47000
|
||||
167,84,11700
|
||||
168,71,9800
|
||||
169,83,55400
|
||||
170,51,77000
|
||||
171,40,34100
|
||||
172,39,130000
|
||||
173,27,82000
|
||||
174,36,54000
|
||||
175,81,29630
|
||||
176,35,93800
|
||||
177,59,122900
|
||||
178,26,65000
|
||||
179,66,108000
|
||||
180,46,2500
|
||||
181,28,42000
|
||||
182,25,77000
|
||||
183,66,9000
|
||||
184,58,80500
|
||||
185,56,84000
|
||||
186,61,85000
|
||||
187,32,156000
|
||||
188,86,359400
|
||||
189,60,99000
|
||||
190,26,42000
|
||||
191,62,56000
|
||||
192,32,78000
|
||||
193,26,35000
|
||||
194,50,27000
|
||||
195,28,70000
|
||||
196,32,38000
|
||||
197,59,120000
|
||||
198,64,9600
|
||||
199,33,107200
|
||||
200,60,70800
|
||||
|
@@ -0,0 +1,77 @@
|
||||
#
|
||||
# Multi-line chart
|
||||
#
|
||||
|
||||
# Load data
|
||||
marstat <- read.csv("data/mar_w_age_all.tsv", sep="\t")
|
||||
head(marstat)
|
||||
unique(marstat$MARST)
|
||||
|
||||
# Subset married
|
||||
married <- marstat[marstat$MARST == 1,]
|
||||
|
||||
# Line chart for 2021
|
||||
married2021 <- married[married$YEAR == 2021,]
|
||||
par(las=1)
|
||||
plot(married2021$AGE, married2021$prop*100,
|
||||
ylim=c(0, 100),
|
||||
type="n",
|
||||
bty="n", xaxt="n", yaxt="n",
|
||||
xlab="", ylab="",
|
||||
main="Proportion of people married, by age")
|
||||
axis(1, tick=FALSE)
|
||||
axis(2,
|
||||
at=seq(0, 100, by=20),
|
||||
labels=paste0(seq(0, 100, by=20), "%"),
|
||||
tick=FALSE)
|
||||
grid()
|
||||
lines(married2021$AGE, married2021$prop*100,
|
||||
lwd=2,
|
||||
col="#b31dc2")
|
||||
|
||||
|
||||
|
||||
# All available years
|
||||
plot(married2021$AGE, married2021$prop*100,
|
||||
ylim=c(0, 100),
|
||||
type="n",
|
||||
bty="n", xaxt="n", yaxt="n",
|
||||
xlab="", ylab="",
|
||||
main="Proportion of people married, by age")
|
||||
axis(1, tick=FALSE)
|
||||
axis(2,
|
||||
at=seq(0, 100, by=20),
|
||||
labels=paste0(seq(0, 100, by=20), "%"),
|
||||
tick=FALSE)
|
||||
grid()
|
||||
abline(h=0, lwd=2)
|
||||
years <- unique(married$YEAR)
|
||||
|
||||
# Multiple lines with a for-loop
|
||||
for (yr in years) {
|
||||
curr <- married[married$YEAR == yr,]
|
||||
lines(curr$AGE, curr$prop*100,
|
||||
col="#b31dc2")
|
||||
}
|
||||
|
||||
# Change line width for each year
|
||||
for (yr in years) {
|
||||
curr <- married[married$YEAR == yr,]
|
||||
|
||||
if (yr == 1900) {
|
||||
lines(curr$AGE, curr$prop*100,
|
||||
lwd=3,
|
||||
col="green")
|
||||
} else {
|
||||
lines(curr$AGE, curr$prop*100,
|
||||
lwd=min(c(3, 15*1/(2021-yr+.5))),
|
||||
col="#b31dc2")
|
||||
}
|
||||
|
||||
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
@@ -0,0 +1,19 @@
|
||||
name,emmy_year,emmy_title,emmy_desc,grammy_year,grammy_title,grammy_desc,oscar_year,oscar_title,oscar_desc,tony_year,tony_title,tony_desc,completion_year,category
|
||||
Viola Davis,2015,,,2023,,,2017,,,2001,,,2023,
|
||||
Jennifer Hudson,2021,,,2009,,,2007,,,2022,,,2022,
|
||||
Alan Menken,2020,,,1991,,,1990,,,2012,,,2020,
|
||||
John Legend,2018,Outstanding Variety Special (Live),Jesus Christ Superstar Live in Concert,2006,Best R&B Album,Get Lifted,2015,Best Original Song ,"""Glory"" from Selma",2017,Best Revival of a Play,Jitney,2018,Singer/Composer/Producer
|
||||
Andrew Lloyd Webber,2018,Outstanding Variety Special (Live),Jesus Christ Superstar Live in Concert,1980,Best Cast Show Album,Evita,1996,Best Original Song,"""You Must Love Me"" from Evita",1980,Best Original Score,Evita,2018,Composer/Producer
|
||||
Tim Rice,2018,Outstanding Variety Special (Live),Jesus Christ Superstar Live in Concert,1980,Best Cast Show Album,Evita,1993,Best Original Song,"""A Whole New World"" from Aladdin",1980,Best Original Score,Evita,2018,Lyricist/Producer
|
||||
Robert Lopez,2008,Outstanding Achievement in Music Direction and Composition,Wonder Pets,2012,Best Musical Theater Album,The Book of Mormon: Original Broadway Cast Recording,2014,Best Original Song,"""Let It Go"" from Frozen",2004,Best Original Score,Avenue Q,2014,Composer
|
||||
Scott Rudin,1984,Outstanding Children's Program,He Makes Me Feel Like Dancin',2012,Best Musical Theater Album,The Book of Mormon: Original Broadway Cast Recording,2008,Best Picture,No Country For Old Men,1994,Best Musical,Passion,2012,Producer
|
||||
Whoopi Goldberg,2002,Outstanding Special Class Special,Beyond Tara: The Extraordinary Life of Hattie McDaniel (Host),1986,Best Comedy Recording,Whoopi Goldberg: Original Broadway Show Recording,1991,Best Actress in a Supporting Role,Ghost,2002,Best Musical,Thoroughly Modern Millie,2002,Comedian/Actress/Host
|
||||
Mel Brooks,1967,Outstanding Writing Achievement in Variety ,"The Sid Caesar, Imogene Coca, Carl Reiner, Howard Morris Special",1998,Best Spoken Comedy Album,The 2000 Year Old Man in the Year 2000,1968,Best Writing (Screenplay Written Directly for the Screen),The Producers,2001,Best Book of a Musical ,The Producers,2001,Writer/Composer/Actor
|
||||
Mike Nichols,2001,"Outstanding Directing for a Miniseries, Movie or a Special",Wit,1961,Best Comedy Performance,An Evening with Mike Nichols and Elaine May,1967,Best Director,The Graduate,1964,"Best Director, Dramatic",Barefoot in the Park,2001,Director/Comedian
|
||||
Jonathan Tunick,1982,Outstanding Achievement in Music Direction,Night of 100 Stars,1988,Best Instrumental Arrangement Accompanying Vocals,"""No One is Alone,"" Cleo Laine",1977,"Best Music, Original Song Score and Its Adaptation or Best Adaptation Score ",A Little Night Music,1997,Best Orchestrations,Titanic,1997,Composer/Conductor
|
||||
Marvin Hamlisch,1995,Outstanding Individual Achievement in Music Direction,Barbra: The Concert,1974,Song of the Year,"""The Way We Were""",1973,"Best Music, Original Dramatic Score",The Way We Were,1976,Best Musical Score ,A Chorus Line,1995,Composer
|
||||
Audrey Hepburn,1993,"Outstanding Individual Achievement, Informational Programming",Gardens of the World with Audrey Hepburn,1994,Best Spoken Word Album for Children,Audrey Hepburn's Enchanted Tales,1953,Best Actress in a Leading Role,Roman Holiday,1954,Best Actress in a Play,Ondine,1994,Actress
|
||||
John Gielgud,1991,Outstanding Lead Actor in a Miniseries or Special,Summer's Lease,1979,"Best Spoken Word, Documentary or Drama Recording",Ages of Man,1981,Best Actor in a Supporting Role,Arthur,1961,Outstanding Foreign Company,The Importance of Being Earnest,1991,Actor/Director
|
||||
Helen Hayes,1953,Best Actress,"Schlitz Playhouse of Stars for the episode ""Not a Chance""",1977,Best Spoken Word Recording,Great American Documents,1932,Best Actress in a Leading Role,The Sin of Madelon Claudet,1947,"Best Actress, Dramatic",Happy Birthday,1977,Actress
|
||||
Rita Moreno,1977,Outstanding Continuing or Single Performance by a Supporting Actress in Variety or Music,The Muppet Show,1972,Best Recording for Children,The Electric Company,1961,Best Actress in a Supporting Role,West Side Story,1975,Best Featured or Supporting Actress in a Play,The Ritz,1977,Actress/Singer
|
||||
Richard Rodgers,1962,Outstanding Achievement in Original Music Composed,Winston Churchill: The Valiant Years,1960,Best Show Album (Original Cast),The Sound of Music,1945,Best Song,"""It Might as Well Be Spring"" from State Fair",1950,Best Musical,South Pacific,1962,Composer
|
||||
|
@@ -0,0 +1,45 @@
|
||||
year,winner,hotdogs,country,record
|
||||
1980,Paul Siederman & Joe Baldini,9.75,United States,0
|
||||
1981,Thomas DeBerry ,11,United States,1
|
||||
1982,Steven Abrams ,11.1,United States,1
|
||||
1983,Emil Gomez,10.5,Mexico,0
|
||||
1984,Birgit Felden ,9.5,Germany,0
|
||||
1985,Oscar Rodriguez ,11.75,United States,1
|
||||
1986,Mark Heller ,15.5,United States,1
|
||||
1987,Don Wolfman ,13.5,United States,0
|
||||
1988,Jay Green ,10,United States,0
|
||||
1989,Jay Green ,15.5,United States,0
|
||||
1990,Mike DeVito & Jay Green,15,United States,0
|
||||
1991,Frank Dellarosa ,21,United States,1
|
||||
1992,Frank Dellarosa ,19,United States,0
|
||||
1993,Mike DeVito ,17,United States,0
|
||||
1994,Mike DeVito ,20,United States,0
|
||||
1995,Edward Krachie ,19.5,United States,0
|
||||
1996,Edward Krachie ,22,United States,1
|
||||
1997,Hirofumi Nakajima ,24.5,Japan,1
|
||||
1998,Hirofumi Nakajima ,19,Japan,0
|
||||
1999,Steve Keiner ,21.5,United States,0
|
||||
2000,"Kazutoyo ""The Rabbit"" Arai ",25.13,Japan,1
|
||||
2001,Takeru Kobayashi ,50,Japan,1
|
||||
2002,Takeru Kobayashi ,50.5,Japan,1
|
||||
2003,Takeru Kobayashi ,44.5,Japan,0
|
||||
2004,Takeru Kobayashi ,53.5,Japan,1
|
||||
2005,Takeru Kobayashi ,49,Japan,0
|
||||
2006,"Takeru ""Tsunami"" Kobayashi ",53.75,Japan,1
|
||||
2007,Joey Chestnut ,66,United States,1
|
||||
2008,Joey Chestnut ,59,United States,0
|
||||
2009,Joey Chestnut ,68,United States,1
|
||||
2010,Joey Chestnut ,54,United States,0
|
||||
2011,Joey Chestnut ,62,United States,0
|
||||
2012,Joey Chestnut ,68,United States,0
|
||||
2013,Joey Chestnut ,69,United States,1
|
||||
2014,Joey Chestnut ,61,United States,0
|
||||
2015,Matt Stonie,62,United States,0
|
||||
2016,Joey Chestnut ,70,United States,1
|
||||
2017,Joey Chestnut ,72,United States,1
|
||||
2018,Joey Chestnut ,74,United States,1
|
||||
2019,Joey Chestnut ,71,United States,0
|
||||
2020,Joey Chestnut ,75,United States,1
|
||||
2021,Joey Chestnut ,76,United States,1
|
||||
2022,Joey Chestnut ,63,United States,0
|
||||
2023,Joey Chestnut ,62,United States,0
|
||||
|
Binary file not shown.
File diff suppressed because it is too large.
Load diff
@@ -0,0 +1,289 @@
|
||||
"MONTH" "HOUR" "n_all" "n_drunk_all" "n_ped_all" "n_weather_all" "n_rural_all" "n_drunk_rural" "n_ped_rural" "n_weather_rural" "n_urban" "n_drunk_urban" "n_ped_urban" "n_weather_urban" "pct_drunk_all" "pct_ped_all" "pct_weather_all" "pct_drunk_rural" "pct_ped_rural" "pct_weather_rural" "pct_drunk_urban" "pct_ped_urban" "pct_weather_urban"
|
||||
1 0 86 49 17 25 35 23 2 13 51 26 15 12 0.57 0.198 0.291 0.657 0.057 0.371 0.51 0.294 0.235
|
||||
1 2 103 58 23 33 36 22 3 12 67 36 20 21 0.563 0.223 0.32 0.611 0.083 0.333 0.537 0.299 0.313
|
||||
1 3 70 36 12 29 28 16 2 11 42 20 10 18 0.514 0.171 0.414 0.571 0.071 0.393 0.476 0.238 0.429
|
||||
1 4 57 27 11 20 17 6 2 3 40 21 9 17 0.474 0.193 0.351 0.353 0.118 0.176 0.525 0.225 0.425
|
||||
1 5 69 10 23 33 34 1 5 17 35 9 18 16 0.145 0.333 0.478 0.029 0.147 0.5 0.257 0.514 0.457
|
||||
1 6 110 13 37 50 55 9 7 31 55 4 30 19 0.118 0.336 0.455 0.164 0.127 0.564 0.073 0.545 0.345
|
||||
1 7 107 11 22 53 58 5 2 28 49 6 20 25 0.103 0.206 0.495 0.086 0.034 0.483 0.122 0.408 0.51
|
||||
1 8 80 8 7 36 43 4 1 22 37 4 6 14 0.1 0.088 0.45 0.093 0.023 0.512 0.108 0.162 0.378
|
||||
1 9 67 3 7 28 37 1 1 21 30 2 6 7 0.045 0.104 0.418 0.027 0.027 0.568 0.067 0.2 0.233
|
||||
1 11 69 6 8 27 28 3 2 15 41 3 6 12 0.087 0.116 0.391 0.107 0.071 0.536 0.073 0.146 0.293
|
||||
1 12 77 8 8 28 40 2 2 19 37 6 6 9 0.104 0.104 0.364 0.05 0.05 0.475 0.162 0.162 0.243
|
||||
1 13 102 10 16 45 57 6 3 26 45 4 13 19 0.098 0.157 0.441 0.105 0.053 0.456 0.089 0.289 0.422
|
||||
1 14 108 12 17 33 55 7 5 21 53 5 12 12 0.111 0.157 0.306 0.127 0.091 0.382 0.094 0.226 0.226
|
||||
1 15 79 16 14 21 39 11 2 13 40 5 12 8 0.203 0.177 0.266 0.282 0.051 0.333 0.125 0.3 0.2
|
||||
1 16 108 21 12 39 67 13 7 32 41 8 5 7 0.194 0.111 0.361 0.194 0.104 0.478 0.195 0.122 0.171
|
||||
1 17 132 27 43 48 62 14 3 23 70 13 40 25 0.205 0.326 0.364 0.226 0.048 0.371 0.186 0.571 0.357
|
||||
1 18 192 35 77 52 70 16 9 25 122 19 68 27 0.182 0.401 0.271 0.229 0.129 0.357 0.156 0.557 0.221
|
||||
1 19 132 38 63 41 55 21 16 22 77 17 47 19 0.288 0.477 0.311 0.382 0.291 0.4 0.221 0.61 0.247
|
||||
1 20 123 37 45 34 43 18 6 14 80 19 39 20 0.301 0.366 0.276 0.419 0.14 0.326 0.238 0.488 0.25
|
||||
1 21 114 38 33 37 49 22 8 20 65 16 25 17 0.333 0.289 0.325 0.449 0.163 0.408 0.246 0.385 0.262
|
||||
1 22 114 45 35 35 48 24 7 14 66 21 28 21 0.395 0.307 0.307 0.5 0.146 0.292 0.318 0.424 0.318
|
||||
1 23 88 39 28 31 29 16 3 12 59 23 25 19 0.443 0.318 0.352 0.552 0.103 0.414 0.39 0.424 0.322
|
||||
2 0 66 38 15 20 31 20 4 13 35 18 11 7 0.576 0.227 0.303 0.645 0.129 0.419 0.514 0.314 0.2
|
||||
2 1 76 51 15 18 28 19 2 6 48 32 13 12 0.671 0.197 0.237 0.679 0.071 0.214 0.667 0.271 0.25
|
||||
2 2 82 49 20 23 29 19 1 7 53 30 19 16 0.598 0.244 0.28 0.655 0.034 0.241 0.566 0.358 0.302
|
||||
2 3 59 37 7 22 28 15 3 9 31 22 4 13 0.627 0.119 0.373 0.536 0.107 0.321 0.71 0.129 0.419
|
||||
2 4 38 14 7 15 18 6 2 7 20 8 5 8 0.368 0.184 0.395 0.333 0.111 0.389 0.4 0.25 0.4
|
||||
2 5 62 19 16 24 27 11 2 11 35 8 14 13 0.306 0.258 0.387 0.407 0.074 0.407 0.229 0.4 0.371
|
||||
2 6 80 20 17 30 42 11 2 15 38 9 15 15 0.25 0.212 0.375 0.262 0.048 0.357 0.237 0.395 0.395
|
||||
2 7 76 11 7 33 48 7 3 20 28 4 4 13 0.145 0.092 0.434 0.146 0.062 0.417 0.143 0.143 0.464
|
||||
2 8 60 6 8 23 39 5 4 16 21 1 4 7 0.1 0.133 0.383 0.128 0.103 0.41 0.048 0.19 0.333
|
||||
2 9 62 8 6 26 34 4 1 17 28 4 5 9 0.129 0.097 0.419 0.118 0.029 0.5 0.143 0.179 0.321
|
||||
2 12 86 12 10 21 42 8 1 8 44 4 9 13 0.14 0.116 0.244 0.19 0.024 0.19 0.091 0.205 0.295
|
||||
2 13 81 5 8 24 51 4 4 19 30 1 4 5 0.062 0.099 0.296 0.078 0.078 0.373 0.033 0.133 0.167
|
||||
2 14 93 12 10 27 59 10 3 21 34 2 7 6 0.129 0.108 0.29 0.169 0.051 0.356 0.059 0.206 0.176
|
||||
2 15 107 18 12 24 68 14 1 15 39 4 11 9 0.168 0.112 0.224 0.206 0.015 0.221 0.103 0.282 0.231
|
||||
2 16 96 18 12 31 56 12 2 23 40 6 10 8 0.188 0.125 0.323 0.214 0.036 0.411 0.15 0.25 0.2
|
||||
2 17 91 23 15 33 57 12 4 23 34 11 11 10 0.253 0.165 0.363 0.211 0.07 0.404 0.324 0.324 0.294
|
||||
2 18 125 25 58 36 45 11 12 10 80 14 46 26 0.2 0.464 0.288 0.244 0.267 0.222 0.175 0.575 0.325
|
||||
2 19 121 27 48 29 43 16 6 14 78 11 42 15 0.223 0.397 0.24 0.372 0.14 0.326 0.141 0.538 0.192
|
||||
2 20 115 31 43 32 52 20 10 21 63 11 33 11 0.27 0.374 0.278 0.385 0.192 0.404 0.175 0.524 0.175
|
||||
2 21 99 40 37 27 50 22 10 15 49 18 27 12 0.404 0.374 0.273 0.44 0.2 0.3 0.367 0.551 0.245
|
||||
2 22 78 24 27 21 34 14 3 10 44 10 24 11 0.308 0.346 0.269 0.412 0.088 0.294 0.227 0.545 0.25
|
||||
2 23 71 34 14 24 43 23 4 18 28 11 10 6 0.479 0.197 0.338 0.535 0.093 0.419 0.393 0.357 0.214
|
||||
3 0 98 47 21 32 37 17 4 16 61 30 17 16 0.48 0.214 0.327 0.459 0.108 0.432 0.492 0.279 0.262
|
||||
3 3 72 45 13 26 34 19 7 11 38 26 6 15 0.625 0.181 0.361 0.559 0.206 0.324 0.684 0.158 0.395
|
||||
3 4 57 26 8 18 28 14 1 9 29 12 7 9 0.456 0.14 0.316 0.5 0.036 0.321 0.414 0.241 0.31
|
||||
3 5 68 15 18 32 26 8 1 15 42 7 17 17 0.221 0.265 0.471 0.308 0.038 0.577 0.167 0.405 0.405
|
||||
3 6 102 19 29 46 51 13 5 25 51 6 24 21 0.186 0.284 0.451 0.255 0.098 0.49 0.118 0.471 0.412
|
||||
3 7 91 14 11 41 51 7 2 23 40 7 9 18 0.154 0.121 0.451 0.137 0.039 0.451 0.175 0.225 0.45
|
||||
3 8 83 3 11 38 50 2 1 25 33 1 10 13 0.036 0.133 0.458 0.04 0.02 0.5 0.03 0.303 0.394
|
||||
3 9 71 9 9 27 38 4 3 16 33 5 6 11 0.127 0.127 0.38 0.105 0.079 0.421 0.152 0.182 0.333
|
||||
3 10 85 7 15 33 43 4 2 21 42 3 13 12 0.082 0.176 0.388 0.093 0.047 0.488 0.071 0.31 0.286
|
||||
3 11 86 7 8 27 42 5 1 17 44 2 7 10 0.081 0.093 0.314 0.119 0.024 0.405 0.045 0.159 0.227
|
||||
3 12 108 12 11 37 57 3 2 24 51 9 9 13 0.111 0.102 0.343 0.053 0.035 0.421 0.176 0.176 0.255
|
||||
3 13 101 13 13 29 42 6 1 17 59 7 12 12 0.129 0.129 0.287 0.143 0.024 0.405 0.119 0.203 0.203
|
||||
3 15 118 16 11 33 61 12 2 14 57 4 9 19 0.136 0.093 0.28 0.197 0.033 0.23 0.07 0.158 0.333
|
||||
3 16 112 27 13 32 50 17 1 16 62 10 12 16 0.241 0.116 0.286 0.34 0.02 0.32 0.161 0.194 0.258
|
||||
3 17 114 38 10 31 62 25 2 20 52 13 8 11 0.333 0.088 0.272 0.403 0.032 0.323 0.25 0.154 0.212
|
||||
3 18 115 34 17 32 62 21 4 16 53 13 13 16 0.296 0.148 0.278 0.339 0.065 0.258 0.245 0.245 0.302
|
||||
3 19 127 34 45 41 58 20 8 18 69 14 37 23 0.268 0.354 0.323 0.345 0.138 0.31 0.203 0.536 0.333
|
||||
3 20 178 54 75 38 72 31 14 16 106 23 61 22 0.303 0.421 0.213 0.431 0.194 0.222 0.217 0.575 0.208
|
||||
3 21 119 39 37 37 55 21 7 22 64 18 30 15 0.328 0.311 0.311 0.382 0.127 0.4 0.281 0.469 0.234
|
||||
3 22 106 47 37 26 32 16 6 11 74 31 31 15 0.443 0.349 0.245 0.5 0.188 0.344 0.419 0.419 0.203
|
||||
3 23 90 42 19 23 36 17 2 12 54 25 17 11 0.467 0.211 0.256 0.472 0.056 0.333 0.463 0.315 0.204
|
||||
4 0 77 38 17 29 34 19 4 13 43 19 13 16 0.494 0.221 0.377 0.559 0.118 0.382 0.442 0.302 0.372
|
||||
4 1 92 48 19 25 35 15 5 12 57 33 14 13 0.522 0.207 0.272 0.429 0.143 0.343 0.579 0.246 0.228
|
||||
4 2 83 54 13 30 25 19 1 11 58 35 12 19 0.651 0.157 0.361 0.76 0.04 0.44 0.603 0.207 0.328
|
||||
4 3 73 38 10 22 35 20 2 10 38 18 8 12 0.521 0.137 0.301 0.571 0.057 0.286 0.474 0.211 0.316
|
||||
4 4 63 25 13 21 27 10 5 11 36 15 8 10 0.397 0.206 0.333 0.37 0.185 0.407 0.417 0.222 0.278
|
||||
4 5 80 19 14 19 40 10 2 9 40 9 12 10 0.238 0.175 0.238 0.25 0.05 0.225 0.225 0.3 0.25
|
||||
4 6 67 9 14 26 40 3 5 16 27 6 9 10 0.134 0.209 0.388 0.075 0.125 0.4 0.222 0.333 0.37
|
||||
4 7 83 14 9 28 49 10 2 17 34 4 7 11 0.169 0.108 0.337 0.204 0.041 0.347 0.118 0.206 0.324
|
||||
4 8 50 6 9 17 25 5 1 10 25 1 8 7 0.12 0.18 0.34 0.2 0.04 0.4 0.04 0.32 0.28
|
||||
4 9 56 3 5 20 29 2 1 12 27 1 4 8 0.054 0.089 0.357 0.069 0.034 0.414 0.037 0.148 0.296
|
||||
4 10 72 7 12 18 33 5 3 6 39 2 9 12 0.097 0.167 0.25 0.152 0.091 0.182 0.051 0.231 0.308
|
||||
4 11 83 9 8 24 50 7 2 13 33 2 6 11 0.108 0.096 0.289 0.14 0.04 0.26 0.061 0.182 0.333
|
||||
4 12 90 11 8 16 49 7 3 13 41 4 5 3 0.122 0.089 0.178 0.143 0.061 0.265 0.098 0.122 0.073
|
||||
4 13 119 18 14 36 58 7 3 19 61 11 11 17 0.151 0.118 0.303 0.121 0.052 0.328 0.18 0.18 0.279
|
||||
4 15 126 17 11 34 75 12 2 22 51 5 9 12 0.135 0.087 0.27 0.16 0.027 0.293 0.098 0.176 0.235
|
||||
4 16 132 18 9 30 75 9 1 19 57 9 8 11 0.136 0.068 0.227 0.12 0.013 0.253 0.158 0.14 0.193
|
||||
4 17 142 42 14 32 83 28 5 20 59 14 9 12 0.296 0.099 0.225 0.337 0.06 0.241 0.237 0.153 0.203
|
||||
4 19 114 41 15 23 59 26 1 13 55 15 14 10 0.36 0.132 0.202 0.441 0.017 0.22 0.273 0.255 0.182
|
||||
4 20 179 60 62 50 75 39 8 22 104 21 54 28 0.335 0.346 0.279 0.52 0.107 0.293 0.202 0.519 0.269
|
||||
4 21 144 50 45 37 55 23 8 10 89 27 37 27 0.347 0.312 0.257 0.418 0.145 0.182 0.303 0.416 0.303
|
||||
4 22 133 62 40 42 45 25 5 14 88 37 35 28 0.466 0.301 0.316 0.556 0.111 0.311 0.42 0.398 0.318
|
||||
4 23 118 60 21 36 60 38 5 18 58 22 16 18 0.508 0.178 0.305 0.633 0.083 0.3 0.379 0.276 0.31
|
||||
5 0 125 61 28 29 55 32 6 13 70 29 22 16 0.488 0.224 0.232 0.582 0.109 0.236 0.414 0.314 0.229
|
||||
5 1 110 69 18 35 48 31 4 15 62 38 14 20 0.627 0.164 0.318 0.646 0.083 0.312 0.613 0.226 0.323
|
||||
5 2 105 65 15 28 52 34 2 14 53 31 13 14 0.619 0.143 0.267 0.654 0.038 0.269 0.585 0.245 0.264
|
||||
5 3 91 57 13 29 36 24 1 11 55 33 12 18 0.626 0.143 0.319 0.667 0.028 0.306 0.6 0.218 0.327
|
||||
5 4 70 32 9 22 37 19 3 13 33 13 6 9 0.457 0.129 0.314 0.514 0.081 0.351 0.394 0.182 0.273
|
||||
5 5 91 27 18 30 51 16 5 18 40 11 13 12 0.297 0.198 0.33 0.314 0.098 0.353 0.275 0.325 0.3
|
||||
5 7 97 15 9 27 56 8 2 17 41 7 7 10 0.155 0.093 0.278 0.143 0.036 0.304 0.171 0.171 0.244
|
||||
5 8 83 6 10 25 45 4 3 18 38 2 7 7 0.072 0.12 0.301 0.089 0.067 0.4 0.053 0.184 0.184
|
||||
5 9 85 11 5 22 48 9 1 14 37 2 4 8 0.129 0.059 0.259 0.188 0.021 0.292 0.054 0.108 0.216
|
||||
5 10 91 9 7 22 54 4 4 15 37 5 3 7 0.099 0.077 0.242 0.074 0.074 0.278 0.135 0.081 0.189
|
||||
5 11 98 16 13 25 59 8 6 17 39 8 7 8 0.163 0.133 0.255 0.136 0.102 0.288 0.205 0.179 0.205
|
||||
5 13 132 18 14 34 76 12 6 24 56 6 8 10 0.136 0.106 0.258 0.158 0.079 0.316 0.107 0.143 0.179
|
||||
5 15 143 20 17 27 78 10 2 18 65 10 15 9 0.14 0.119 0.189 0.128 0.026 0.231 0.154 0.231 0.138
|
||||
5 16 170 39 23 42 103 28 5 30 67 11 18 12 0.229 0.135 0.247 0.272 0.049 0.291 0.164 0.269 0.179
|
||||
5 17 158 47 11 36 90 30 1 22 68 17 10 14 0.297 0.07 0.228 0.333 0.011 0.244 0.25 0.147 0.206
|
||||
5 18 146 54 13 45 89 40 3 29 57 14 10 16 0.37 0.089 0.308 0.449 0.034 0.326 0.246 0.175 0.281
|
||||
5 19 126 55 11 29 69 28 3 21 57 27 8 8 0.437 0.087 0.23 0.406 0.043 0.304 0.474 0.14 0.14
|
||||
5 20 155 57 49 39 69 34 10 16 86 23 39 23 0.368 0.316 0.252 0.493 0.145 0.232 0.267 0.453 0.267
|
||||
5 21 177 59 57 38 77 36 12 18 100 23 45 20 0.333 0.322 0.215 0.468 0.156 0.234 0.23 0.45 0.2
|
||||
5 22 146 52 44 41 58 26 7 16 88 26 37 25 0.356 0.301 0.281 0.448 0.121 0.276 0.295 0.42 0.284
|
||||
5 23 111 53 22 28 55 31 5 17 56 22 17 11 0.477 0.198 0.252 0.564 0.091 0.309 0.393 0.304 0.196
|
||||
6 0 119 65 29 35 62 39 6 22 57 26 23 13 0.546 0.244 0.294 0.629 0.097 0.355 0.456 0.404 0.228
|
||||
6 1 104 60 21 29 41 24 5 12 63 36 16 17 0.577 0.202 0.279 0.585 0.122 0.293 0.571 0.254 0.27
|
||||
6 2 107 65 24 33 45 26 7 12 62 39 17 21 0.607 0.224 0.308 0.578 0.156 0.267 0.629 0.274 0.339
|
||||
6 3 71 32 23 24 29 16 7 11 42 16 16 13 0.451 0.324 0.338 0.552 0.241 0.379 0.381 0.381 0.31
|
||||
6 4 69 29 14 20 26 12 4 10 43 17 10 10 0.42 0.203 0.29 0.462 0.154 0.385 0.395 0.233 0.233
|
||||
6 5 74 13 11 20 50 9 3 16 24 4 8 4 0.176 0.149 0.27 0.18 0.06 0.32 0.167 0.333 0.167
|
||||
6 6 92 20 10 20 49 15 2 11 43 5 8 9 0.217 0.109 0.217 0.306 0.041 0.224 0.116 0.186 0.209
|
||||
6 7 75 14 10 28 42 9 1 20 33 5 9 8 0.187 0.133 0.373 0.214 0.024 0.476 0.152 0.273 0.242
|
||||
6 8 70 4 12 15 42 3 3 9 28 1 9 6 0.057 0.171 0.214 0.071 0.071 0.214 0.036 0.321 0.214
|
||||
6 9 89 8 9 15 50 5 2 6 39 3 7 9 0.09 0.101 0.169 0.1 0.04 0.12 0.077 0.179 0.231
|
||||
6 10 89 5 10 18 57 4 2 12 32 1 8 6 0.056 0.112 0.202 0.07 0.035 0.211 0.031 0.25 0.188
|
||||
6 11 99 9 14 20 50 8 3 11 49 1 11 9 0.091 0.141 0.202 0.16 0.06 0.22 0.02 0.224 0.184
|
||||
6 12 130 17 16 37 84 14 3 25 46 3 13 12 0.131 0.123 0.285 0.167 0.036 0.298 0.065 0.283 0.261
|
||||
6 13 108 9 12 19 64 5 4 11 44 4 8 8 0.083 0.111 0.176 0.078 0.062 0.172 0.091 0.182 0.182
|
||||
6 14 150 16 17 44 89 10 3 31 61 6 14 13 0.107 0.113 0.293 0.112 0.034 0.348 0.098 0.23 0.213
|
||||
6 15 162 23 20 42 85 14 5 24 77 9 15 18 0.142 0.123 0.259 0.165 0.059 0.282 0.117 0.195 0.234
|
||||
6 16 135 25 16 31 81 18 5 19 54 7 11 12 0.185 0.119 0.23 0.222 0.062 0.235 0.13 0.204 0.222
|
||||
6 17 123 26 17 31 73 15 7 19 50 11 10 12 0.211 0.138 0.252 0.205 0.096 0.26 0.22 0.2 0.24
|
||||
6 18 152 51 18 30 84 28 6 16 68 23 12 14 0.336 0.118 0.197 0.333 0.071 0.19 0.338 0.176 0.206
|
||||
6 19 109 42 11 23 61 24 1 12 48 18 10 11 0.385 0.101 0.211 0.393 0.016 0.197 0.375 0.208 0.229
|
||||
6 20 139 55 32 37 72 38 8 17 67 17 24 20 0.396 0.23 0.266 0.528 0.111 0.236 0.254 0.358 0.299
|
||||
6 21 175 67 60 38 72 36 8 17 103 31 52 21 0.383 0.343 0.217 0.5 0.111 0.236 0.301 0.505 0.204
|
||||
6 22 151 59 47 35 61 27 12 11 90 32 35 24 0.391 0.311 0.232 0.443 0.197 0.18 0.356 0.389 0.267
|
||||
6 23 147 66 44 39 62 36 8 19 85 30 36 20 0.449 0.299 0.265 0.581 0.129 0.306 0.353 0.424 0.235
|
||||
7 0 113 53 26 20 52 24 9 11 61 29 17 9 0.469 0.23 0.177 0.462 0.173 0.212 0.475 0.279 0.148
|
||||
7 1 118 64 24 20 55 29 9 12 63 35 15 8 0.542 0.203 0.169 0.527 0.164 0.218 0.556 0.238 0.127
|
||||
7 2 113 57 21 25 50 24 7 16 63 33 14 9 0.504 0.186 0.221 0.48 0.14 0.32 0.524 0.222 0.143
|
||||
7 3 71 44 14 17 27 20 2 7 44 24 12 10 0.62 0.197 0.239 0.741 0.074 0.259 0.545 0.273 0.227
|
||||
7 4 62 16 21 15 25 8 7 5 37 8 14 10 0.258 0.339 0.242 0.32 0.28 0.2 0.216 0.378 0.27
|
||||
7 5 89 21 16 25 49 10 3 14 40 11 13 11 0.236 0.18 0.281 0.204 0.061 0.286 0.275 0.325 0.275
|
||||
7 6 90 22 7 20 58 15 2 16 32 7 5 4 0.244 0.078 0.222 0.259 0.034 0.276 0.219 0.156 0.125
|
||||
7 7 104 16 18 20 53 8 6 6 51 8 12 14 0.154 0.173 0.192 0.151 0.113 0.113 0.157 0.235 0.275
|
||||
7 8 68 4 11 12 39 3 2 6 29 1 9 6 0.059 0.162 0.176 0.077 0.051 0.154 0.034 0.31 0.207
|
||||
7 9 83 5 11 16 44 3 2 10 39 2 9 6 0.06 0.133 0.193 0.068 0.045 0.227 0.051 0.231 0.154
|
||||
7 11 135 14 7 30 85 10 1 19 50 4 6 11 0.104 0.052 0.222 0.118 0.012 0.224 0.08 0.12 0.22
|
||||
7 12 108 10 10 17 69 7 2 6 39 3 8 11 0.093 0.093 0.157 0.101 0.029 0.087 0.077 0.205 0.282
|
||||
7 13 141 18 17 35 80 14 5 23 61 4 12 12 0.128 0.121 0.248 0.175 0.062 0.288 0.066 0.197 0.197
|
||||
7 14 151 18 15 35 105 16 6 26 46 2 9 9 0.119 0.099 0.232 0.152 0.057 0.248 0.043 0.196 0.196
|
||||
7 15 172 24 11 45 108 16 4 31 64 8 7 14 0.14 0.064 0.262 0.148 0.037 0.287 0.125 0.109 0.219
|
||||
7 16 144 27 12 21 83 19 3 11 61 8 9 10 0.188 0.083 0.146 0.229 0.036 0.133 0.131 0.148 0.164
|
||||
7 17 155 39 16 35 105 29 6 21 50 10 10 14 0.252 0.103 0.226 0.276 0.057 0.2 0.2 0.2 0.28
|
||||
7 18 162 55 18 29 97 36 5 17 65 19 13 12 0.34 0.111 0.179 0.371 0.052 0.175 0.292 0.2 0.185
|
||||
7 19 134 50 21 25 87 34 7 13 47 16 14 12 0.373 0.157 0.187 0.391 0.08 0.149 0.34 0.298 0.255
|
||||
7 20 156 71 27 29 75 39 5 15 81 32 22 14 0.455 0.173 0.186 0.52 0.067 0.2 0.395 0.272 0.173
|
||||
7 21 196 74 62 31 95 49 13 19 101 25 49 12 0.378 0.316 0.158 0.516 0.137 0.2 0.248 0.485 0.119
|
||||
7 22 180 74 46 37 84 44 10 18 96 30 36 19 0.411 0.256 0.206 0.524 0.119 0.214 0.312 0.375 0.198
|
||||
7 23 125 40 32 20 58 24 9 9 67 16 23 11 0.32 0.256 0.16 0.414 0.155 0.155 0.239 0.343 0.164
|
||||
8 0 139 68 35 22 71 46 8 9 68 22 27 13 0.489 0.252 0.158 0.648 0.113 0.127 0.324 0.397 0.191
|
||||
8 1 125 80 24 22 50 37 7 13 75 43 17 9 0.64 0.192 0.176 0.74 0.14 0.26 0.573 0.227 0.12
|
||||
8 2 120 82 23 22 55 35 6 10 65 47 17 12 0.683 0.192 0.183 0.636 0.109 0.182 0.723 0.262 0.185
|
||||
8 3 100 63 20 18 49 30 8 11 51 33 12 7 0.63 0.2 0.18 0.612 0.163 0.224 0.647 0.235 0.137
|
||||
8 4 80 34 16 17 39 17 6 11 41 17 10 6 0.425 0.2 0.212 0.436 0.154 0.282 0.415 0.244 0.146
|
||||
8 5 105 30 28 20 56 23 2 12 49 7 26 8 0.286 0.267 0.19 0.411 0.036 0.214 0.143 0.531 0.163
|
||||
8 6 96 19 18 27 49 10 6 14 47 9 12 13 0.198 0.188 0.281 0.204 0.122 0.286 0.191 0.255 0.277
|
||||
8 7 96 14 15 19 51 7 2 13 45 7 13 6 0.146 0.156 0.198 0.137 0.039 0.255 0.156 0.289 0.133
|
||||
8 8 77 5 7 18 48 4 2 12 29 1 5 6 0.065 0.091 0.234 0.083 0.042 0.25 0.034 0.172 0.207
|
||||
8 9 87 8 9 9 47 6 2 7 40 2 7 2 0.092 0.103 0.103 0.128 0.043 0.149 0.05 0.175 0.05
|
||||
8 10 95 8 10 19 63 6 3 14 32 2 7 5 0.084 0.105 0.2 0.095 0.048 0.222 0.062 0.219 0.156
|
||||
8 11 103 13 9 18 66 6 2 13 37 7 7 5 0.126 0.087 0.175 0.091 0.03 0.197 0.189 0.189 0.135
|
||||
8 12 118 8 5 19 64 3 2 12 54 5 3 7 0.068 0.042 0.161 0.047 0.031 0.188 0.093 0.056 0.13
|
||||
8 13 140 20 11 22 80 10 3 12 60 10 8 10 0.143 0.079 0.157 0.125 0.038 0.15 0.167 0.133 0.167
|
||||
8 14 134 18 13 24 93 10 7 16 41 8 6 8 0.134 0.097 0.179 0.108 0.075 0.172 0.195 0.146 0.195
|
||||
8 15 168 33 24 36 98 26 5 25 70 7 19 11 0.196 0.143 0.214 0.265 0.051 0.255 0.1 0.271 0.157
|
||||
8 16 177 36 10 41 114 25 3 32 63 11 7 9 0.203 0.056 0.232 0.219 0.026 0.281 0.175 0.111 0.143
|
||||
8 17 151 40 7 29 83 24 2 16 68 16 5 13 0.265 0.046 0.192 0.289 0.024 0.193 0.235 0.074 0.191
|
||||
8 18 126 47 12 20 73 30 5 10 53 17 7 10 0.373 0.095 0.159 0.411 0.068 0.137 0.321 0.132 0.189
|
||||
8 19 136 55 14 18 83 36 1 13 53 19 13 5 0.404 0.103 0.132 0.434 0.012 0.157 0.358 0.245 0.094
|
||||
8 20 180 66 59 28 84 36 13 11 96 30 46 17 0.367 0.328 0.156 0.429 0.155 0.131 0.312 0.479 0.177
|
||||
8 21 184 70 49 36 81 43 7 20 103 27 42 16 0.38 0.266 0.196 0.531 0.086 0.247 0.262 0.408 0.155
|
||||
8 22 136 56 43 34 66 32 12 20 70 24 31 14 0.412 0.316 0.25 0.485 0.182 0.303 0.343 0.443 0.2
|
||||
8 23 127 69 28 22 64 40 7 11 63 29 21 11 0.543 0.22 0.173 0.625 0.109 0.172 0.46 0.333 0.175
|
||||
9 0 92 52 19 19 48 31 3 15 44 21 16 4 0.565 0.207 0.207 0.646 0.062 0.312 0.477 0.364 0.091
|
||||
9 1 98 53 18 21 55 33 6 12 43 20 12 9 0.541 0.184 0.214 0.6 0.109 0.218 0.465 0.279 0.209
|
||||
9 2 97 64 13 11 36 27 3 6 61 37 10 5 0.66 0.134 0.113 0.75 0.083 0.167 0.607 0.164 0.082
|
||||
9 3 81 46 15 20 35 20 6 11 46 26 9 9 0.568 0.185 0.247 0.571 0.171 0.314 0.565 0.196 0.196
|
||||
9 4 58 18 14 17 29 8 4 6 29 10 10 11 0.31 0.241 0.293 0.276 0.138 0.207 0.345 0.345 0.379
|
||||
9 5 100 14 30 21 45 5 8 10 55 9 22 11 0.14 0.3 0.21 0.111 0.178 0.222 0.164 0.4 0.2
|
||||
9 6 110 12 27 36 56 6 5 21 54 6 22 15 0.109 0.245 0.327 0.107 0.089 0.375 0.111 0.407 0.278
|
||||
9 7 114 11 19 29 63 5 2 24 51 6 17 5 0.096 0.167 0.254 0.079 0.032 0.381 0.118 0.333 0.098
|
||||
9 8 80 10 16 19 48 8 1 12 32 2 15 7 0.125 0.2 0.238 0.167 0.021 0.25 0.062 0.469 0.219
|
||||
9 9 79 5 15 18 47 4 3 10 32 1 12 8 0.063 0.19 0.228 0.085 0.064 0.213 0.031 0.375 0.25
|
||||
9 10 78 6 13 17 48 5 1 10 30 1 12 7 0.077 0.167 0.218 0.104 0.021 0.208 0.033 0.4 0.233
|
||||
9 11 108 12 16 30 63 11 1 20 45 1 15 10 0.111 0.148 0.278 0.175 0.016 0.317 0.022 0.333 0.222
|
||||
9 12 90 9 4 19 57 4 1 11 33 5 3 8 0.1 0.044 0.211 0.07 0.018 0.193 0.152 0.091 0.242
|
||||
9 13 113 19 11 23 67 11 1 13 46 8 10 10 0.168 0.097 0.204 0.164 0.015 0.194 0.174 0.217 0.217
|
||||
9 14 149 14 20 27 95 11 5 19 54 3 15 8 0.094 0.134 0.181 0.116 0.053 0.2 0.056 0.278 0.148
|
||||
9 15 170 25 20 37 106 17 8 25 64 8 12 12 0.147 0.118 0.218 0.16 0.075 0.236 0.125 0.188 0.188
|
||||
9 16 147 27 17 30 92 18 2 18 55 9 15 12 0.184 0.116 0.204 0.196 0.022 0.196 0.164 0.273 0.218
|
||||
9 17 174 45 22 38 112 32 6 27 62 13 16 11 0.259 0.126 0.218 0.286 0.054 0.241 0.21 0.258 0.177
|
||||
9 18 136 39 19 27 81 24 6 18 55 15 13 9 0.287 0.14 0.199 0.296 0.074 0.222 0.273 0.236 0.164
|
||||
9 19 156 42 44 26 79 30 9 16 77 12 35 10 0.269 0.282 0.167 0.38 0.114 0.203 0.156 0.455 0.13
|
||||
9 20 207 60 78 44 100 35 22 24 107 25 56 20 0.29 0.377 0.213 0.35 0.22 0.24 0.234 0.523 0.187
|
||||
9 21 171 47 61 32 66 25 10 16 105 22 51 16 0.275 0.357 0.187 0.379 0.152 0.242 0.21 0.486 0.152
|
||||
9 22 120 46 41 27 52 23 7 16 68 23 34 11 0.383 0.342 0.225 0.442 0.135 0.308 0.338 0.5 0.162
|
||||
9 23 117 50 38 21 50 24 10 7 67 26 28 14 0.427 0.325 0.179 0.48 0.2 0.14 0.388 0.418 0.209
|
||||
10 0 126 68 29 27 52 32 5 8 74 36 24 19 0.54 0.23 0.214 0.615 0.096 0.154 0.486 0.324 0.257
|
||||
10 1 113 52 27 31 51 29 4 18 62 23 23 13 0.46 0.239 0.274 0.569 0.078 0.353 0.371 0.371 0.21
|
||||
10 2 114 67 25 27 45 28 6 10 69 39 19 17 0.588 0.219 0.237 0.622 0.133 0.222 0.565 0.275 0.246
|
||||
10 3 85 43 16 25 42 19 2 17 43 24 14 8 0.506 0.188 0.294 0.452 0.048 0.405 0.558 0.326 0.186
|
||||
10 4 61 30 10 19 35 18 5 13 26 12 5 6 0.492 0.164 0.311 0.514 0.143 0.371 0.462 0.192 0.231
|
||||
10 5 79 19 26 30 40 11 6 15 39 8 20 15 0.241 0.329 0.38 0.275 0.15 0.375 0.205 0.513 0.385
|
||||
10 6 139 15 45 46 80 9 13 32 59 6 32 14 0.108 0.324 0.331 0.112 0.162 0.4 0.102 0.542 0.237
|
||||
10 7 106 11 23 34 57 6 6 20 49 5 17 14 0.104 0.217 0.321 0.105 0.105 0.351 0.102 0.347 0.286
|
||||
10 8 94 5 10 28 55 3 1 23 39 2 9 5 0.053 0.106 0.298 0.055 0.018 0.418 0.051 0.231 0.128
|
||||
10 9 97 8 16 32 58 4 4 24 39 4 12 8 0.082 0.165 0.33 0.069 0.069 0.414 0.103 0.308 0.205
|
||||
10 11 100 10 13 26 66 9 4 15 34 1 9 11 0.1 0.13 0.26 0.136 0.061 0.227 0.029 0.265 0.324
|
||||
10 13 122 20 11 30 71 15 1 20 51 5 10 10 0.164 0.09 0.246 0.211 0.014 0.282 0.098 0.196 0.196
|
||||
10 14 129 19 20 37 74 11 2 22 55 8 18 15 0.147 0.155 0.287 0.149 0.027 0.297 0.145 0.327 0.273
|
||||
10 15 153 29 15 34 81 19 4 23 72 10 11 11 0.19 0.098 0.222 0.235 0.049 0.284 0.139 0.153 0.153
|
||||
10 16 143 23 18 39 94 18 5 27 49 5 13 12 0.161 0.126 0.273 0.191 0.053 0.287 0.102 0.265 0.245
|
||||
10 17 145 33 14 39 85 20 1 28 60 13 13 11 0.228 0.097 0.269 0.235 0.012 0.329 0.217 0.217 0.183
|
||||
10 18 165 37 33 36 74 15 5 17 91 22 28 19 0.224 0.2 0.218 0.203 0.068 0.23 0.242 0.308 0.209
|
||||
10 19 245 52 91 57 104 25 22 21 141 27 69 36 0.212 0.371 0.233 0.24 0.212 0.202 0.191 0.489 0.255
|
||||
10 20 145 33 64 32 55 18 10 11 90 15 54 21 0.228 0.441 0.221 0.327 0.182 0.2 0.167 0.6 0.233
|
||||
10 21 149 52 58 48 56 24 7 19 93 28 51 29 0.349 0.389 0.322 0.429 0.125 0.339 0.301 0.548 0.312
|
||||
10 22 151 49 53 28 62 24 8 12 89 25 45 16 0.325 0.351 0.185 0.387 0.129 0.194 0.281 0.506 0.18
|
||||
10 23 130 58 32 32 66 34 9 19 64 24 23 13 0.446 0.246 0.246 0.515 0.136 0.288 0.375 0.359 0.203
|
||||
11 0 116 57 26 35 47 26 5 20 69 31 21 15 0.491 0.224 0.302 0.553 0.106 0.426 0.449 0.304 0.217
|
||||
11 1 88 53 14 32 32 24 2 14 56 29 12 18 0.602 0.159 0.364 0.75 0.062 0.438 0.518 0.214 0.321
|
||||
11 2 86 51 10 25 33 21 1 16 53 30 9 9 0.593 0.116 0.291 0.636 0.03 0.485 0.566 0.17 0.17
|
||||
11 3 84 41 13 26 36 20 4 10 48 21 9 16 0.488 0.155 0.31 0.556 0.111 0.278 0.438 0.188 0.333
|
||||
11 4 58 27 9 18 27 13 2 12 31 14 7 6 0.466 0.155 0.31 0.481 0.074 0.444 0.452 0.226 0.194
|
||||
11 5 82 22 25 38 37 7 7 20 45 15 18 18 0.268 0.305 0.463 0.189 0.189 0.541 0.333 0.4 0.4
|
||||
11 6 106 15 23 37 53 7 1 18 53 8 22 19 0.142 0.217 0.349 0.132 0.019 0.34 0.151 0.415 0.358
|
||||
11 7 92 14 8 44 58 8 1 27 34 6 7 17 0.152 0.087 0.478 0.138 0.017 0.466 0.176 0.206 0.5
|
||||
11 9 85 9 7 36 51 6 3 24 34 3 4 12 0.106 0.082 0.424 0.118 0.059 0.471 0.088 0.118 0.353
|
||||
11 10 91 13 14 31 45 7 1 16 46 6 13 15 0.143 0.154 0.341 0.156 0.022 0.356 0.13 0.283 0.326
|
||||
11 11 84 12 9 34 48 8 3 21 36 4 6 13 0.143 0.107 0.405 0.167 0.062 0.438 0.111 0.167 0.361
|
||||
11 12 101 12 8 32 59 10 2 20 42 2 6 12 0.119 0.079 0.317 0.169 0.034 0.339 0.048 0.143 0.286
|
||||
11 15 134 20 15 39 76 15 3 23 58 5 12 16 0.149 0.112 0.291 0.197 0.039 0.303 0.086 0.207 0.276
|
||||
11 16 112 23 18 42 63 14 1 26 49 9 17 16 0.205 0.161 0.375 0.222 0.016 0.413 0.184 0.347 0.327
|
||||
11 17 231 39 93 70 100 25 19 39 131 14 74 31 0.169 0.403 0.303 0.25 0.19 0.39 0.107 0.565 0.237
|
||||
11 18 224 42 105 68 100 24 19 35 124 18 86 33 0.188 0.469 0.304 0.24 0.19 0.35 0.145 0.694 0.266
|
||||
11 19 183 49 77 57 79 27 18 24 104 22 59 33 0.268 0.421 0.311 0.342 0.228 0.304 0.212 0.567 0.317
|
||||
11 20 124 27 56 47 55 18 15 23 69 9 41 24 0.218 0.452 0.379 0.327 0.273 0.418 0.13 0.594 0.348
|
||||
11 21 132 42 50 41 64 28 13 21 68 14 37 20 0.318 0.379 0.311 0.438 0.203 0.328 0.206 0.544 0.294
|
||||
11 22 104 32 24 27 47 17 6 11 57 15 18 16 0.308 0.231 0.26 0.362 0.128 0.234 0.263 0.316 0.281
|
||||
11 23 75 33 17 23 39 19 3 10 36 14 14 13 0.44 0.227 0.307 0.487 0.077 0.256 0.389 0.389 0.361
|
||||
12 0 95 45 17 34 45 25 4 18 50 20 13 16 0.474 0.179 0.358 0.556 0.089 0.4 0.4 0.26 0.32
|
||||
12 1 90 50 17 32 33 20 3 15 57 30 14 17 0.556 0.189 0.356 0.606 0.091 0.455 0.526 0.246 0.298
|
||||
12 2 97 63 15 36 27 20 3 10 70 43 12 26 0.649 0.155 0.371 0.741 0.111 0.37 0.614 0.171 0.371
|
||||
12 3 79 43 13 29 35 16 6 14 44 27 7 15 0.544 0.165 0.367 0.457 0.171 0.4 0.614 0.159 0.341
|
||||
12 4 68 24 7 22 34 13 3 11 34 11 4 11 0.353 0.103 0.324 0.382 0.088 0.324 0.324 0.118 0.324
|
||||
12 5 89 26 23 45 44 12 5 25 45 14 18 20 0.292 0.258 0.506 0.273 0.114 0.568 0.311 0.4 0.444
|
||||
12 6 109 10 39 56 52 6 5 27 57 4 34 29 0.092 0.358 0.514 0.115 0.096 0.519 0.07 0.596 0.509
|
||||
12 7 90 15 10 44 62 10 1 32 28 5 9 12 0.167 0.111 0.489 0.161 0.016 0.516 0.179 0.321 0.429
|
||||
12 8 79 10 8 40 44 7 2 19 35 3 6 21 0.127 0.101 0.506 0.159 0.045 0.432 0.086 0.171 0.6
|
||||
12 9 87 5 8 38 49 3 1 24 38 2 7 14 0.057 0.092 0.437 0.061 0.02 0.49 0.053 0.184 0.368
|
||||
12 10 74 6 9 31 44 3 1 22 30 3 8 9 0.081 0.122 0.419 0.068 0.023 0.5 0.1 0.267 0.3
|
||||
12 11 85 6 7 31 49 2 1 22 36 4 6 9 0.071 0.082 0.365 0.041 0.02 0.449 0.111 0.167 0.25
|
||||
12 12 101 6 5 51 64 4 2 34 37 2 3 17 0.059 0.05 0.505 0.062 0.031 0.531 0.054 0.081 0.459
|
||||
12 14 108 13 13 35 55 4 3 22 53 9 10 13 0.12 0.12 0.324 0.073 0.055 0.4 0.17 0.189 0.245
|
||||
12 15 137 17 19 44 77 11 6 29 60 6 13 15 0.124 0.139 0.321 0.143 0.078 0.377 0.1 0.217 0.25
|
||||
12 16 148 27 19 58 77 16 4 37 71 11 15 21 0.182 0.128 0.392 0.208 0.052 0.481 0.155 0.211 0.296
|
||||
12 17 210 30 89 82 101 20 21 44 109 10 68 38 0.143 0.424 0.39 0.198 0.208 0.436 0.092 0.624 0.349
|
||||
12 18 222 39 102 89 89 20 20 36 133 19 82 53 0.176 0.459 0.401 0.225 0.225 0.404 0.143 0.617 0.398
|
||||
12 19 175 43 70 68 66 18 10 29 109 25 60 39 0.246 0.4 0.389 0.273 0.152 0.439 0.229 0.55 0.358
|
||||
12 20 135 29 51 49 63 13 9 22 72 16 42 27 0.215 0.378 0.363 0.206 0.143 0.349 0.222 0.583 0.375
|
||||
12 21 132 46 45 44 55 23 6 27 77 23 39 17 0.348 0.341 0.333 0.418 0.109 0.491 0.299 0.506 0.221
|
||||
12 22 119 46 32 41 51 24 6 23 68 22 26 18 0.387 0.269 0.345 0.471 0.118 0.451 0.324 0.382 0.265
|
||||
12 23 116 50 28 46 50 25 6 20 66 25 22 26 0.431 0.241 0.397 0.5 0.12 0.4 0.379 0.333 0.394
|
||||
2 10 63 3 7 26 41 0 1 20 22 3 6 6 0.048 0.111 0.413 0 0.024 0.488 0.136 0.273 0.273
|
||||
11 14 115 13 5 42 68 8 0 29 47 5 5 13 0.113 0.043 0.365 0.118 0 0.426 0.106 0.106 0.277
|
||||
1 1 92 58 9 26 42 26 0 16 50 32 9 10 0.63 0.098 0.283 0.619 0 0.381 0.64 0.18 0.2
|
||||
10 12 97 8 10 28 55 5 0 20 42 3 10 8 0.082 0.103 0.289 0.091 0 0.364 0.071 0.238 0.19
|
||||
5 14 137 21 8 34 74 16 0 20 63 5 8 14 0.153 0.058 0.248 0.216 0 0.27 0.079 0.127 0.222
|
||||
3 1 94 58 23 25 30 22 0 9 64 36 23 16 0.617 0.245 0.266 0.733 0 0.3 0.562 0.359 0.25
|
||||
4 14 122 16 14 36 60 6 0 18 62 10 14 18 0.131 0.115 0.295 0.1 0 0.3 0.161 0.226 0.29
|
||||
11 8 82 12 8 27 45 6 0 14 37 6 8 13 0.146 0.098 0.329 0.133 0 0.311 0.162 0.216 0.351
|
||||
11 13 114 15 9 43 51 6 0 25 63 9 9 18 0.132 0.079 0.377 0.118 0 0.49 0.143 0.143 0.286
|
||||
3 2 81 54 10 21 32 23 0 8 49 31 10 13 0.667 0.123 0.259 0.719 0 0.25 0.633 0.204 0.265
|
||||
5 12 99 10 9 25 51 7 0 19 48 3 9 6 0.101 0.091 0.253 0.137 0 0.373 0.062 0.188 0.125
|
||||
12 13 103 7 9 34 55 5 0 20 48 2 9 14 0.068 0.087 0.33 0.091 0 0.364 0.042 0.188 0.292
|
||||
7 10 102 9 6 21 62 8 0 15 40 1 6 6 0.088 0.059 0.206 0.129 0 0.242 0.025 0.15 0.15
|
||||
3 14 93 19 5 25 53 11 0 17 40 8 5 8 0.204 0.054 0.269 0.208 0 0.321 0.2 0.125 0.2
|
||||
5 6 84 20 2 26 58 12 0 17 26 8 2 9 0.238 0.024 0.31 0.207 0 0.293 0.308 0.077 0.346
|
||||
4 18 113 40 12 26 59 22 0 15 54 18 12 11 0.354 0.106 0.23 0.373 0 0.254 0.333 0.222 0.204
|
||||
10 10 108 9 10 28 61 6 0 17 47 3 10 11 0.083 0.093 0.259 0.098 0 0.279 0.064 0.213 0.234
|
||||
2 11 67 8 5 25 40 3 0 18 27 5 5 7 0.119 0.075 0.373 0.075 0 0.45 0.185 0.185 0.259
|
||||
1 10 71 5 5 28 37 5 0 14 34 0 5 14 0.07 0.07 0.394 0.135 0 0.378 0 0.147 0.412
|
||||
|
@@ -0,0 +1,13 @@
|
||||
month,"V1","V2","V3","V4","V5","V6","V7","V8","V9","V10","V11","V12","V13","V14","V15","V16","V17","V18","V19","V20","V21","V22","V23","V24"
|
||||
"Jan.",0.57,0.63,0.563,0.514,0.474,0.145,0.118,0.103,0.1,0.045,0.07,0.087,0.104,0.098,0.111,0.203,0.194,0.205,0.182,0.288,0.301,0.333,0.395,0.443
|
||||
"Feb.",0.576,0.671,0.598,0.627,0.368,0.306,0.25,0.145,0.1,0.129,0.048,0.119,0.14,0.062,0.129,0.168,0.188,0.253,0.2,0.223,0.27,0.404,0.308,0.479
|
||||
"March",0.48,0.617,0.667,0.625,0.456,0.221,0.186,0.154,0.036,0.127,0.082,0.081,0.111,0.129,0.204,0.136,0.241,0.333,0.296,0.268,0.303,0.328,0.443,0.467
|
||||
"April",0.494,0.522,0.651,0.521,0.397,0.238,0.134,0.169,0.12,0.054,0.097,0.108,0.122,0.151,0.131,0.135,0.136,0.296,0.354,0.36,0.335,0.347,0.466,0.508
|
||||
"May",0.488,0.627,0.619,0.626,0.457,0.297,0.238,0.155,0.072,0.129,0.099,0.163,0.101,0.136,0.153,0.14,0.229,0.297,0.37,0.437,0.368,0.333,0.356,0.477
|
||||
"June",0.546,0.577,0.607,0.451,0.42,0.176,0.217,0.187,0.057,0.09,0.056,0.091,0.131,0.083,0.107,0.142,0.185,0.211,0.336,0.385,0.396,0.383,0.391,0.449
|
||||
"July",0.469,0.542,0.504,0.62,0.258,0.236,0.244,0.154,0.059,0.06,0.088,0.104,0.093,0.128,0.119,0.14,0.188,0.252,0.34,0.373,0.455,0.378,0.411,0.32
|
||||
"Aug.",0.489,0.64,0.683,0.63,0.425,0.286,0.198,0.146,0.065,0.092,0.084,0.126,0.068,0.143,0.134,0.196,0.203,0.265,0.373,0.404,0.367,0.38,0.412,0.543
|
||||
"Sept.",0.565,0.541,0.66,0.568,0.31,0.14,0.109,0.096,0.125,0.063,0.077,0.111,0.1,0.168,0.094,0.147,0.184,0.259,0.287,0.269,0.29,0.275,0.383,0.427
|
||||
"Oct.",0.54,0.46,0.588,0.506,0.492,0.241,0.108,0.104,0.053,0.082,0.083,0.1,0.082,0.164,0.147,0.19,0.161,0.228,0.224,0.212,0.228,0.349,0.325,0.446
|
||||
"Nov.",0.491,0.602,0.593,0.488,0.466,0.268,0.142,0.152,0.146,0.106,0.143,0.143,0.119,0.132,0.113,0.149,0.205,0.169,0.188,0.268,0.218,0.318,0.308,0.44
|
||||
"Dec.",0.474,0.556,0.649,0.544,0.353,0.292,0.092,0.167,0.127,0.057,0.081,0.071,0.059,0.068,0.12,0.124,0.182,0.143,0.176,0.246,0.215,0.348,0.387,0.431
|
||||
|
@@ -0,0 +1,277 @@
|
||||
"year" "sex" "name" "n" "prop"
|
||||
1880 "M" "Nathan" 114 0.00096284
|
||||
1881 "M" "Nathan" 91 0.0008404
|
||||
1882 "M" "Nathan" 113 0.00092599
|
||||
1883 "M" "Nathan" 93 0.00082684
|
||||
1884 "M" "Nathan" 100 0.00081474
|
||||
1885 "M" "Nathan" 103 0.00088835
|
||||
1886 "M" "Nathan" 136 0.00114246
|
||||
1887 "M" "Nathan" 106 0.00096969
|
||||
1888 "M" "Nathan" 129 0.00099303
|
||||
1889 "M" "Nathan" 121 0.00101653
|
||||
1890 "M" "Nathan" 110 0.00091896
|
||||
1891 "M" "Nathan" 106 0.00097012
|
||||
1892 "M" "Nathan" 144 0.00109545
|
||||
1893 "M" "Nathan" 114 0.00094183
|
||||
1894 "M" "Nathan" 127 0.00101687
|
||||
1895 "M" "Nathan" 119 0.00093965
|
||||
1896 "M" "Nathan" 110 0.00085224
|
||||
1897 "M" "Nathan" 139 0.00113989
|
||||
1898 "M" "Nathan" 99 0.00074941
|
||||
1899 "M" "Nathan" 112 0.00097228
|
||||
1900 "M" "Nathan" 186 0.00114721
|
||||
1901 "M" "Nathan" 131 0.00113327
|
||||
1902 "M" "Nathan" 143 0.00107721
|
||||
1903 "M" "Nathan" 146 0.00112893
|
||||
1904 "M" "Nathan" 131 0.00094579
|
||||
1905 "M" "Nathan" 168 0.00117287
|
||||
1906 "M" "Nathan" 148 0.00102727
|
||||
1907 "M" "Nathan" 176 0.0011098
|
||||
1908 "M" "Nathan" 178 0.00106992
|
||||
1909 "M" "Nathan" 209 0.00118168
|
||||
1910 "M" "Nathan" 245 0.00117494
|
||||
1911 "M" "Nathan" 348 0.00144162
|
||||
1912 "M" "Nathan" 581 0.00128694
|
||||
1913 "M" "Nathan" 615 0.00114686
|
||||
1914 "M" "Nathan" 848 0.00124099
|
||||
1915 "M" "Nathan" 916 0.0010398
|
||||
1916 "M" "Nathan" 904 0.00097914
|
||||
1917 "M" "Nathan" 881 0.00091835
|
||||
1918 "M" "Nathan" 945 0.00090114
|
||||
1919 "M" "Nathan" 849 0.00083618
|
||||
1920 "M" "Nathan" 815 0.00074036
|
||||
1921 "M" "Nathan" 751 0.00065996
|
||||
1922 "M" "Nathan" 749 0.00066562
|
||||
1923 "M" "Nathan" 739 0.00065264
|
||||
1924 "M" "Nathan" 680 0.00058166
|
||||
1925 "M" "Nathan" 615 0.00053411
|
||||
1926 "M" "Nathan" 669 0.00058402
|
||||
1927 "M" "Nathan" 636 0.0005474
|
||||
1928 "M" "Nathan" 548 0.00048021
|
||||
1929 "M" "Nathan" 513 0.00046319
|
||||
1930 "M" "Nathan" 540 0.00047812
|
||||
1931 "M" "Nathan" 442 0.00041325
|
||||
1932 "M" "Nathan" 486 0.00045239
|
||||
1933 "M" "Nathan" 413 0.0004049
|
||||
1934 "M" "Nathan" 469 0.00044173
|
||||
1935 "M" "Nathan" 468 0.00043763
|
||||
1936 "M" "Nathan" 464 0.00043602
|
||||
1937 "M" "Nathan" 434 0.0003969
|
||||
1938 "M" "Nathan" 516 0.0004541
|
||||
1939 "M" "Nathan" 468 0.000413
|
||||
1940 "M" "Nathan" 497 0.00041905
|
||||
1941 "M" "Nathan" 528 0.00042083
|
||||
1942 "M" "Nathan" 522 0.00037072
|
||||
1943 "M" "Nathan" 582 0.00040019
|
||||
1944 "M" "Nathan" 507 0.00036502
|
||||
1945 "M" "Nathan" 488 0.00035587
|
||||
1946 "M" "Nathan" 558 0.00033814
|
||||
1947 "M" "Nathan" 617 0.00033219
|
||||
1948 "M" "Nathan" 619 0.00034725
|
||||
1949 "M" "Nathan" 660 0.00036629
|
||||
1950 "M" "Nathan" 753 0.00041395
|
||||
1951 "M" "Nathan" 870 0.00045506
|
||||
1952 "M" "Nathan" 850 0.00043055
|
||||
1953 "M" "Nathan" 810 0.00040475
|
||||
1954 "M" "Nathan" 961 0.00046461
|
||||
1955 "M" "Nathan" 949 0.00045416
|
||||
1956 "M" "Nathan" 1095 0.00051059
|
||||
1957 "M" "Nathan" 1227 0.00056092
|
||||
1958 "M" "Nathan" 1242 0.00057686
|
||||
1959 "M" "Nathan" 1374 0.00063427
|
||||
1960 "M" "Nathan" 1627 0.00075126
|
||||
1961 "M" "Nathan" 1490 0.00069111
|
||||
1962 "M" "Nathan" 1534 0.00072976
|
||||
1963 "M" "Nathan" 1543 0.00074715
|
||||
1964 "M" "Nathan" 1500 0.00073989
|
||||
1965 "M" "Nathan" 1419 0.00074873
|
||||
1966 "M" "Nathan" 1422 0.00078222
|
||||
1967 "M" "Nathan" 1434 0.00080572
|
||||
1968 "M" "Nathan" 1656 0.0009324
|
||||
1969 "M" "Nathan" 1909 0.00104318
|
||||
1970 "M" "Nathan" 2548 0.0013371
|
||||
1971 "M" "Nathan" 3050 0.00167732
|
||||
1972 "M" "Nathan" 3522 0.00210309
|
||||
1973 "M" "Nathan" 4749 0.00294199
|
||||
1974 "M" "Nathan" 5849 0.00358672
|
||||
1975 "M" "Nathan" 7064 0.00435236
|
||||
1976 "M" "Nathan" 8616 0.00527545
|
||||
1977 "M" "Nathan" 9894 0.00578644
|
||||
1978 "M" "Nathan" 9891 0.00578726
|
||||
1979 "M" "Nathan" 10741 0.00599445
|
||||
1980 "M" "Nathan" 11144 0.00600747
|
||||
1981 "M" "Nathan" 11261 0.00604645
|
||||
1982 "M" "Nathan" 10803 0.00572458
|
||||
1983 "M" "Nathan" 10556 0.00566512
|
||||
1984 "M" "Nathan" 10612 0.00565604
|
||||
1985 "M" "Nathan" 10650 0.00553586
|
||||
1986 "M" "Nathan" 9995 0.00520313
|
||||
1987 "M" "Nathan" 9908 0.0050824
|
||||
1988 "M" "Nathan" 10148 0.00507063
|
||||
1989 "M" "Nathan" 10906 0.0052046
|
||||
1990 "M" "Nathan" 10936 0.00508377
|
||||
1991 "M" "Nathan" 10494 0.00495189
|
||||
1992 "M" "Nathan" 10146 0.00483461
|
||||
1993 "M" "Nathan" 10192 0.00493569
|
||||
1994 "M" "Nathan" 10382 0.00509434
|
||||
1995 "M" "Nathan" 10304 0.00512383
|
||||
1996 "M" "Nathan" 10283 0.00513285
|
||||
1997 "M" "Nathan" 10441 0.00522746
|
||||
1998 "M" "Nathan" 11584 0.00571447
|
||||
1999 "M" "Nathan" 12534 0.0061491
|
||||
2000 "M" "Nathan" 13036 0.00624512
|
||||
2001 "M" "Nathan" 12645 0.00611631
|
||||
2002 "M" "Nathan" 13220 0.00640029
|
||||
2003 "M" "Nathan" 13659 0.00650412
|
||||
2004 "M" "Nathan" 14627 0.00692504
|
||||
2005 "M" "Nathan" 14356 0.00675248
|
||||
2006 "M" "Nathan" 14273 0.00651486
|
||||
2007 "M" "Nathan" 13589 0.00613936
|
||||
2008 "M" "Nathan" 13253 0.00608367
|
||||
2009 "M" "Nathan" 12119 0.00571933
|
||||
2010 "M" "Nathan" 11372 0.00554158
|
||||
2011 "M" "Nathan" 10501 0.0051765
|
||||
2012 "M" "Nathan" 10417 0.00514194
|
||||
2013 "M" "Nathan" 9709 0.00481423
|
||||
2014 "M" "Nathan" 8967 0.00438618
|
||||
2015 "M" "Nathan" 8581 0.00420982
|
||||
2016 "M" "Nathan" 7970 0.00394987
|
||||
2017 "M" "Nathan" 7390 0.00376409
|
||||
1880 "F" "Beatrice" 87 0.00089135
|
||||
1881 "F" "Beatrice" 87 0.00088008
|
||||
1882 "F" "Beatrice" 123 0.00106314
|
||||
1883 "F" "Beatrice" 126 0.00104948
|
||||
1884 "F" "Beatrice" 167 0.00121379
|
||||
1885 "F" "Beatrice" 188 0.00132443
|
||||
1886 "F" "Beatrice" 192 0.0012489
|
||||
1887 "F" "Beatrice" 262 0.00168573
|
||||
1888 "F" "Beatrice" 316 0.00166803
|
||||
1889 "F" "Beatrice" 352 0.00186028
|
||||
1890 "F" "Beatrice" 417 0.00206783
|
||||
1891 "F" "Beatrice" 485 0.00246736
|
||||
1892 "F" "Beatrice" 541 0.00240537
|
||||
1893 "F" "Beatrice" 564 0.00250408
|
||||
1894 "F" "Beatrice" 684 0.00289866
|
||||
1895 "F" "Beatrice" 814 0.00329413
|
||||
1896 "F" "Beatrice" 870 0.00345248
|
||||
1897 "F" "Beatrice" 942 0.00379418
|
||||
1898 "F" "Beatrice" 1122 0.00409274
|
||||
1899 "F" "Beatrice" 1061 0.00428704
|
||||
1900 "F" "Beatrice" 1382 0.0043493
|
||||
1901 "F" "Beatrice" 1183 0.00465329
|
||||
1902 "F" "Beatrice" 1429 0.00509749
|
||||
1903 "F" "Beatrice" 1439 0.00517261
|
||||
1904 "F" "Beatrice" 1549 0.00529689
|
||||
1905 "F" "Beatrice" 1661 0.0053604
|
||||
1906 "F" "Beatrice" 1679 0.00535669
|
||||
1907 "F" "Beatrice" 1858 0.00550626
|
||||
1908 "F" "Beatrice" 1997 0.00563279
|
||||
1909 "F" "Beatrice" 2105 0.00571862
|
||||
1910 "F" "Beatrice" 2459 0.00586138
|
||||
1911 "F" "Beatrice" 2522 0.00570823
|
||||
1912 "F" "Beatrice" 3205 0.00546265
|
||||
1913 "F" "Beatrice" 3567 0.00544652
|
||||
1914 "F" "Beatrice" 4232 0.00531245
|
||||
1915 "F" "Beatrice" 5342 0.00521743
|
||||
1916 "F" "Beatrice" 5586 0.00514497
|
||||
1917 "F" "Beatrice" 5839 0.00519624
|
||||
1918 "F" "Beatrice" 5907 0.00491282
|
||||
1919 "F" "Beatrice" 5856 0.00498532
|
||||
1920 "F" "Beatrice" 5804 0.00466545
|
||||
1921 "F" "Beatrice" 5968 0.00466355
|
||||
1922 "F" "Beatrice" 5476 0.00438938
|
||||
1923 "F" "Beatrice" 5464 0.00436261
|
||||
1924 "F" "Beatrice" 5269 0.00406651
|
||||
1925 "F" "Beatrice" 4991 0.00395147
|
||||
1926 "F" "Beatrice" 4519 0.00367353
|
||||
1927 "F" "Beatrice" 4240 0.00342932
|
||||
1928 "F" "Beatrice" 3921 0.0032799
|
||||
1929 "F" "Beatrice" 3572 0.00308591
|
||||
1930 "F" "Beatrice" 3392 0.00290804
|
||||
1931 "F" "Beatrice" 2842 0.00257515
|
||||
1932 "F" "Beatrice" 2787 0.00251939
|
||||
1933 "F" "Beatrice" 2410 0.00230416
|
||||
1934 "F" "Beatrice" 2408 0.00222505
|
||||
1935 "F" "Beatrice" 2241 0.0020622
|
||||
1936 "F" "Beatrice" 1956 0.00181533
|
||||
1937 "F" "Beatrice" 1986 0.00180257
|
||||
1938 "F" "Beatrice" 1911 0.00167432
|
||||
1939 "F" "Beatrice" 1780 0.00156961
|
||||
1940 "F" "Beatrice" 1729 0.0014637
|
||||
1941 "F" "Beatrice" 1665 0.00133643
|
||||
1942 "F" "Beatrice" 1771 0.00127374
|
||||
1943 "F" "Beatrice" 1757 0.00122416
|
||||
1944 "F" "Beatrice" 1579 0.00115554
|
||||
1945 "F" "Beatrice" 1359 0.00100961
|
||||
1946 "F" "Beatrice" 1463 0.00090709
|
||||
1947 "F" "Beatrice" 1466 0.00080646
|
||||
1948 "F" "Beatrice" 1432 0.00082177
|
||||
1949 "F" "Beatrice" 1340 0.00076332
|
||||
1950 "F" "Beatrice" 1270 0.00072216
|
||||
1951 "F" "Beatrice" 1283 0.00069454
|
||||
1952 "F" "Beatrice" 1223 0.00064291
|
||||
1953 "F" "Beatrice" 1093 0.00056659
|
||||
1954 "F" "Beatrice" 1085 0.000545
|
||||
1955 "F" "Beatrice" 1033 0.00051529
|
||||
1956 "F" "Beatrice" 1010 0.00049047
|
||||
1957 "F" "Beatrice" 981 0.00046769
|
||||
1958 "F" "Beatrice" 879 0.00042566
|
||||
1959 "F" "Beatrice" 882 0.00042434
|
||||
1960 "F" "Beatrice" 909 0.00043705
|
||||
1961 "F" "Beatrice" 766 0.00036891
|
||||
1962 "F" "Beatrice" 736 0.0003631
|
||||
1963 "F" "Beatrice" 718 0.00036118
|
||||
1964 "F" "Beatrice" 650 0.0003321
|
||||
1965 "F" "Beatrice" 639 0.00034968
|
||||
1966 "F" "Beatrice" 602 0.00034291
|
||||
1967 "F" "Beatrice" 503 0.000293
|
||||
1968 "F" "Beatrice" 494 0.00028897
|
||||
1969 "F" "Beatrice" 437 0.00024791
|
||||
1970 "F" "Beatrice" 424 0.00023146
|
||||
1971 "F" "Beatrice" 427 0.00024367
|
||||
1972 "F" "Beatrice" 309 0.00019163
|
||||
1973 "F" "Beatrice" 327 0.00021042
|
||||
1974 "F" "Beatrice" 316 0.00020177
|
||||
1975 "F" "Beatrice" 322 0.00020631
|
||||
1976 "F" "Beatrice" 282 0.0001794
|
||||
1977 "F" "Beatrice" 284 0.00017265
|
||||
1978 "F" "Beatrice" 292 0.00017764
|
||||
1979 "F" "Beatrice" 280 0.00016249
|
||||
1980 "F" "Beatrice" 287 0.0001612
|
||||
1981 "F" "Beatrice" 338 0.00018901
|
||||
1982 "F" "Beatrice" 289 0.00015932
|
||||
1983 "F" "Beatrice" 257 0.00014363
|
||||
1984 "F" "Beatrice" 235 0.00013035
|
||||
1985 "F" "Beatrice" 294 0.00015927
|
||||
1986 "F" "Beatrice" 258 0.00013983
|
||||
1987 "F" "Beatrice" 209 0.00011154
|
||||
1988 "F" "Beatrice" 286 0.00014876
|
||||
1989 "F" "Beatrice" 303 0.00015212
|
||||
1990 "F" "Beatrice" 290 0.00014119
|
||||
1991 "F" "Beatrice" 306 0.00015051
|
||||
1992 "F" "Beatrice" 286 0.00014269
|
||||
1993 "F" "Beatrice" 266 0.00013494
|
||||
1994 "F" "Beatrice" 224 0.00011493
|
||||
1995 "F" "Beatrice" 198 0.00010306
|
||||
1996 "F" "Beatrice" 215 0.00011216
|
||||
1997 "F" "Beatrice" 182 0.00009535
|
||||
1998 "F" "Beatrice" 220 0.00011352
|
||||
1999 "F" "Beatrice" 196 0.00010071
|
||||
2000 "F" "Beatrice" 218 0.00010928
|
||||
2001 "F" "Beatrice" 218 0.0001101
|
||||
2002 "F" "Beatrice" 190 0.00009625
|
||||
2003 "F" "Beatrice" 210 0.00010472
|
||||
2004 "F" "Beatrice" 234 0.00011604
|
||||
2005 "F" "Beatrice" 213 0.00010502
|
||||
2006 "F" "Beatrice" 272 0.0001302
|
||||
2007 "F" "Beatrice" 308 0.00014564
|
||||
2008 "F" "Beatrice" 338 0.00016243
|
||||
2009 "F" "Beatrice" 327 0.00016164
|
||||
2010 "F" "Beatrice" 321 0.00016392
|
||||
2011 "F" "Beatrice" 396 0.00020465
|
||||
2012 "F" "Beatrice" 404 0.00020865
|
||||
2013 "F" "Beatrice" 485 0.0002521
|
||||
2014 "F" "Beatrice" 489 0.00025056
|
||||
2015 "F" "Beatrice" 541 0.0002781
|
||||
2016 "F" "Beatrice" 557 0.00028883
|
||||
2017 "F" "Beatrice" 544 0.00029015
|
||||
|
@@ -0,0 +1,36 @@
|
||||
"Year","Price"
|
||||
1863,0.06
|
||||
1883,0.04
|
||||
1885,0.02
|
||||
1917,0.03
|
||||
1919,0.02
|
||||
1932,0.03
|
||||
1958,0.04
|
||||
1963,0.05
|
||||
1968,0.06
|
||||
1971,0.08
|
||||
1974,0.10
|
||||
1975,0.13
|
||||
1978,0.15
|
||||
1981,0.20
|
||||
1985,0.22
|
||||
1988,0.25
|
||||
1991,0.29
|
||||
1995,0.32
|
||||
1999,0.33
|
||||
2001,0.34
|
||||
2002,0.37
|
||||
2006,0.39
|
||||
2007,0.41
|
||||
2008,0.42
|
||||
2009,0.44
|
||||
2012,0.45
|
||||
2013,0.46
|
||||
2014,0.49
|
||||
2016,0.47
|
||||
2017,0.49
|
||||
2018,0.50
|
||||
2019,0.55
|
||||
2021,0.58
|
||||
2022,0.60
|
||||
2023,0.66
|
||||
|
Binary file not shown.
@@ -0,0 +1,182 @@
|
||||
#
|
||||
# Timeline
|
||||
#
|
||||
|
||||
# Load data
|
||||
egots <- read.csv("data/EGOT-winners.csv")
|
||||
|
||||
# Dimensions of data frame
|
||||
dim(egots)
|
||||
|
||||
# Column names
|
||||
colnames(egots)
|
||||
|
||||
# Range of completion years
|
||||
range(egots$completion_year)
|
||||
|
||||
# Blank plot
|
||||
plot(NA,
|
||||
xlim=range(egots$completion_year), ylim=c(0,2),
|
||||
xlab="Completion Year", ylab="",
|
||||
yaxt="n", bty="n", type="n")
|
||||
|
||||
# Baseline
|
||||
abline(h=1)
|
||||
|
||||
# Points
|
||||
points(egots$completion_year,
|
||||
rep(1, dim(egots)[1]))
|
||||
|
||||
# e.g. 2001
|
||||
egots[egots$completion_year == 2001, c("completion_year", "name")]
|
||||
|
||||
# Jitter
|
||||
points(jitter(egots$completion_year),
|
||||
jitter(rep(1, dim(egots)[1]), factor=2),
|
||||
pch=21, bg="#efe2aa", cex=2)
|
||||
|
||||
# Last rows of data frame
|
||||
tail(egots)
|
||||
|
||||
# Annotation
|
||||
anntext <- paste0(egots$name[18], "\ncompletes first \nEGOT in ",
|
||||
egots$completion_year[18])
|
||||
text(egots$completion_year[18]-1,
|
||||
1.5,
|
||||
anntext,
|
||||
pos=4)
|
||||
|
||||
|
||||
|
||||
#
|
||||
# Dot plot
|
||||
#
|
||||
|
||||
# Load data
|
||||
egots <- read.csv("data/EGOT-winners.csv")
|
||||
|
||||
# Awards and colors
|
||||
year_cols <- c("emmy_year", "grammy_year", "oscar_year", "tony_year")
|
||||
award_colors <- c("#3F78E7", "#cb84cc", "#BDB63B", "#83c4b3")
|
||||
|
||||
# Blank plot
|
||||
par(las=1)
|
||||
plot(NA, xlim=c(1930, 2023),
|
||||
ylim=c(0, dim(egots)[1]),
|
||||
type="n", xlab="", ylab="")
|
||||
|
||||
# Points
|
||||
for (i in 1:length(year_cols)) {
|
||||
points(egots[,year_cols[i]], 1:dim(egots)[1], pch=19)
|
||||
}
|
||||
|
||||
|
||||
# With color
|
||||
plot(NA, xlim=c(1930, 2023),
|
||||
ylim=c(0, dim(egots)[1]),
|
||||
type="n", xlab="", ylab="")
|
||||
for (i in 1:length(year_cols)) {
|
||||
points(egots[,year_cols[i]], 1:dim(egots)[1],
|
||||
pch=21, cex=1.5,
|
||||
col="black",
|
||||
bg=award_colors[i])
|
||||
}
|
||||
|
||||
|
||||
# Connect
|
||||
plot(NA, xlim=c(1930, 2023),
|
||||
ylim=c(0, dim(egots)[1]),
|
||||
type="n", xlab="", ylab="")
|
||||
for (j in 1:dim(egots)[1]) {
|
||||
endyrs <- range(egots[j, year_cols])
|
||||
lines(endyrs, c(j, j))
|
||||
}
|
||||
for (i in 1:length(year_cols)) {
|
||||
points(egots[,year_cols[i]], 1:dim(egots)[1],
|
||||
pch=21, cex=1.5,
|
||||
col="black",
|
||||
bg=award_colors[i])
|
||||
}
|
||||
|
||||
### With Labels
|
||||
|
||||
# Blank plot, margin
|
||||
par(las=1, mar=c(4,12,2,2))
|
||||
plot(NA, xlim=c(1930, 2023),
|
||||
ylim=c(0, dim(egots)[1]),
|
||||
yaxt="n", bty="n",
|
||||
type="n", xlab="", ylab="")
|
||||
|
||||
# Axis and grid
|
||||
axis(side=2, at=1:dim(egots)[1], labels = egots$name,
|
||||
tick=FALSE)
|
||||
grid(NULL, 0, lty=1, lwd=.5)
|
||||
|
||||
# Lines and points
|
||||
for (j in 1:dim(egots)[1]) {
|
||||
endyrs <- range(egots[j, year_cols])
|
||||
lines(endyrs, c(j, j))
|
||||
}
|
||||
for (i in 1:length(year_cols)) {
|
||||
points(egots[,year_cols[i]], 1:dim(egots)[1],
|
||||
pch=21, cex=1.5,
|
||||
col="black",
|
||||
bg=award_colors[i])
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
#
|
||||
# Bar chart, highlighted
|
||||
#
|
||||
|
||||
# Load data
|
||||
winners <- read.csv("data/hot-dog-contest-winners.csv")
|
||||
|
||||
# Bar chart
|
||||
barplot(winners$hotdogs,
|
||||
names.arg=winners$year,
|
||||
border=NA,
|
||||
space=.1,
|
||||
xlab="Year",
|
||||
ylab="Hot dogs and buns (HDB) eaten")
|
||||
|
||||
# Record years
|
||||
head(winners)
|
||||
|
||||
# Bar chart, color
|
||||
barplot(winners$hotdogs,
|
||||
names.arg=winners$year,
|
||||
col="lightblue",
|
||||
border=NA,
|
||||
space=.1,
|
||||
xlab="Year",
|
||||
ylab="Hot dogs and buns (HDB) eaten")
|
||||
|
||||
|
||||
# Bar chart, some color
|
||||
winners$barcolor <- NA
|
||||
head(winners)
|
||||
winners$barcolor[winners$record == 1] <- "#04b8c8"
|
||||
winners$barcolor[winners$record != 1] <- "lightgray"
|
||||
barplot(winners$hotdogs,
|
||||
names.arg=winners$year,
|
||||
col=winners$barcolor,
|
||||
border=NA,
|
||||
space=.1,
|
||||
xlab="Year",
|
||||
ylab="Hot dogs and buns (HDB) eaten")
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Binary file not shown.
@@ -0,0 +1,73 @@
|
||||
library(readr)
|
||||
library(dplyr)
|
||||
library(extrafont)
|
||||
|
||||
# Load data.
|
||||
accidents <- read_tsv("data/month_hour_pct.tsv")
|
||||
|
||||
# Color scale.
|
||||
getCol <- function(p) {
|
||||
if (p <= .1) {
|
||||
col <- "#dff5ee"
|
||||
} else if (p <= .2) {
|
||||
col <- "#92dee9"
|
||||
} else if (p <= .3) {
|
||||
col <- "#3fc1f9"
|
||||
} else if (p <= .4) {
|
||||
col <- "#5598fd"
|
||||
} else if (p <= .5) {
|
||||
col <- "#a75bd8"
|
||||
} else {
|
||||
col <- "#d4007f"
|
||||
}
|
||||
return(col)
|
||||
}
|
||||
|
||||
|
||||
# Setup blank plot.
|
||||
par(mar=c(0,0,0,0), bg="white", las=1, family="Inconsolata")
|
||||
plot(0:1, 0:1, type="n", xlab="", ylab="", axes=FALSE, asp=1, bty="n")
|
||||
|
||||
|
||||
par(new=TRUE, plt=c(0.33, .66, 0.1, .12))
|
||||
symbols(1:6, rep(1, 6), squares=rep(1, 6),
|
||||
bg=sapply(c(.1, .2, .3, .4, .5, .6), getCol),
|
||||
fg="white",
|
||||
inches=FALSE, bty="n",
|
||||
xaxt="n", yaxt="n", ylab="", xlab="")
|
||||
axis(1, at=c(2,3,4,5,6)-.5,
|
||||
labels=paste0(c(.1, .2, .3, .4, .5)*100, "%"), lwd=0, lwd.ticks=.5)
|
||||
|
||||
par(new=TRUE, plt=c(0.1, .99, 0.25, .95))
|
||||
plot(NA, xlim=c(0, 24), ylim=c(12,1), type="n", asp="1",
|
||||
xlab="", ylab="",
|
||||
xaxt="n", yaxt="n", bty="n", cex.main=1.7,
|
||||
main="")
|
||||
axis(2, at=1:12,
|
||||
labels=c("Jan.", "Feb.", "March", "April", "May", "June", "July", "Aug.", "Sept.", "Oct.", "Nov.", "Dec."),
|
||||
lwd=0, lwd.ticks=.8)
|
||||
axis(1, at=c(0, 6, 12, 18, 23),
|
||||
labels=c("12am", "6am", "noon", "6pm", "11pm"),
|
||||
lwd=0, lwd.ticks=.8)
|
||||
|
||||
|
||||
|
||||
# Get color.
|
||||
squarecol <- sapply(accidents$pct_drunk_all, getCol)
|
||||
|
||||
# Add squares.
|
||||
symbols(accidents$HOUR, accidents$MONTH,
|
||||
squares=rep(1, dim(accidents)[1]),
|
||||
inches=FALSE,
|
||||
bg=squarecol,
|
||||
fg="#ffffff",
|
||||
add=TRUE)
|
||||
|
||||
# Make a matrix.
|
||||
pmat <- matrix(NA, nrow=12, ncol=24)
|
||||
for (i in 1:dim(accidents)[1]) {
|
||||
pmat[accidents$MONTH[i], accidents$HOUR[i]+1] <- accidents$pct_drunk_all[i]
|
||||
}
|
||||
# pmat[accidents$MONTH, accidents$HOUR+1] <- accidents$pct_drunk_all
|
||||
row.names(pmat) <- c("Jan.", "Feb", "March", "April", "May", "June", "July", "Aug", "Sept", "Oct", "Nov", "Dec")
|
||||
write.table(pmat, file="month_hour_pct_matrix.csv", sep=",")
|
||||
@@ -0,0 +1,42 @@
|
||||
import seaborn as sns
|
||||
import pandas as pd
|
||||
import matplotlib.colors as mc
|
||||
|
||||
# For defining color map
|
||||
def NonLinCdict(steps, hexcol_array):
|
||||
cdict = {'red': (), 'green': (), 'blue': ()}
|
||||
for s, hexcol in zip(steps, hexcol_array):
|
||||
rgb = mc.hex2color(hexcol)
|
||||
cdict['red'] = cdict['red'] + ((s, rgb[0], rgb[0]),)
|
||||
cdict['green'] = cdict['green'] + ((s, rgb[1], rgb[1]),)
|
||||
cdict['blue'] = cdict['blue'] + ((s, rgb[2], rgb[2]),)
|
||||
return cdict
|
||||
|
||||
# Load data
|
||||
thedata = pd.read_csv("data/month_hour_pct_matrix.csv")
|
||||
mns = thedata.iloc[0:12, 0]
|
||||
pmat = thedata.iloc[0:12, 1:25]
|
||||
|
||||
# Set figure size
|
||||
sns.set(rc={'figure.figsize':(11,4.5), 'pdf.fonttype': 42})
|
||||
|
||||
# Make color map
|
||||
# hc = ['#dff5ee', '#92dee9', '#3fc1f9', '#5598fd', '#a75bd8', '#d4007f']
|
||||
hc = ['#f0f0f0', '#c3dde3', '#acc6cc', '#aeaaaa', '#c0877c', '#da5241']
|
||||
th = [0, 0.1, 0.2, 0.3, .4, 1]
|
||||
cdict = NonLinCdict(th, hc)
|
||||
cm = mc.LinearSegmentedColormap('custom', cdict)
|
||||
|
||||
# Heatmap
|
||||
p1 = sns.heatmap(
|
||||
pmat,
|
||||
square=True,
|
||||
linewidths=0.1,
|
||||
yticklabels=mns,
|
||||
cmap=cm)
|
||||
p1.set_xticks([0.5,6.5,12.5,18.5,23.5])
|
||||
p1.set_xticklabels(["12am", "6am", "noon", "6pm", "11pm"])
|
||||
fig = p1.get_figure()
|
||||
|
||||
# Save file
|
||||
fig.savefig("pmat-heatmap.pdf")
|
||||
Binary file not shown.
Binary file not shown.
@@ -0,0 +1,158 @@
|
||||
#
|
||||
# Bar chart
|
||||
#
|
||||
|
||||
# Load data
|
||||
winners <- read.csv("data/hot-dog-contest-winners.csv")
|
||||
head(winners)
|
||||
|
||||
# Default bar chart
|
||||
barplot(winners$hotdogs)
|
||||
|
||||
# Year labels
|
||||
barplot(winners$hotdogs, names.arg=winners$year)
|
||||
|
||||
# Axis labels
|
||||
barplot(winners$hotdogs,
|
||||
names.arg=winners$year,
|
||||
border=NA,
|
||||
space=.1,
|
||||
xlab="Year",
|
||||
ylab="Hot dogs and buns (HDB) eaten",
|
||||
main="Contest Winners")
|
||||
|
||||
|
||||
|
||||
|
||||
#
|
||||
# Line chart
|
||||
#
|
||||
|
||||
# Graphical parameter to make axis labels horizontal
|
||||
par(las=1)
|
||||
|
||||
# Line chart with plot()
|
||||
plot(winners$year, winners$hotdogs,
|
||||
type="l",
|
||||
xlab="",
|
||||
ylab="Hot dogs and buns (HDB) eaten",
|
||||
main="Nathan's Hot Dog Eating Contest, Winning Results, 1980-2023")
|
||||
|
||||
par(mfrow=c(3,2), las=1)
|
||||
for (currtype in c("p", "l", "b", "c", "o", "n")) {
|
||||
plot(winners$year, winners$hotdogs, type=currtype,
|
||||
xlab="", ylab="",
|
||||
main=paste0("type='", currtype, "'"))
|
||||
}
|
||||
|
||||
# Text
|
||||
text(2001, 50,
|
||||
"In 2001, Takeru Kobayashi nearly doubled the previous record with 50 HDBs.",
|
||||
pos=2)
|
||||
|
||||
# Text with line breaks
|
||||
text(2001, 48,
|
||||
"In 2001, Takeru Kobayashi
|
||||
nearly doubled the previous
|
||||
record with 50 HDBs.",
|
||||
pos=2)
|
||||
|
||||
# Find documentation
|
||||
?text
|
||||
|
||||
# Wrapped text
|
||||
anno <- "In 2001, Takeru Kobayashi nearly doubled the previous record with 50 HDBs."
|
||||
text(2001, 48,
|
||||
paste(strwrap(anno, 30), collapse="\n"),
|
||||
pos=2)
|
||||
|
||||
|
||||
#
|
||||
# Dot plot
|
||||
#
|
||||
|
||||
par(las=1)
|
||||
plot(winners$year, winners$hotdogs,
|
||||
type="p",
|
||||
bty="n",
|
||||
xlab="",
|
||||
ylab="Hot dogs and buns (HDB) eaten",
|
||||
main="Nathan's Hot Dog Eating Contest, Winning Results, 1980-2023")
|
||||
|
||||
|
||||
|
||||
|
||||
#
|
||||
# Step chart
|
||||
#
|
||||
|
||||
# Load data
|
||||
postage <- read.csv("data/us-postage.csv")
|
||||
|
||||
# Summary
|
||||
head(postage)
|
||||
summary(postage)
|
||||
|
||||
# Plot as regular time series
|
||||
par(las=1)
|
||||
plot(postage$Year, postage$Price, type="l",
|
||||
xlab="Year", ylab="Postage Rate (Dollars)",
|
||||
main="US Postage Rates for Letters, First Ounce, 1863-2023")
|
||||
|
||||
# Default step chart
|
||||
plot(postage$Year, postage$Price, type="s")
|
||||
|
||||
# Add labels
|
||||
par(las=1)
|
||||
plot(postage$Year, postage$Price, type="s",
|
||||
xlab="Year", ylab="Postage Rate (Dollars)",
|
||||
main="US Postage Rates for Letters, First Ounce, 1863-2023")
|
||||
|
||||
# Change limits ("zoom")
|
||||
postagesub <- postage[postage$Year >= 1991,]
|
||||
head(postagesub)
|
||||
|
||||
par(las=1)
|
||||
plot(postagesub$Year, postagesub$Price, type="s",
|
||||
xlab="Year", ylab="Postage Rate (Dollars)",
|
||||
main="US Postage Rates for Letters, First Ounce, 1991-2023")
|
||||
|
||||
|
||||
|
||||
|
||||
#
|
||||
# Smoothing
|
||||
#
|
||||
|
||||
# Load data.
|
||||
# install.packages("babynames")
|
||||
library(babynames)
|
||||
nathan <- babynames[babynames$name == "Nathan" & babynames$sex == "M", ]
|
||||
beatrice <- babynames[babynames$name == "Beatrice" & babynames$sex == "F",]
|
||||
|
||||
# Line chart, no smoothing
|
||||
par(las=1, mar=c(4,5,3,2))
|
||||
plot(nathan$year, nathan$prop,
|
||||
type="l",
|
||||
xlab="", ylab="Proportion")
|
||||
lines(beatrice$year, beatrice$prop,
|
||||
lwd=2)
|
||||
|
||||
# Splines
|
||||
natcoords <- spline(nathan$year, nathan$prop)
|
||||
beacoords <- spline(beatrice$year, beatrice$prop)
|
||||
par(las=1, mar=c(4,5,3,2))
|
||||
plot(natcoords,
|
||||
col="#ac5c5a",
|
||||
type="l",
|
||||
xlab="", ylab="Proportion")
|
||||
lines(beacoords, lwd=2, col="#176572")
|
||||
|
||||
natcoords <- spline(nathan$year, nathan$prop, n=20)
|
||||
beacoords <- spline(beatrice$year, beatrice$prop, n=20)
|
||||
par(las=1, mar=c(4,5,3,2))
|
||||
plot(natcoords,
|
||||
col="#ac5c5a",
|
||||
type="l",
|
||||
xlab="", ylab="Proportion")
|
||||
lines(beacoords, lwd=2, col="#176572")
|
||||
Binary file not shown.
@@ -0,0 +1,323 @@
|
||||
"year" "htype" "n" "p"
|
||||
1976 "composite" 2628779.59 0.0359171491054953
|
||||
1976 "extended" 5395372.77 0.0737172522934185
|
||||
1976 "nuclear-father" 617377.93 0.00843526602633583
|
||||
1976 "nuclear-married-children" 27239504.11 0.372174728684127
|
||||
1976 "nuclear-married-nochildren" 16911072.87 0.23105684786821
|
||||
1976 "nuclear-mother" 5147660.37 0.0703327451860424
|
||||
1976 "single" 15250328.33 0.20836601083637
|
||||
1977 "composite" 2975564.08 0.0399304190012852
|
||||
1977 "extended" 5419860.21 0.0727315168805551
|
||||
1977 "nuclear-father" 633988.84 0.00850777847249008
|
||||
1977 "nuclear-married-children" 27274570.78 0.366009606933288
|
||||
1977 "nuclear-married-nochildren" 17061382.14 0.228954282036918
|
||||
1977 "nuclear-mother" 5322025.98 0.0714186357959817
|
||||
1977 "single" 15831337.16 0.212447760879482
|
||||
1978 "composite" 3271869.12 0.0428525973962617
|
||||
1978 "extended" 5788589.5 0.0758147976700633
|
||||
1978 "nuclear-father" 675047.27 0.00884128546216286
|
||||
1978 "nuclear-married-children" 26920265.66 0.352582350888287
|
||||
1978 "nuclear-married-nochildren" 17049146.71 0.22329750766847
|
||||
1978 "nuclear-mother" 5672523.72 0.0742946512462897
|
||||
1978 "single" 16974268.74 0.222316809668466
|
||||
1979 "composite" 3688161.69 0.0474735256922412
|
||||
1979 "extended" 5632829.34 0.0725050284854784
|
||||
1979 "nuclear-father" 676854.46 0.00871238039369094
|
||||
1979 "nuclear-married-children" 27075789.32 0.348515951295164
|
||||
1979 "nuclear-married-nochildren" 17411606.71 0.224119880842422
|
||||
1979 "nuclear-mother" 5716536.38 0.0735824943473564
|
||||
1979 "single" 17487031.52 0.225090738943647
|
||||
1980 "composite" 3985795.41 0.0501995587151689
|
||||
1980 "extended" 5534101.84 0.0696998821253608
|
||||
1980 "nuclear-father" 732158.06 0.00922124889540031
|
||||
1980 "nuclear-married-children" 27172136.02 0.342222592291195
|
||||
1980 "nuclear-married-nochildren" 17932025.5 0.225846957601157
|
||||
1980 "nuclear-mother" 6030410.98 0.0759507046717957
|
||||
1980 "single" 18012385.09 0.226859055699923
|
||||
1981 "composite" 4300180.92 0.0520402621932969
|
||||
1981 "extended" 5880761.12 0.0711682499584102
|
||||
1981 "nuclear-father" 816029.05 0.00987548349927263
|
||||
1981 "nuclear-married-children" 27844174.13 0.336966780988604
|
||||
1981 "nuclear-married-nochildren" 18291186.36 0.22135769441088
|
||||
1981 "nuclear-mother" 6364050.5 0.0770169587728375
|
||||
1981 "single" 19135425.27 0.231574570176698
|
||||
1982 "composite" 4425843.87 0.0528187007039854
|
||||
1982 "extended" 6109930.19 0.0729168455795199
|
||||
1982 "nuclear-father" 804656.94 0.00960289954449856
|
||||
1982 "nuclear-married-children" 27429330.09 0.327345839367472
|
||||
1982 "nuclear-married-nochildren" 18762701.21 0.223916958826045
|
||||
1982 "nuclear-mother" 6695897.7 0.0799098718683007
|
||||
1982 "single" 19564762.72 0.233488884110178
|
||||
1983 "composite" 4647353 0.0551498353045369
|
||||
1983 "extended" 6297265.44 0.0747292387483697
|
||||
1983 "nuclear-father" 895631.94 0.0106284058870679
|
||||
1983 "nuclear-married-children" 27629102.24 0.32787275641601
|
||||
1983 "nuclear-married-nochildren" 18589581.26 0.220601349815541
|
||||
1983 "nuclear-mother" 6656862.12 0.0789965491244178
|
||||
1983 "single" 19551962.45 0.232021864704056
|
||||
1984 "composite" 4912045.91 0.0572437966280052
|
||||
1984 "extended" 6149223.62 0.0716615668446401
|
||||
1984 "nuclear-father" 881814.77 0.0102764563447354
|
||||
1984 "nuclear-married-children" 27962928.9 0.325873219510477
|
||||
1984 "nuclear-married-nochildren" 18694537.6 0.217861625896122
|
||||
1984 "nuclear-mother" 6915270.03 0.0805888866834837
|
||||
1984 "single" 20293405.66 0.236494448092536
|
||||
1985 "composite" 5111709.65 0.0586315936717927
|
||||
1985 "extended" 6182269.17 0.070910970842229
|
||||
1985 "nuclear-father" 984020.75 0.0112867726707859
|
||||
1985 "nuclear-married-children" 27903585.15 0.320055671882903
|
||||
1985 "nuclear-married-nochildren" 19078325.57 0.21882945420392
|
||||
1985 "nuclear-mother" 7042838.78 0.0807817520787598
|
||||
1985 "single" 20880786.8 0.23950378464961
|
||||
1986 "composite" 5315550.32 0.0598521155387804
|
||||
1986 "extended" 6386386.76 0.071909536214278
|
||||
1986 "nuclear-father" 1026250.91 0.011555395836625
|
||||
1986 "nuclear-married-children" 28297174.2 0.31862095882471
|
||||
1986 "nuclear-married-nochildren" 19137166.47 0.215480962401521
|
||||
1986 "nuclear-mother" 7219271.06 0.0812876597110068
|
||||
1986 "single" 21429602.72 0.241293371473079
|
||||
1987 "composite" 5591725.67 0.062224080653711
|
||||
1987 "extended" 6547396.75 0.0728586786060707
|
||||
1987 "nuclear-father" 1117979.07 0.0124407426126183
|
||||
1987 "nuclear-married-children" 28339302.15 0.315356497567858
|
||||
1987 "nuclear-married-nochildren" 19645095.73 0.218608367665754
|
||||
1987 "nuclear-mother" 7207922.6 0.0802089343571296
|
||||
1987 "single" 21414913.69 0.238302698536858
|
||||
1988 "composite" 5772345.02 0.0631306965698012
|
||||
1988 "extended" 6562520.83 0.0717726521571869
|
||||
1988 "nuclear-father" 1086020.17 0.0118775315029513
|
||||
1988 "nuclear-married-children" 28511394.61 0.311822005730658
|
||||
1988 "nuclear-married-nochildren" 20001466.94 0.21875105108323
|
||||
1988 "nuclear-mother" 7308102.59 0.0799268937514529
|
||||
1988 "single" 22192987.94 0.242719169204719
|
||||
1989 "composite" 6066472.98 0.0651619692730516
|
||||
1989 "extended" 6591383.41 0.0708002037832075
|
||||
1989 "nuclear-father" 1057515.98 0.0113591248195951
|
||||
1989 "nuclear-married-children" 28605714.48 0.307263329800481
|
||||
1989 "nuclear-married-nochildren" 20268357.28 0.217709050818948
|
||||
1989 "nuclear-mother" 7572072.2 0.0813341026419157
|
||||
1989 "single" 22936851.44 0.246372218862801
|
||||
1990 "composite" 6376907.97 0.068110148768524
|
||||
1990 "extended" 6640379.72 0.0709242242065303
|
||||
1990 "nuclear-father" 1097403.51 0.011721090640924
|
||||
1990 "nuclear-married-children" 28286335.5 0.302119228956253
|
||||
1990 "nuclear-married-nochildren" 20495481.49 0.218907078467126
|
||||
1990 "nuclear-mother" 7512212.73 0.0802360531198163
|
||||
1990 "single" 23217678.16 0.247982175840827
|
||||
1991 "composite" 6563325.14 0.0693664548034937
|
||||
1991 "extended" 6884046.14 0.0727560901295643
|
||||
1991 "nuclear-father" 1070677.13 0.0113157698518771
|
||||
1991 "nuclear-married-children" 28122425.55 0.297220222869942
|
||||
1991 "nuclear-married-nochildren" 20433478.66 0.215957299648124
|
||||
1991 "nuclear-mother" 7717835.25 0.0815682384508434
|
||||
1991 "single" 23826355.13 0.251815924246156
|
||||
1992 "composite" 6901645.33 0.0719078532368738
|
||||
1992 "extended" 6887820.44 0.0717638124880954
|
||||
1992 "nuclear-father" 1202146.49 0.0125250964427845
|
||||
1992 "nuclear-married-children" 28218307.73 0.29400495589387
|
||||
1992 "nuclear-married-nochildren" 20701670.87 0.21568954060959
|
||||
1992 "nuclear-mother" 7853020.91 0.0818201817192453
|
||||
1992 "single" 24214408.87 0.252288559609541
|
||||
1993 "composite" 6990232.77 0.0723608210010821
|
||||
1993 "extended" 6926553.28 0.0717016297654046
|
||||
1993 "nuclear-father" 1174704.61 0.0121601944899692
|
||||
1993 "nuclear-married-children" 28640691.62 0.296479963951474
|
||||
1993 "nuclear-married-nochildren" 21042693.56 0.217827736525544
|
||||
1993 "nuclear-mother" 8027258.15 0.083095800845789
|
||||
1993 "single" 23800318.46 0.246373853420737
|
||||
1994 "composite" 7570039.74 0.0778308390078657
|
||||
1994 "extended" 7250256.28 0.0745430075238214
|
||||
1994 "nuclear-father" 1125699.5 0.011573801401964
|
||||
1994 "nuclear-married-children" 28441814.12 0.292422540950275
|
||||
1994 "nuclear-married-nochildren" 20819849.49 0.214057839784099
|
||||
1994 "nuclear-mother" 8329377.25 0.0856379149973299
|
||||
1994 "single" 23725691.82 0.243934056334644
|
||||
1995 "composite" 7575983.06 0.0764573886371595
|
||||
1995 "extended" 7391950.41 0.0746001173455608
|
||||
1995 "nuclear-father" 1271997.74 0.0128370964906525
|
||||
1995 "nuclear-married-children" 28512148.92 0.287746743042085
|
||||
1995 "nuclear-married-nochildren" 21369592.44 0.215663527922776
|
||||
1995 "nuclear-mother" 8160804.89 0.0823594543606017
|
||||
1995 "single" 24805173.78 0.250335672201165
|
||||
1996 "composite" 7970055.87 0.0799532380844666
|
||||
1996 "extended" 7450091.91 0.0747371137602061
|
||||
1996 "nuclear-father" 1341474.39 0.0134572734542054
|
||||
1996 "nuclear-married-children" 28115191.55 0.282043268008802
|
||||
1996 "nuclear-married-nochildren" 21641260.04 0.2170987060378
|
||||
1996 "nuclear-mother" 8219614.73 0.0824567385962726
|
||||
1996 "single" 24946277.55 0.250253662058248
|
||||
1997 "composite" 8462347.48 0.0837161827210115
|
||||
1997 "extended" 7739944.91 0.076569609540085
|
||||
1997 "nuclear-father" 1416166.08 0.0140098263037266
|
||||
1997 "nuclear-married-children" 28304874.48 0.280014032685759
|
||||
1997 "nuclear-married-nochildren" 21267509.21 0.21039489234554
|
||||
1997 "nuclear-mother" 8456456.38 0.083657903336338
|
||||
1997 "single" 25436472.9 0.251637553067539
|
||||
1998 "composite" 8468892.73 0.0825555129486877
|
||||
1998 "extended" 7637700.89 0.0744529816145868
|
||||
1998 "nuclear-father" 1437506.89 0.0140129438941686
|
||||
1998 "nuclear-married-children" 28591491.86 0.278712383274044
|
||||
1998 "nuclear-married-nochildren" 21837649.42 0.212875331750921
|
||||
1998 "nuclear-mother" 8246779.43 0.0803903329188037
|
||||
1998 "single" 26364196.69 0.257000513598788
|
||||
1999 "composite" 8780403.95 0.0844332209772884
|
||||
1999 "extended" 7767278.64 0.0746909091583756
|
||||
1999 "nuclear-father" 1529191.62 0.0147048558020019
|
||||
1999 "nuclear-married-children" 28251115.73 0.271665484967356
|
||||
1999 "nuclear-married-nochildren" 22528331.35 0.21663463206885
|
||||
1999 "nuclear-mother" 8467102.21 0.08142048088052
|
||||
1999 "single" 26668865.89 0.256450416145608
|
||||
2000 "composite" 9392882.58 0.0896421842307627
|
||||
2000 "extended" 7988673.88 0.076240937711205
|
||||
2000 "nuclear-father" 1439843.41 0.0137413309623923
|
||||
2000 "nuclear-married-children" 28200481.89 0.269134929713948
|
||||
2000 "nuclear-married-nochildren" 22899238.79 0.218541833656927
|
||||
2000 "nuclear-mother" 8092547.86 0.0772322724130535
|
||||
2000 "single" 26768278.4 0.255466511311711
|
||||
2001 "composite" 9638999.14 0.089011172432275
|
||||
2001 "extended" 8385291.92 0.0774338345864903
|
||||
2001 "nuclear-father" 1512920.51 0.0139710385316971
|
||||
2001 "nuclear-married-children" 28686320.07 0.264903331259992
|
||||
2001 "nuclear-married-nochildren" 23687060.94 0.218737758466502
|
||||
2001 "nuclear-mother" 8118904.52 0.0749738847046828
|
||||
2001 "single" 28260270.09 0.26096898001836
|
||||
2002 "composite" 9539477.56 0.0872071033449697
|
||||
2002 "extended" 8395685.61 0.0767508931215668
|
||||
2002 "nuclear-father" 1632783.2 0.0149264246775303
|
||||
2002 "nuclear-married-children" 28600205.77 0.261454684974571
|
||||
2002 "nuclear-married-nochildren" 23926565.69 0.218729639405749
|
||||
2002 "nuclear-mother" 8449644.1 0.0772441657965296
|
||||
2002 "single" 28844405.66 0.263687088679084
|
||||
2003 "composite" 9699661.9 0.087084876736775
|
||||
2003 "extended" 8808481.99 0.0790837429433754
|
||||
2003 "nuclear-father" 1645783.92 0.0147760706802127
|
||||
2003 "nuclear-married-children" 28833111.24 0.258867573340172
|
||||
2003 "nuclear-married-nochildren" 24310278.72 0.218260971113627
|
||||
2003 "nuclear-mother" 8587657.18 0.0771011479253706
|
||||
2003 "single" 29496728.32 0.264825617260468
|
||||
2004 "composite" 9804628.37 0.0874503363035857
|
||||
2004 "extended" 9120481.7 0.0813482328770508
|
||||
2004 "nuclear-father" 1646594.38 0.0146864548917721
|
||||
2004 "nuclear-married-children" 28676158.31 0.255771008698044
|
||||
2004 "nuclear-married-nochildren" 24766225.94 0.220897183013127
|
||||
2004 "nuclear-mother" 8445921.14 0.0753316307578279
|
||||
2004 "single" 29656521.49 0.264515153458592
|
||||
2005 "composite" 10006409.59 0.0881810599961824
|
||||
2005 "extended" 9431784.83 0.0831172036767798
|
||||
2005 "nuclear-father" 1589058.18 0.0140035077964467
|
||||
2005 "nuclear-married-children" 29027481.97 0.255803453387787
|
||||
2005 "nuclear-married-nochildren" 24557059.8 0.216408047669538
|
||||
2005 "nuclear-mother" 8618682.22 0.0759517714215265
|
||||
2005 "single" 30245247 0.26653495605174
|
||||
2006 "composite" 10297404.01 0.0899257664205084
|
||||
2006 "extended" 9531252.67 0.0832350756039985
|
||||
2006 "nuclear-father" 1681913.6 0.0146879125443847
|
||||
2006 "nuclear-married-children" 29015036.13 0.253384188789247
|
||||
2006 "nuclear-married-nochildren" 24607590.04 0.2148945881855
|
||||
2006 "nuclear-mother" 8818047.19 0.0770067534616388
|
||||
2006 "single" 30558806.37 0.266865714994722
|
||||
2007 "composite" 10313204.37 0.0888063800538201
|
||||
2007 "extended" 9516294 0.0819442329802185
|
||||
2007 "nuclear-father" 1667378.31 0.0143576939406037
|
||||
2007 "nuclear-married-children" 29236392.33 0.251752808876081
|
||||
2007 "nuclear-married-nochildren" 25221081.39 0.217177208841511
|
||||
2007 "nuclear-mother" 8963936.68 0.0771879174525132
|
||||
2007 "single" 31213058.03 0.268773757855253
|
||||
2008 "composite" 10646809.08 0.0910911600605037
|
||||
2008 "extended" 9635855.95 0.0824417240946155
|
||||
2008 "nuclear-father" 1753269.87 0.0150004931202757
|
||||
2008 "nuclear-married-children" 28594729.28 0.244648611819688
|
||||
2008 "nuclear-married-nochildren" 25265802.88 0.216167236296419
|
||||
2008 "nuclear-mother" 8772654.66 0.0750564120935269
|
||||
2008 "single" 32211693.86 0.275594362514971
|
||||
2009 "composite" 10715530.7 0.0913819783626526
|
||||
2009 "extended" 10137683.76 0.0864541032954844
|
||||
2009 "nuclear-father" 1644005.32 0.0140200670210693
|
||||
2009 "nuclear-married-children" 28479418.15 0.242872298724713
|
||||
2009 "nuclear-married-nochildren" 25864081.03 0.220568720227114
|
||||
2009 "nuclear-mother" 8713438.68 0.0743081502178945
|
||||
2009 "single" 31706716.9 0.270394682151072
|
||||
2010 "composite" 11920662.91 0.100582419516824
|
||||
2010 "extended" 10708170.68 0.0903518305756296
|
||||
2010 "nuclear-father" 1734387.75 0.014634162344193
|
||||
2010 "nuclear-married-children" 28212122.1 0.238044102240456
|
||||
2010 "nuclear-married-nochildren" 25540672.52 0.21550333715027
|
||||
2010 "nuclear-mother" 8797920.66 0.0742338033866819
|
||||
2010 "single" 31602430.03 0.266650344785945
|
||||
2011 "composite" 11987785.45 0.0999028865393945
|
||||
2011 "extended" 10554704.76 0.0879599886478688
|
||||
2011 "nuclear-father" 1829748.99 0.0152486217330109
|
||||
2011 "nuclear-married-children" 27741032.61 0.231186088947102
|
||||
2011 "nuclear-married-nochildren" 25883881.52 0.215709105695722
|
||||
2011 "nuclear-mother" 8935779.14 0.0744683105389168
|
||||
2011 "single" 33061452.73 0.275524997897985
|
||||
2012 "composite" 12227450.05 0.100915055882802
|
||||
2012 "extended" 10410830.86 0.0859222138489376
|
||||
2012 "nuclear-father" 1887319.43 0.015576342161966
|
||||
2012 "nuclear-married-children" 27640615.09 0.228122315367167
|
||||
2012 "nuclear-married-nochildren" 26463618.49 0.218408378513843
|
||||
2012 "nuclear-mother" 9293508.56 0.0767007783180191
|
||||
2012 "single" 33242423.55 0.274354915907265
|
||||
2013 "composite" 12848231.4 0.104841230811202
|
||||
2013 "extended" 10740467.89 0.0876419359224646
|
||||
2013 "nuclear-father" 1926537.52 0.0157204955695895
|
||||
2013 "nuclear-married-children" 27969500.34 0.228230388255612
|
||||
2013 "nuclear-married-nochildren" 26354238.98 0.215049897977068
|
||||
2013 "nuclear-mother" 9094804.68 0.0742133673463169
|
||||
2013 "single" 33615633.2 0.274302684117747
|
||||
2014 "composite" 24486978.73 0.0991060915758774
|
||||
2014 "extended" 22116766.3 0.0895131363676436
|
||||
2014 "nuclear-father" 3870159.48 0.0156636873853376
|
||||
2014 "nuclear-married-children" 56221156.52 0.22754375490785
|
||||
2014 "nuclear-married-nochildren" 53422034.48 0.216214874841138
|
||||
2014 "nuclear-mother" 18405813.22 0.0744938046715825
|
||||
2014 "single" 68555533.58 0.277464650250571
|
||||
2015 "composite" 12766210.56 0.102352983882629
|
||||
2015 "extended" 11096943.91 0.0889696528056223
|
||||
2015 "nuclear-father" 1883948.25 0.015104538967275
|
||||
2015 "nuclear-married-children" 28386300.82 0.227586923830036
|
||||
2015 "nuclear-married-nochildren" 26848404.8 0.215256855654487
|
||||
2015 "nuclear-mother" 8763640.55 0.0702624130905221
|
||||
2015 "single" 34981843.62 0.280466631769429
|
||||
2016 "composite" 12950225.76 0.102724489386347
|
||||
2016 "extended" 10825457.21 0.0858702840305541
|
||||
2016 "nuclear-father" 1975140.39 0.0156673166776592
|
||||
2016 "nuclear-married-children" 28214026.71 0.223800846489452
|
||||
2016 "nuclear-married-nochildren" 27380345.12 0.217187871763709
|
||||
2016 "nuclear-mother" 9113049.74 0.0722870317971879
|
||||
2016 "single" 35609315.37 0.282462159855092
|
||||
2017 "composite" 12831835.37 0.101421934334673
|
||||
2017 "extended" 11396121.89 0.0900741548399015
|
||||
2017 "nuclear-father" 2042132.35 0.0161408720679691
|
||||
2017 "nuclear-married-children" 27829541.1 0.21996275736261
|
||||
2017 "nuclear-married-nochildren" 28026002.2 0.221515572233513
|
||||
2017 "nuclear-mother" 8881544.64 0.0701991111399789
|
||||
2017 "single" 35512154.33 0.280685598021354
|
||||
2018 "composite" 13630453.86 0.106755566845541
|
||||
2018 "extended" 11336580.16 0.0887896363174157
|
||||
2018 "nuclear-father" 1989927.08 0.0155853792976115
|
||||
2018 "nuclear-married-children" 27984330.86 0.219177082028028
|
||||
2018 "nuclear-married-nochildren" 28186771.08 0.220762621340248
|
||||
2018 "nuclear-mother" 8735020.99 0.0684138713775119
|
||||
2018 "single" 35816008.15 0.280515842793643
|
||||
2019 "composite" 13332222.8 0.103612014327867
|
||||
2019 "extended" 11564485.39 0.0898739575461556
|
||||
2019 "nuclear-father" 1893593.99 0.0147161572804681
|
||||
2019 "nuclear-married-children" 27918305.71 0.216968463145867
|
||||
2019 "nuclear-married-nochildren" 28919282.67 0.224747604004613
|
||||
2019 "nuclear-mother" 8500056.56 0.0660586006770303
|
||||
2019 "single" 36546539.97 0.284023203017999
|
||||
2020 "composite" 13110723.7 0.101958995681941
|
||||
2020 "extended" 11639529.63 0.0905178675441837
|
||||
2020 "nuclear-father" 1901185.67 0.014785071057374
|
||||
2020 "nuclear-married-children" 28271692.12 0.219862259379643
|
||||
2020 "nuclear-married-nochildren" 29049611.21 0.225911952055129
|
||||
2020 "nuclear-mother" 8305042.62 0.0645863511432945
|
||||
2020 "single" 36310414.77 0.282377503138435
|
||||
2021 "composite" 14105790.72 0.108487098946671
|
||||
2021 "extended" 11643889.72 0.0895527121628647
|
||||
2021 "nuclear-father" 2142912.65 0.0164810595385484
|
||||
2021 "nuclear-married-children" 27565701.82 0.212006762346236
|
||||
2021 "nuclear-married-nochildren" 28881925.41 0.22212978782412
|
||||
2021 "nuclear-mother" 8638090.98 0.0664352285851585
|
||||
2021 "single" 37044436.63 0.284907350596401
|
||||
|
@@ -0,0 +1,20 @@
|
||||
waymet category year p
|
||||
Met Through Family Friends and Family 2010 0.0638
|
||||
Met Through Friend Friends and Family 2010 0.1722
|
||||
Met Through Neighbors Friends and Family 2010 0.0304
|
||||
Met Through Coworker Work 2010 0.0853
|
||||
Met Online Online 2010 0.189
|
||||
Primary or Secondary School School 2010 0.0461
|
||||
College School 2010 0.0398
|
||||
Military Work 2010 0.0051
|
||||
Church Group Setting 2010 0.0318
|
||||
Volunteering Group Setting 2010 0.0345
|
||||
Customer Work 2010 0.0343
|
||||
Bar or Restaurant Group Setting 2010 0.1528
|
||||
Party Group Setting 2010 0.0693
|
||||
Public Group Setting 2010 0.0236
|
||||
Blind Date Dating 2010 0.0068
|
||||
Vacation Group Setting 2010 0.0085
|
||||
Singles Service Dating 2010 0.0024
|
||||
Business Trip Work 2010 0.0002
|
||||
Work Neighbors Work 2010 0.0039
|
||||
|
@@ -0,0 +1,115 @@
|
||||
"waymet" "year" "p"
|
||||
"met_through_family" 1960 0.1353
|
||||
"met_through_friend" 1960 0.1919
|
||||
"met_through_as_nghbrs" 1960 0.0477
|
||||
"met_as_through_cowork" 1960 0.0799
|
||||
"met_online" 1960 0.0042
|
||||
"school" 1960 0.1224
|
||||
"college" 1960 0.0417
|
||||
"mil" 1960 0.048
|
||||
"church" 1960 0.0322
|
||||
"vol_org" 1960 0.032
|
||||
"customer" 1960 0.046
|
||||
"bar_restaurant" 1960 0.0871
|
||||
"party" 1960 0.0514
|
||||
"public" 1960 0.0288
|
||||
"blind_date" 1960 0.0393
|
||||
"vacation" 1960 0.0102
|
||||
"single_serve_nonint" 1960 0
|
||||
"business_trip" 1960 0
|
||||
"work_neighbors" 1960 0.0019
|
||||
"met_through_family" 1970 0.1285
|
||||
"met_through_friend" 1970 0.2097
|
||||
"met_through_as_nghbrs" 1970 0.0391
|
||||
"met_as_through_cowork" 1970 0.1007
|
||||
"met_online" 1970 0.0032
|
||||
"school" 1970 0.0973
|
||||
"college" 1970 0.0646
|
||||
"mil" 1970 0.019
|
||||
"church" 1970 0.0455
|
||||
"vol_org" 1970 0.0342
|
||||
"customer" 1970 0.0312
|
||||
"bar_restaurant" 1970 0.1008
|
||||
"party" 1970 0.0589
|
||||
"public" 1970 0.0196
|
||||
"blind_date" 1970 0.0351
|
||||
"vacation" 1970 0.007
|
||||
"single_serve_nonint" 1970 0.0023
|
||||
"business_trip" 1970 0
|
||||
"work_neighbors" 1970 0.0033
|
||||
"met_through_family" 1980 0.1055
|
||||
"met_through_friend" 1980 0.1769
|
||||
"met_through_as_nghbrs" 1980 0.0374
|
||||
"met_as_through_cowork" 1980 0.1639
|
||||
"met_online" 1980 0.0002
|
||||
"school" 1980 0.0532
|
||||
"college" 1980 0.039
|
||||
"mil" 1980 0.0096
|
||||
"church" 1980 0.0415
|
||||
"vol_org" 1980 0.0406
|
||||
"customer" 1980 0.0569
|
||||
"bar_restaurant" 1980 0.1381
|
||||
"party" 1980 0.0576
|
||||
"public" 1980 0.0181
|
||||
"blind_date" 1980 0.0257
|
||||
"vacation" 1980 0.0087
|
||||
"single_serve_nonint" 1980 0.006
|
||||
"business_trip" 1980 0.0013
|
||||
"work_neighbors" 1980 0.02
|
||||
"met_through_family" 1990 0.1025
|
||||
"met_through_friend" 1990 0.1755
|
||||
"met_through_as_nghbrs" 1990 0.0355
|
||||
"met_as_through_cowork" 1990 0.1524
|
||||
"met_online" 1990 0.0153
|
||||
"school" 1990 0.0671
|
||||
"college" 1990 0.0511
|
||||
"mil" 1990 0.0134
|
||||
"church" 1990 0.0432
|
||||
"vol_org" 1990 0.0349
|
||||
"customer" 1990 0.0524
|
||||
"bar_restaurant" 1990 0.1171
|
||||
"party" 1990 0.0597
|
||||
"public" 1990 0.0267
|
||||
"blind_date" 1990 0.0189
|
||||
"vacation" 1990 0.007
|
||||
"single_serve_nonint" 1990 0.0171
|
||||
"business_trip" 1990 0.0047
|
||||
"work_neighbors" 1990 0.0053
|
||||
"met_through_family" 2000 0.0808
|
||||
"met_through_friend" 2000 0.1918
|
||||
"met_through_as_nghbrs" 2000 0.0439
|
||||
"met_as_through_cowork" 2000 0.1022
|
||||
"met_online" 2000 0.0949
|
||||
"school" 2000 0.0746
|
||||
"college" 2000 0.055
|
||||
"mil" 2000 0.0028
|
||||
"church" 2000 0.0445
|
||||
"vol_org" 2000 0.0357
|
||||
"customer" 2000 0.033
|
||||
"bar_restaurant" 2000 0.1065
|
||||
"party" 2000 0.0739
|
||||
"public" 2000 0.0242
|
||||
"blind_date" 2000 0.0107
|
||||
"vacation" 2000 0.0092
|
||||
"single_serve_nonint" 2000 0.0052
|
||||
"business_trip" 2000 0.002
|
||||
"work_neighbors" 2000 0.0092
|
||||
"met_through_family" 2010 0.0638
|
||||
"met_through_friend" 2010 0.1722
|
||||
"met_through_as_nghbrs" 2010 0.0304
|
||||
"met_as_through_cowork" 2010 0.0853
|
||||
"met_online" 2010 0.189
|
||||
"school" 2010 0.0461
|
||||
"college" 2010 0.0398
|
||||
"mil" 2010 0.0051
|
||||
"church" 2010 0.0318
|
||||
"vol_org" 2010 0.0345
|
||||
"customer" 2010 0.0343
|
||||
"bar_restaurant" 2010 0.1528
|
||||
"party" 2010 0.0693
|
||||
"public" 2010 0.0236
|
||||
"blind_date" 2010 0.0068
|
||||
"vacation" 2010 0.0085
|
||||
"single_serve_nonint" 2010 0.0024
|
||||
"business_trip" 2010 0.0002
|
||||
"work_neighbors" 2010 0.0039
|
||||
|
@@ -0,0 +1,8 @@
|
||||
"1976" "1977" "1978" "1979" "1980" "1981" "1982" "1983" "1984" "1985" "1986" "1987" "1988" "1989" "1990" "1991" "1992" "1993" "1994" "1995" "1996" "1997" "1998" "1999" "2000" "2001" "2002" "2003" "2004" "2005" "2006" "2007" "2008" "2009" "2010" "2011" "2012" "2013" "2014" "2015" "2016" "2017" "2018" "2019" "2020" "2021" "waymet"
|
||||
0.0359171491054953 0.0399304190012852 0.0428525973962617 0.0474735256922412 0.0501995587151689 0.0520402621932969 0.0528187007039854 0.0551498353045369 0.0572437966280052 0.0586315936717927 0.0598521155387804 0.062224080653711 0.0631306965698012 0.0651619692730516 0.068110148768524 0.0693664548034937 0.0719078532368738 0.0723608210010821 0.0778308390078657 0.0764573886371595 0.0799532380844666 0.0837161827210115 0.0825555129486877 0.0844332209772884 0.0896421842307627 0.089011172432275 0.0872071033449697 0.087084876736775 0.0874503363035857 0.0881810599961824 0.0899257664205084 0.0888063800538201 0.0910911600605037 0.0913819783626526 0.100582419516824 0.0999028865393945 0.100915055882802 0.104841230811202 0.0991060915758774 0.102352983882629 0.102724489386347 0.101421934334673 0.106755566845541 0.103612014327867 0.101958995681941 0.108487098946671 "composite"
|
||||
0.0737172522934185 0.0727315168805551 0.0758147976700633 0.0725050284854784 0.0696998821253608 0.0711682499584102 0.0729168455795199 0.0747292387483697 0.0716615668446401 0.070910970842229 0.071909536214278 0.0728586786060707 0.0717726521571869 0.0708002037832075 0.0709242242065303 0.0727560901295643 0.0717638124880954 0.0717016297654046 0.0745430075238214 0.0746001173455608 0.0747371137602061 0.076569609540085 0.0744529816145868 0.0746909091583756 0.076240937711205 0.0774338345864903 0.0767508931215668 0.0790837429433754 0.0813482328770508 0.0831172036767798 0.0832350756039985 0.0819442329802185 0.0824417240946155 0.0864541032954844 0.0903518305756296 0.0879599886478688 0.0859222138489376 0.0876419359224646 0.0895131363676436 0.0889696528056223 0.0858702840305541 0.0900741548399015 0.0887896363174157 0.0898739575461556 0.0905178675441837 0.0895527121628647 "extended"
|
||||
0.00843526602633583 0.00850777847249008 0.00884128546216286 0.00871238039369094 0.00922124889540031 0.00987548349927263 0.00960289954449856 0.0106284058870679 0.0102764563447354 0.0112867726707859 0.011555395836625 0.0124407426126183 0.0118775315029513 0.0113591248195951 0.011721090640924 0.0113157698518771 0.0125250964427845 0.0121601944899692 0.011573801401964 0.0128370964906525 0.0134572734542054 0.0140098263037266 0.0140129438941686 0.0147048558020019 0.0137413309623923 0.0139710385316971 0.0149264246775303 0.0147760706802127 0.0146864548917721 0.0140035077964467 0.0146879125443847 0.0143576939406037 0.0150004931202757 0.0140200670210693 0.014634162344193 0.0152486217330109 0.015576342161966 0.0157204955695895 0.0156636873853376 0.015104538967275 0.0156673166776592 0.0161408720679691 0.0155853792976115 0.0147161572804681 0.014785071057374 0.0164810595385484 "nuclear_father"
|
||||
0.372174728684127 0.366009606933288 0.352582350888287 0.348515951295164 0.342222592291195 0.336966780988604 0.327345839367472 0.32787275641601 0.325873219510477 0.320055671882903 0.31862095882471 0.315356497567858 0.311822005730658 0.307263329800481 0.302119228956253 0.297220222869942 0.29400495589387 0.296479963951474 0.292422540950275 0.287746743042085 0.282043268008802 0.280014032685759 0.278712383274044 0.271665484967356 0.269134929713948 0.264903331259992 0.261454684974571 0.258867573340172 0.255771008698044 0.255803453387787 0.253384188789247 0.251752808876081 0.244648611819688 0.242872298724713 0.238044102240456 0.231186088947102 0.228122315367167 0.228230388255612 0.22754375490785 0.227586923830036 0.223800846489452 0.21996275736261 0.219177082028028 0.216968463145867 0.219862259379643 0.212006762346236 "nuclear_married_children"
|
||||
0.23105684786821 0.228954282036918 0.22329750766847 0.224119880842422 0.225846957601157 0.22135769441088 0.223916958826045 0.220601349815541 0.217861625896122 0.21882945420392 0.215480962401521 0.218608367665754 0.21875105108323 0.217709050818948 0.218907078467126 0.215957299648124 0.21568954060959 0.217827736525544 0.214057839784099 0.215663527922776 0.2170987060378 0.21039489234554 0.212875331750921 0.21663463206885 0.218541833656927 0.218737758466502 0.218729639405749 0.218260971113627 0.220897183013127 0.216408047669538 0.2148945881855 0.217177208841511 0.216167236296419 0.220568720227114 0.21550333715027 0.215709105695722 0.218408378513843 0.215049897977068 0.216214874841138 0.215256855654487 0.217187871763709 0.221515572233513 0.220762621340248 0.224747604004613 0.225911952055129 0.22212978782412 "nuclear_married_nochildren"
|
||||
0.0703327451860424 0.0714186357959817 0.0742946512462897 0.0735824943473564 0.0759507046717957 0.0770169587728375 0.0799098718683007 0.0789965491244178 0.0805888866834837 0.0807817520787598 0.0812876597110068 0.0802089343571296 0.0799268937514529 0.0813341026419157 0.0802360531198163 0.0815682384508434 0.0818201817192453 0.083095800845789 0.0856379149973299 0.0823594543606017 0.0824567385962726 0.083657903336338 0.0803903329188037 0.08142048088052 0.0772322724130535 0.0749738847046828 0.0772441657965296 0.0771011479253706 0.0753316307578279 0.0759517714215265 0.0770067534616388 0.0771879174525132 0.0750564120935269 0.0743081502178945 0.0742338033866819 0.0744683105389168 0.0767007783180191 0.0742133673463169 0.0744938046715825 0.0702624130905221 0.0722870317971879 0.0701991111399789 0.0684138713775119 0.0660586006770303 0.0645863511432945 0.0664352285851585 "nuclear_mother"
|
||||
0.20836601083637 0.212447760879482 0.222316809668466 0.225090738943647 0.226859055699923 0.231574570176698 0.233488884110178 0.232021864704056 0.236494448092536 0.23950378464961 0.241293371473079 0.238302698536858 0.242719169204719 0.246372218862801 0.247982175840827 0.251815924246156 0.252288559609541 0.246373853420737 0.243934056334644 0.250335672201165 0.250253662058248 0.251637553067539 0.257000513598788 0.256450416145608 0.255466511311711 0.26096898001836 0.263687088679084 0.264825617260468 0.264515153458592 0.26653495605174 0.266865714994722 0.268773757855253 0.275594362514971 0.270394682151072 0.266650344785945 0.275524997897985 0.274354915907265 0.274302684117747 0.277464650250571 0.280466631769429 0.282462159855092 0.280685598021354 0.280515842793643 0.284023203017999 0.282377503138435 0.284907350596401 "single"
|
||||
|
@@ -0,0 +1,47 @@
|
||||
"year" "p_composite" "p_extended" "p_nuclear_father" "p_nuclear_married_children" "p_nuclear_married_nochildren" "p_nuclear_mother" "p_single"
|
||||
1976 0.0359171491054953 0.0737172522934185 0.00843526602633583 0.372174728684127 0.23105684786821 0.0703327451860424 0.20836601083637
|
||||
1977 0.0399304190012852 0.0727315168805551 0.00850777847249008 0.366009606933288 0.228954282036918 0.0714186357959817 0.212447760879482
|
||||
1978 0.0428525973962617 0.0758147976700633 0.00884128546216286 0.352582350888287 0.22329750766847 0.0742946512462897 0.222316809668466
|
||||
1979 0.0474735256922412 0.0725050284854784 0.00871238039369094 0.348515951295164 0.224119880842422 0.0735824943473564 0.225090738943647
|
||||
1980 0.0501995587151689 0.0696998821253608 0.00922124889540031 0.342222592291195 0.225846957601157 0.0759507046717957 0.226859055699923
|
||||
1981 0.0520402621932969 0.0711682499584102 0.00987548349927263 0.336966780988604 0.22135769441088 0.0770169587728375 0.231574570176698
|
||||
1982 0.0528187007039854 0.0729168455795199 0.00960289954449856 0.327345839367472 0.223916958826045 0.0799098718683007 0.233488884110178
|
||||
1983 0.0551498353045369 0.0747292387483697 0.0106284058870679 0.32787275641601 0.220601349815541 0.0789965491244178 0.232021864704056
|
||||
1984 0.0572437966280052 0.0716615668446401 0.0102764563447354 0.325873219510477 0.217861625896122 0.0805888866834837 0.236494448092536
|
||||
1985 0.0586315936717927 0.070910970842229 0.0112867726707859 0.320055671882903 0.21882945420392 0.0807817520787598 0.23950378464961
|
||||
1986 0.0598521155387804 0.071909536214278 0.011555395836625 0.31862095882471 0.215480962401521 0.0812876597110068 0.241293371473079
|
||||
1987 0.062224080653711 0.0728586786060707 0.0124407426126183 0.315356497567858 0.218608367665754 0.0802089343571296 0.238302698536858
|
||||
1988 0.0631306965698012 0.0717726521571869 0.0118775315029513 0.311822005730658 0.21875105108323 0.0799268937514529 0.242719169204719
|
||||
1989 0.0651619692730516 0.0708002037832075 0.0113591248195951 0.307263329800481 0.217709050818948 0.0813341026419157 0.246372218862801
|
||||
1990 0.068110148768524 0.0709242242065303 0.011721090640924 0.302119228956253 0.218907078467126 0.0802360531198163 0.247982175840827
|
||||
1991 0.0693664548034937 0.0727560901295643 0.0113157698518771 0.297220222869942 0.215957299648124 0.0815682384508434 0.251815924246156
|
||||
1992 0.0719078532368738 0.0717638124880954 0.0125250964427845 0.29400495589387 0.21568954060959 0.0818201817192453 0.252288559609541
|
||||
1993 0.0723608210010821 0.0717016297654046 0.0121601944899692 0.296479963951474 0.217827736525544 0.083095800845789 0.246373853420737
|
||||
1994 0.0778308390078657 0.0745430075238214 0.011573801401964 0.292422540950275 0.214057839784099 0.0856379149973299 0.243934056334644
|
||||
1995 0.0764573886371595 0.0746001173455608 0.0128370964906525 0.287746743042085 0.215663527922776 0.0823594543606017 0.250335672201165
|
||||
1996 0.0799532380844666 0.0747371137602061 0.0134572734542054 0.282043268008802 0.2170987060378 0.0824567385962726 0.250253662058248
|
||||
1997 0.0837161827210115 0.076569609540085 0.0140098263037266 0.280014032685759 0.21039489234554 0.083657903336338 0.251637553067539
|
||||
1998 0.0825555129486877 0.0744529816145868 0.0140129438941686 0.278712383274044 0.212875331750921 0.0803903329188037 0.257000513598788
|
||||
1999 0.0844332209772884 0.0746909091583756 0.0147048558020019 0.271665484967356 0.21663463206885 0.08142048088052 0.256450416145608
|
||||
2000 0.0896421842307627 0.076240937711205 0.0137413309623923 0.269134929713948 0.218541833656927 0.0772322724130535 0.255466511311711
|
||||
2001 0.089011172432275 0.0774338345864903 0.0139710385316971 0.264903331259992 0.218737758466502 0.0749738847046828 0.26096898001836
|
||||
2002 0.0872071033449697 0.0767508931215668 0.0149264246775303 0.261454684974571 0.218729639405749 0.0772441657965296 0.263687088679084
|
||||
2003 0.087084876736775 0.0790837429433754 0.0147760706802127 0.258867573340172 0.218260971113627 0.0771011479253706 0.264825617260468
|
||||
2004 0.0874503363035857 0.0813482328770508 0.0146864548917721 0.255771008698044 0.220897183013127 0.0753316307578279 0.264515153458592
|
||||
2005 0.0881810599961824 0.0831172036767798 0.0140035077964467 0.255803453387787 0.216408047669538 0.0759517714215265 0.26653495605174
|
||||
2006 0.0899257664205084 0.0832350756039985 0.0146879125443847 0.253384188789247 0.2148945881855 0.0770067534616388 0.266865714994722
|
||||
2007 0.0888063800538201 0.0819442329802185 0.0143576939406037 0.251752808876081 0.217177208841511 0.0771879174525132 0.268773757855253
|
||||
2008 0.0910911600605037 0.0824417240946155 0.0150004931202757 0.244648611819688 0.216167236296419 0.0750564120935269 0.275594362514971
|
||||
2009 0.0913819783626526 0.0864541032954844 0.0140200670210693 0.242872298724713 0.220568720227114 0.0743081502178945 0.270394682151072
|
||||
2010 0.100582419516824 0.0903518305756296 0.014634162344193 0.238044102240456 0.21550333715027 0.0742338033866819 0.266650344785945
|
||||
2011 0.0999028865393945 0.0879599886478688 0.0152486217330109 0.231186088947102 0.215709105695722 0.0744683105389168 0.275524997897985
|
||||
2012 0.100915055882802 0.0859222138489376 0.015576342161966 0.228122315367167 0.218408378513843 0.0767007783180191 0.274354915907265
|
||||
2013 0.104841230811202 0.0876419359224646 0.0157204955695895 0.228230388255612 0.215049897977068 0.0742133673463169 0.274302684117747
|
||||
2014 0.0991060915758774 0.0895131363676436 0.0156636873853376 0.22754375490785 0.216214874841138 0.0744938046715825 0.277464650250571
|
||||
2015 0.102352983882629 0.0889696528056223 0.015104538967275 0.227586923830036 0.215256855654487 0.0702624130905221 0.280466631769429
|
||||
2016 0.102724489386347 0.0858702840305541 0.0156673166776592 0.223800846489452 0.217187871763709 0.0722870317971879 0.282462159855092
|
||||
2017 0.101421934334673 0.0900741548399015 0.0161408720679691 0.21996275736261 0.221515572233513 0.0701991111399789 0.280685598021354
|
||||
2018 0.106755566845541 0.0887896363174157 0.0155853792976115 0.219177082028028 0.220762621340248 0.0684138713775119 0.280515842793643
|
||||
2019 0.103612014327867 0.0898739575461556 0.0147161572804681 0.216968463145867 0.224747604004613 0.0660586006770303 0.284023203017999
|
||||
2020 0.101958995681941 0.0905178675441837 0.014785071057374 0.219862259379643 0.225911952055129 0.0645863511432945 0.282377503138435
|
||||
2021 0.108487098946671 0.0895527121628647 0.0164810595385484 0.212006762346236 0.22212978782412 0.0664352285851585 0.284907350596401
|
||||
|
@@ -0,0 +1,3 @@
|
||||
waymet,p
|
||||
"Met Online",18.9
|
||||
"Met Offline",81.1
|
||||
@@ -0,0 +1,7 @@
|
||||
"decade" "ponline" "poffline"
|
||||
1960 0.0042 0.9958
|
||||
1970 0.0032 0.9968
|
||||
1980 0.0002 0.9998
|
||||
1990 0.0153 0.9847
|
||||
2000 0.0949 0.9051
|
||||
2010 0.189 0.811
|
||||
|
@@ -0,0 +1,442 @@
|
||||
"code" "occname" "p" "n"
|
||||
440 "Other managers" 0.0304212311721698 31477
|
||||
4850 "Sales representatives, wholesale and manufacturing" 0.00693434360518215 7175
|
||||
9130 "Driver/sales workers and truck drivers" 0.00452206184371391 4679
|
||||
5730 "Medical secretaries and administrative assistants" 0.000636896506733803 659
|
||||
820 "Budget analysts" 0.000648494015202401 671
|
||||
3255 "Registered nurses" 0.0538501311968146 55719
|
||||
1430 "Industrial engineers, including health and safety" 0.00135497557274779 1402
|
||||
9610 "Cleaners of vehicles and equipment" 0.0000898806906316293 93
|
||||
7840 "Food batchmakers" 0.0000463900338743893 48
|
||||
6050 "Other agricultural workers" 0.00148931337917571 1541
|
||||
1555 "Other engineering technologists and technicians, except drafters" 0.000786697657786519 814
|
||||
4700 "First-line supervisors of retail sales workers" 0.00822263350423551 8508
|
||||
5740 "Secretaries and administrative assistants, except legal, medical, and executive" 0.0150004107450916 15521
|
||||
4220 "Janitors and building cleaners" 0.00223831913443928 2316
|
||||
1021 "Software developers" 0.0117163829304005 12123
|
||||
3322 "Diagnostic medical sonographers" 0.000773167231239822 800
|
||||
4200 "First-line supervisors of housekeeping and janitorial workers" 0.000298635843066381 309
|
||||
220 "Construction managers" 0.00248379973035793 2570
|
||||
5240 "Customer service representatives" 0.00471342073344576 4877
|
||||
420 "Social and community service managers" 0.00276310639264331 2859
|
||||
350 "Medical and health services managers" 0.0185521477135995 19196
|
||||
4950 "Door-to-door sales workers, news and street vendors, and related workers" 0.000358556303487467 371
|
||||
2002 "Educational, guidance, and career counselors and advisors" 0.00243451031936639 2519
|
||||
4720 "Cashiers" 0.00279983183612721 2897
|
||||
6260 "Construction laborers" 0.00186913178152227 1934
|
||||
1551 "Electrical and electronic engineering technologists and technicians" 0.00039238236985421 406
|
||||
7330 "Industrial and refractory machinery mechanics" 0.000700682803311089 725
|
||||
6355 "Electricians" 0.00250989412441227 2597
|
||||
1760 "Physical scientists, all other" 0.00508454100444088 5261
|
||||
1450 "Materials engineers" 0.000199090562044254 206
|
||||
5940 "Other office and administrative support workers" 0.00365708100376436 3784
|
||||
52 "Sales managers" 0.00156663010229969 1621
|
||||
7750 "Other assemblers and fabricators" 0.000876578348418148 907
|
||||
4810 "Insurance sales agents" 0.00182564112476503 1889
|
||||
7410 "Electrical power-line installers and repairers" 0.000336327745589323 348
|
||||
3310 "Dental hygienists" 0.00178408338608589 1846
|
||||
8990 "Miscellaneous production workers, including equipment operators and tenders" 0.00135884140890399 1406
|
||||
5860 "Office clerks, general" 0.00462933879704843 4790
|
||||
4760 "Retail salespersons" 0.0106610096597581 11031
|
||||
5120 "Bookkeeping, accounting, and auditing clerks" 0.00682030143857428 7057
|
||||
7200 "Automotive service technicians and mechanics" 0.0015163742322691 1569
|
||||
5250 "Eligibility interviewers, government programs" 0.000280273121324435 290
|
||||
2360 "Other teachers and instructors" 0.00702035845965758 7264
|
||||
6200 "First-line supervisors of construction trades and extraction workers" 0.00144292334530132 1493
|
||||
9122 "Bus drivers, transit and intercity" 0.000558613324570771 578
|
||||
9645 "Stockers and order fillers" 0.00155213321671394 1606
|
||||
8810 "Painting workers" 0.000125639675076471 130
|
||||
3930 "Security guards and gaming surveillance officers" 0.00133467993292774 1381
|
||||
1006 "Computer systems analysts" 0.00553587737567713 5728
|
||||
4510 "Hairdressers, hairstylists, and cosmetologists" 0.00144195688626227 1492
|
||||
7720 "Electrical, electronics, and electromechanical assemblers" 0.000489994732798237 507
|
||||
1050 "Computer support specialists" 0.00237748923606245 2460
|
||||
8030 "Machinists" 0.000374986107151314 388
|
||||
3500 "Licensed practical and licensed vocational nurses" 0.00338357309571327 3501
|
||||
3603 "Nursing assistants" 0.00342899667054861 3548
|
||||
4120 "Food servers, nonrestaurant" 0.0000386583615619911 40
|
||||
565 "Compliance officers" 0.00208851798338657 2161
|
||||
230 "Education and childcare administrators" 0.00681353622530093 7050
|
||||
6230 "Carpenters" 0.0015241059045815 1577
|
||||
2205 "Postsecondary teachers" 0.0300655742457995 31109
|
||||
9830 "Military, rank not specified" 0.000246447054957693 255
|
||||
10 "Chief executives and legislators" 0.0151502118961443 15676
|
||||
3300 "Clinical laboratory technologists and technicians" 0.00145838668992611 1509
|
||||
9640 "Packers and packagers, hand" 0.000237748923606245 246
|
||||
2310 "Elementary and middle school teachers" 0.0266066173450404 27530
|
||||
3720 "First-line supervisors of firefighting and prevention workers" 0.0002155203657081 223
|
||||
4500 "Barbers" 0.00043394010853335 449
|
||||
5840 "Insurance claims and policy processing clerks" 0.000316998564808327 328
|
||||
4020 "Cooks" 0.00146805128031661 1519
|
||||
7420 "Telecommunications line installers and repairers" 0.000167197413755612 173
|
||||
9030 "Aircraft pilots and flight engineers" 0.00229050792254797 2370
|
||||
2300 "Preschool and kindergarten teachers" 0.00372956543169309 3859
|
||||
3258 "Nurse practitioners, and nurse midwives" 0.00838016632760062 8671
|
||||
7240 "Small engine mechanics" 0.0000212620988590951 22
|
||||
700 "Logisticians" 0.000364355057721766 377
|
||||
5720 "Legal secretaries and administrative assistants" 0.000393348828893259 407
|
||||
8225 "Other metal workers and plastic workers" 0.000621433162109007 643
|
||||
3421 "Pharmacy technicians" 0.00160432200482263 1660
|
||||
9760 "Other material moving workers" 0.000361455680604617 374
|
||||
5000 "First-line supervisors of office and administrative support workers" 0.0129785784353995 13429
|
||||
735 "Market research analysts and marketing specialists" 0.0026094394054344 2700
|
||||
150 "Purchasing managers" 0.000893974611121044 925
|
||||
630 "Human resources workers" 0.0043239377407087 4474
|
||||
8740 "Inspectors, testers, sorters, samplers, and weighers" 0.00176958650050014 1831
|
||||
725 "Meeting, convention, and event planners" 0.000829221855504709 858
|
||||
4465 "Morticians, undertakers, and funeral arrangers" 0.000133371347388869 138
|
||||
300 "Architectural and engineering managers" 0.0021532707390029 2228
|
||||
9121 "Bus drivers, school" 0.000909437955745841 941
|
||||
4840 "Sales representatives of services, except advertising, insurance, financial services, and travel" 0.00231563585756327 2396
|
||||
3740 "Firefighters" 0.00105440681160331 1091
|
||||
4251 "Landscaping and groundskeeping workers" 0.000946163399229732 979
|
||||
800 "Accountants and auditors" 0.011901943065898 12315
|
||||
4010 "First-line supervisors of food preparation and serving workers" 0.000528653094360228 547
|
||||
5500 "Cargo and freight agents" 0.0000231950169371947 24
|
||||
4030 "Food preparation workers" 0.00056441207880507 584
|
||||
1530 "Other engineers" 0.00560352950841061 5798
|
||||
5820 "Word processors and typists" 0.00100318448253367 1038
|
||||
7810 "Butchers and other meat, poultry, and fish processing workers" 0.0000985788219830773 102
|
||||
9620 "Laborers and freight, stock, and material movers, hand" 0.00212234404975331 2196
|
||||
5400 "Receptionists and information clerks" 0.00420409681986653 4350
|
||||
9600 "Industrial truck and tractor operators" 0.000333428368472173 345
|
||||
5160 "Tellers" 0.000579875423429866 600
|
||||
7700 "First-line supervisors of production and operating workers" 0.00112109248529774 1160
|
||||
650 "Training and development specialists" 0.000256111645348191 265
|
||||
2320 "Secondary school teachers" 0.00680677101202758 7043
|
||||
7315 "Heating, air conditioning, and refrigeration mechanics and installers" 0.00113558937088349 1175
|
||||
7140 "Aircraft mechanics and service technicians" 0.000286071875558734 296
|
||||
3323 "Radiologic technologists and technicians" 0.00165747725197037 1715
|
||||
136 "Human resources managers" 0.00269062196471458 2784
|
||||
1108 "Computer occupations, all other" 0.00444281220251183 4597
|
||||
8140 "Welding, soldering, and brazing workers" 0.000358556303487467 371
|
||||
5850 "Mail clerks and mail machine operators, except postal service" 0.0000531552471477378 55
|
||||
137 "Training and development managers" 0.000286071875558734 296
|
||||
310 "Food service managers" 0.00282206039402535 2920
|
||||
7340 "Maintenance and repair workers, general" 0.000884310020730546 915
|
||||
2633 "Floral designers" 0.00025997748150439 269
|
||||
1920 "Chemical technicians" 0.000113075707568824 117
|
||||
3520 "Opticians, dispensing" 0.000154633446247964 160
|
||||
4920 "Real estate brokers and sales agents" 0.0112563484278128 11647
|
||||
160 "Transportation, storage, and distribution managers" 0.000641728801929052 664
|
||||
2435 "Librarians and media collections specialists" 0.00126316196403806 1307
|
||||
750 "Business operations specialists, all other" 0.00178408338608589 1846
|
||||
5110 "Billing and posting clerks" 0.00415674032695309 4301
|
||||
4600 "Childcare workers" 0.00286361813270449 2963
|
||||
4230 "Maids and housekeeping cleaners" 0.00153860279016725 1592
|
||||
2100 "Lawyers, and judges, magistrates, and other judicial workers" 0.0305294745845434 31589
|
||||
8760 "Dental and ophthalmic laboratory technicians and medical appliance technicians" 0.00008698131351448 90
|
||||
6442 "Plumbers, pipefitters, and steamfitters" 0.000697783426193939 722
|
||||
3870 "Police officers" 0.00263360088141064 2725
|
||||
2850 "Writers and authors" 0.00400017396262703 4139
|
||||
6950 "Other extraction workers" 0.0000908471496706791 94
|
||||
2910 "Photographers" 0.00167873935082946 1737
|
||||
7220 "Heavy vehicle and mobile equipment service technicians and mechanics" 0.000408812173518056 423
|
||||
2012 "Healthcare social workers" 0.000556680406492672 576
|
||||
120 "Financial managers" 0.008465214723037 8759
|
||||
4130 "Dining room and cafeteria attendants and bartender helpers" 0.000220352660903349 228
|
||||
3725 "Miscellaneous first-line supervisors, protective service workers" 0.000282206039402535 292
|
||||
1105 "Network and computer systems administrators" 0.000877544807457198 908
|
||||
205 "Farmers, ranchers, and other agricultural managers" 0.00310619935150598 3214
|
||||
3545 "Miscellaneous health technologists and technicians" 0.000892041693042945 923
|
||||
530 "Purchasing agents, except wholesale, retail, and farm products" 0.00153280403593295 1586
|
||||
600 "Cost estimators" 0.000443604698923848 459
|
||||
705 "Project management specialists" 0.00488834981951377 5058
|
||||
2040 "Clergy" 0.00314872354922417 3258
|
||||
710 "Management analysts" 0.0119947231336468 12411
|
||||
7150 "Automotive body and related repairers" 0.000561512701687921 581
|
||||
6520 "Sheet metal workers" 0.000317965023847377 329
|
||||
1360 "Civil engineers" 0.00357203260832798 3696
|
||||
2830 "Editors" 0.00112399186241489 1163
|
||||
910 "Credit counselors and loan officers" 0.000698749885232989 723
|
||||
7640 "Other installation, maintenance, and repair workers" 0.000568277914961269 588
|
||||
4240 "Pest control workers" 0.000110176330451675 114
|
||||
1220 "Operations research analysts" 0.00113268999376634 1172
|
||||
5340 "New accounts clerks" 0.00012950551123267 134
|
||||
5410 "Reservation and transportation ticket agents and travel clerks" 0.000182660758380408 189
|
||||
3910 "Private detectives and investigators" 0.000419443222947603 434
|
||||
2545 "Teaching assistants" 0.0049878951005359 5161
|
||||
4210 "First-line supervisors of landscaping, lawn service, and groundskeeping workers" 0.000140136560662218 145
|
||||
7000 "First-line supervisors of mechanics, installers, and repairers" 0.000455202207392445 471
|
||||
3010 "Dentists" 0.00816561242093157 8449
|
||||
3710 "First-line supervisors of police and detectives" 0.000114042166607874 118
|
||||
2330 "Special education teachers" 0.0017376933522115 1798
|
||||
4622 "Recreation workers" 0.000558613324570771 578
|
||||
4710 "First-line supervisors of non-retail sales workers" 0.0049762975920673 5149
|
||||
1720 "Chemists and materials scientists" 0.00123126881574942 1274
|
||||
3401 "Emergency medical technicians" 0.000584707718625115 605
|
||||
540 "Claims adjusters, appraisers, examiners, and investigators" 0.00177055295953919 1832
|
||||
1560 "Surveying and mapping technicians" 0.000114042166607874 118
|
||||
1610 "Biological scientists" 0.000515122667813531 533
|
||||
4965 "Sales and related workers, all other" 0.000968391957127877 1002
|
||||
5260 "File clerks" 0.000270608530933938 280
|
||||
3090 "Physicians" 0.214119966560517 221551
|
||||
9005 "Supervisors of transportation and material moving workers" 0.000513189749735432 531
|
||||
8555 "Other woodworkers" 0.000365321516760816 378
|
||||
4540 "Tour and travel guides" 0.000393348828893259 407
|
||||
3602 "Personal care aides" 0.00275054242513567 2846
|
||||
410 "Property, real estate, and community association managers" 0.00443411407116038 4588
|
||||
3230 "Speech-language pathologists" 0.00318931482886427 3300
|
||||
3050 "Pharmacists" 0.0102608956175915 10617
|
||||
5710 "Executive secretaries and executive administrative assistants" 0.00103411117178326 1070
|
||||
3100 "Surgeons" 0.00707158078872722 7317
|
||||
1320 "Aerospace engineers" 0.00201603355545784 2086
|
||||
5521 "Public safety telecommunicators" 0.0000570210833039369 59
|
||||
5810 "Data entry keyers" 0.000369187352917015 382
|
||||
5610 "Shipping, receiving, and inventory clerks" 0.000288004793636834 298
|
||||
1970 "Other life, physical, and social science technicians" 0.00118101294571883 1222
|
||||
20 "General and operations managers" 0.00522371110606405 5405
|
||||
2635 "Interior designers" 0.00121483901208557 1257
|
||||
4655 "Personal care and service workers, all other" 0.000345025876940771 357
|
||||
140 "Industrial production managers" 0.00102734595850991 1063
|
||||
1460 "Mechanical engineers" 0.00225378247906408 2332
|
||||
850 "Personal financial advisors" 0.00316032105769277 3270
|
||||
6330 "Drywall installers, ceiling tile installers, and tapers" 0.000309266892495929 320
|
||||
9150 "Motor vehicle operators, all other" 0.0000715179688896835 74
|
||||
5550 "Postal service mail carriers" 0.000539284143789776 558
|
||||
2722 "Coaches and scouts" 0.00229920605389942 2379
|
||||
3645 "Medical assistants" 0.00293416964255512 3036
|
||||
2840 "Technical writers" 0.0013143842931077 1360
|
||||
3550 "Other healthcare practitioners and technical occupations" 0.00118101294571883 1222
|
||||
340 "Lodging managers" 0.000556680406492672 576
|
||||
2003 "Marriage and family therapists" 0.000150767610091765 156
|
||||
1007 "Information security analysts" 0.00103990992601756 1076
|
||||
4621 "Exercise trainers and group fitness instructors" 0.00493570631242721 5107
|
||||
1022 "Software quality assurance analysts and testers" 0.000113075707568824 117
|
||||
3256 "Nurse anesthetists" 0.00116844897821118 1209
|
||||
5600 "Production, planning, and expediting clerks" 0.000660091523670998 683
|
||||
1750 "Geoscientists and hydrologists, except geographers" 0.000156566364326064 162
|
||||
51 "Marketing managers" 0.00309556830207644 3203
|
||||
6240 "Carpet, floor, and tile installers and finishers" 0.000137237183545068 142
|
||||
2600 "Artists and related workers" 0.00228664208639177 2366
|
||||
2014 "Social workers, all other" 0.00502945283921504 5204
|
||||
1106 "Computer network architects" 0.000126606134115521 131
|
||||
3640 "Dental assistants" 0.00120710733977317 1249
|
||||
1010 "Computer programmers" 0.00326276571583205 3376
|
||||
3000 "Chiropractors" 0.000548948734180274 568
|
||||
2640 "Other designers" 0.00313132728652128 3240
|
||||
2006 "Counselors, all other" 0.00167873935082946 1737
|
||||
2145 "Paralegals and legal assistants" 0.00188362866710802 1949
|
||||
2001 "Substance abuse and behavioral disorder counselors" 0.000338260663667422 350
|
||||
8630 "Miscellaneous plant and system operators" 0.000123706756998372 128
|
||||
7925 "Forming machine setters, operators, and tenders, metal and plastic" 0.0000396248206010409 41
|
||||
2170 "Title examiners, abstractors, and searchers" 0.000169130331833711 175
|
||||
4400 "Gambling services workers" 0.000265776235738689 275
|
||||
6305 "Construction equipment operators" 0.000399147583127558 413
|
||||
40 "Advertising and promotions managers" 0.000707448016584437 732
|
||||
2905 "Other media and communication equipment workers" 0.000474531388173441 491
|
||||
2350 "Tutors" 0.00151927360938625 1572
|
||||
3270 "Healthcare diagnosing or treating practitioners, all other" 0.0000338260663667422 35
|
||||
810 "Property appraisers and assessors" 0.00100705031868987 1042
|
||||
3630 "Massage therapists" 0.000592439390937514 613
|
||||
5100 "Bill and account collectors" 0.0000502558700305884 52
|
||||
4800 "Advertising sales agents" 0.000678454245412944 702
|
||||
2555 "Other educational instruction and library workers" 0.000830188314543759 859
|
||||
1310 "Surveyors, cartographers, and photogrammetrists" 0.000198124103005204 205
|
||||
8100 "Model makers, patternmakers, and molding machine setters, metal and plastic" 0.0000763502640849324 79
|
||||
1065 "Database administrators and architects" 0.00126606134115521 1310
|
||||
2810 "News analysts, reporters, and journalists" 0.00123803402902276 1281
|
||||
7210 "Bus and truck mechanics and diesel engine specialists" 0.000263843317660589 273
|
||||
110 "Computer and information systems managers" 0.00509807143098758 5275
|
||||
3620 "Physical therapist assistants and aides" 0.000144968855857467 150
|
||||
2060 "Religious workers, all other" 0.000764469099888374 791
|
||||
4150 "Hosts and hostesses, restaurant, lounge, and coffee shop" 0.00030540105633973 316
|
||||
4435 "Other entertainment attendants and related workers" 0.000224218497059548 232
|
||||
9810 "First-line enlisted military supervisors" 0.000448436994119097 464
|
||||
5330 "Loan interviewers and clerks" 0.0000618533784991858 64
|
||||
520 "Wholesale and retail buyers, except farm products" 0.000804093920489415 832
|
||||
6410 "Painters and paperhangers" 0.000922001923253488 954
|
||||
2400 "Archivists, curators, and museum technicians" 0.000501592241266835 519
|
||||
1410 "Electrical and electronics engineers" 0.00232046815275852 2401
|
||||
3402 "Paramedics" 0.000850483954363804 880
|
||||
8600 "Power plant operators, distributors, and dispatchers" 0.000451336371236246 467
|
||||
4340 "Animal trainers" 0.00012950551123267 134
|
||||
8130 "Tool and die makers" 0.000179761381263259 186
|
||||
4350 "Animal caretakers" 0.000408812173518056 423
|
||||
5630 "Weighers, measurers, checkers, and samplers, recordkeeping" 0.000318931482886427 330
|
||||
3321 "Cardiovascular technologists and technicians" 0.000154633446247964 160
|
||||
4110 "Waiters and waitresses" 0.00160142262770548 1657
|
||||
9720 "Refuse and recyclable material collectors" 0.0000589540013820364 61
|
||||
8610 "Stationary engineers and boiler operators" 0.000363388598682716 376
|
||||
3245 "Other therapists" 0.00258044563426291 2670
|
||||
4040 "Bartenders" 0.000335361286550273 347
|
||||
1650 "Other life scientists" 0.00708607767431297 7332
|
||||
2025 "Other community and social service specialists" 0.000991586974065072 1026
|
||||
8320 "Sewing machine operators" 0.000480330142407739 497
|
||||
102 "Facilities managers" 0.000553781029375522 573
|
||||
2105 "Judicial law clerks" 0.00056344561976602 583
|
||||
4521 "Manicurists and pedicurists" 0.000534451848594527 553
|
||||
3250 "Veterinarians" 0.00243451031936639 2519
|
||||
1400 "Computer hardware engineers" 0.00122933589767132 1272
|
||||
1825 "Other psychologists" 0.00656998854746039 6798
|
||||
6120 "Forest and conservation workers" 0.000078283182163032 81
|
||||
1031 "Web developers" 0.000455202207392445 471
|
||||
7510 "Coin, vending, and amusement machine servicers and repairers" 0.0000657192146553849 68
|
||||
5510 "Couriers and messengers" 0.000295736465949232 306
|
||||
7560 "Riggers" 0.0000183627217419458 19
|
||||
3150 "Occupational therapists" 0.00276503931072141 2861
|
||||
7950 "Cutting, punching, and press machine setters, operators, and tenders, metal and plastic" 0.000133371347388869 138
|
||||
3649 "Phlebotomists" 0.000134337806427919 139
|
||||
3515 "Medical records specialists" 0.00095679444865928 990
|
||||
3647 "Pharmacy aides" 0.000182660758380408 189
|
||||
6005 "First-line supervisors of farming, fishing, and forestry workers" 0.0000376919025229413 39
|
||||
8620 "Water and wastewater treatment plant and system operators" 0.0000753838050458826 78
|
||||
2015 "Probation officers and correctional treatment specialists" 0.000149801151052715 155
|
||||
2180 "Legal support workers, all other" 0.000836953527817107 866
|
||||
7020 "Radio and telecommunications equipment installers and repairers" 0.0000773167231239822 80
|
||||
7905 "Computer numerically controlled tool operators and programmers" 0.0000947129858268782 98
|
||||
640 "Compensation, benefits, and job analysis specialists" 0.000515122667813531 533
|
||||
1240 "Other mathematical science occupations" 0.00122933589767132 1272
|
||||
3802 "Correctional officers and jailers" 0.0000531552471477378 55
|
||||
7040 "Electric motor, power tool, and related repairers" 0.000122740297959322 127
|
||||
9141 "Shuttle drivers and chauffeurs" 0.000504491618383984 522
|
||||
5140 "Payroll and timekeeping clerks" 0.000292837088832083 303
|
||||
3655 "Other healthcare support workers" 0.00129408865328765 1339
|
||||
3648 "Veterinary assistants and laboratory animal caretakers" 0.00008698131351448 90
|
||||
8800 "Packaging and filling machine operators and tenders" 0.000223252038020499 231
|
||||
2004 "Mental health counselors" 0.00220449306807254 2281
|
||||
3424 "Veterinary technologists and technicians" 0.000384650697541811 398
|
||||
930 "Tax examiners and collectors, and revenue agents" 0.0000463900338743893 48
|
||||
7800 "Bakers" 0.00117231481436738 1213
|
||||
2752 "Musicians and singers" 0.0015028438057224 1555
|
||||
1821 "Clinical and counseling psychologists" 0.00082632247838756 855
|
||||
9142 "Taxi drivers" 0.000979023006557425 1013
|
||||
3160 "Physical therapists" 0.00581711695604061 6019
|
||||
5165 "Other financial clerks" 0.0013066526207953 1352
|
||||
3220 "Respiratory therapists" 0.000436839485650499 452
|
||||
1600 "Agricultural and food scientists" 0.000427174895260002 442
|
||||
4000 "Chefs and head cooks" 0.00104280930313471 1079
|
||||
4820 "Securities, commodities, and financial services sales agents" 0.00131535075214675 1361
|
||||
6515 "Roofers" 0.000254178727270091 263
|
||||
425 "Emergency management directors" 0.0000637862965772853 66
|
||||
101 "Administrative services managers" 0.000306367515378779 317
|
||||
1440 "Marine engineers and naval architects" 0.000105344035256426 109
|
||||
4055 "Fast food and counter workers" 0.000125639675076471 130
|
||||
8465 "Other textile, apparel, and furnishings workers" 0.000052188788108688 54
|
||||
3423 "Surgical technologists" 0.000139170101623168 144
|
||||
2751 "Music directors and composers" 0.00039141591081516 405
|
||||
8300 "Laundry and dry-cleaning workers" 0.000148834692013666 154
|
||||
2050 "Directors, religious activities and education" 0.00095582798962023 989
|
||||
2016 "Social and human service assistants" 0.000528653094360228 547
|
||||
2825 "Public relations specialists" 0.00111239435394629 1151
|
||||
7260 "Miscellaneous vehicle and mobile equipment mechanics, installers, and repairers" 0.0000309266892495929 32
|
||||
3801 "Bailiffs" 0.0000570210833039369 59
|
||||
6115 "Fishing and hunting workers" 0.0000202956398200453 21
|
||||
4740 "Counter and rental clerks" 0.000373053189073214 386
|
||||
960 "Other financial specialists" 0.000776066608356971 803
|
||||
1900 "Agricultural and food science technicians" 0.000122740297959322 127
|
||||
3330 "Nuclear medicine technologists and medical dosimetrists" 0.0000405912796400907 42
|
||||
6660 "Construction and building inspectors" 0.000316032105769277 327
|
||||
726 "Fundraisers" 0.000883343561691497 914
|
||||
3820 "Detectives and criminal investigators" 0.00133661285100584 1383
|
||||
3200 "Radiation therapists" 0.000180727840302308 187
|
||||
2710 "Producers and directors" 0.000889142315925795 920
|
||||
9430 "Other transportation workers" 0.0000763502640849324 79
|
||||
5420 "Other information and records clerks" 0.000582774800547016 603
|
||||
3960 "Other protective service workers" 0.000513189749735432 531
|
||||
3610 "Occupational therapy assistants and aides" 0.0000724844279287333 75
|
||||
8650 "Crushing, grinding, polishing, mixing, and blending workers" 0.000147868232974616 153
|
||||
5350 "Correspondence clerks and order clerks" 0.000176862004146109 183
|
||||
6530 "Structural iron and steel workers" 0.0000357589844448418 37
|
||||
860 "Insurance underwriters" 0.0000966459039049777 100
|
||||
845 "Financial and investment analysts" 0.00294576715102372 3048
|
||||
2011 "Child, family, and school social workers" 0.000616600866913758 638
|
||||
7010 "Computer, automated teller, and office machine repairers" 0.000321830860003576 333
|
||||
3030 "Dietitians and nutritionists" 0.00312262915516983 3231
|
||||
7430 "Precision instrument and equipment repairers" 0.000228084333215747 236
|
||||
2805 "Broadcast announcers and radio disc jockeys" 0.0000289937711714933 30
|
||||
1200 "Actuaries" 0.000637862965772853 660
|
||||
8640 "Chemical processing machine setters, operators, and tenders" 0.000069585050811584 72
|
||||
830 "Credit analysts" 0.000171063249911811 177
|
||||
8500 "Cabinetmakers and bench carpenters" 0.0000628198375382355 65
|
||||
2865 "Media and communication workers, all other" 0.000134337806427919 139
|
||||
1305 "Architects, except landscape and naval" 0.00185656781401462 1921
|
||||
500 "Agents and business managers of artists, performers, and athletes" 0.00056537853784412 585
|
||||
1545 "Other drafters" 0.000358556303487467 371
|
||||
8350 "Tailors, dressmakers, and sewers" 0.000441671780845748 457
|
||||
3601 "Home health aides" 0.000453269289314346 469
|
||||
1860 "Other social scientists" 0.000628198375382355 650
|
||||
6825 "Surface mining machine operators and earth drillers" 0.000142069478740317 147
|
||||
9630 "Machine feeders and offbearers" 0.000155599905287014 161
|
||||
9410 "Transportation inspectors" 0.00026191039958249 271
|
||||
2634 "Graphic designers" 0.00153860279016725 1592
|
||||
4252 "Tree trimmers and pruners" 0.0000647527556163351 67
|
||||
7540 "Locksmiths and safe repairers" 0.00004349065675724 45
|
||||
4830 "Travel agents" 0.000404946337361857 419
|
||||
1700 "Astronomers and physicists" 0.000123706756998372 128
|
||||
3324 "Magnetic resonance imaging technologists" 0.000445537617001947 461
|
||||
4525 "Other personal appearance workers" 0.0000773167231239822 80
|
||||
7100 "Other electrical and electronic equipment mechanics, installers, and repairers" 0.000124673216037421 129
|
||||
6250 "Cement masons, concrete finishers, and terrazzo workers" 0.0000512223290696382 53
|
||||
3940 "Crossing guards and flaggers" 0.000420409681986653 435
|
||||
1420 "Environmental engineers" 0.000158499282404164 164
|
||||
8255 "Printing press operators" 0.000297669384027331 308
|
||||
9825 "Military enlisted tactical operations and air/weapons specialists and crew members" 0.000159465741443213 165
|
||||
7855 "Food processing workers, all other" 0.000190392430692806 197
|
||||
9050 "Flight attendants" 0.000460034502587694 476
|
||||
3140 "Audiologists" 0.000342126499823621 354
|
||||
6130 "Logging workers" 0.0000318931482886427 33
|
||||
5310 "Interviewers, except eligibility and loan" 0.000466799715861043 483
|
||||
9240 "Railroad conductors and yardmasters" 0.000183627217419458 190
|
||||
1910 "Biological technicians" 0.0000976123629440275 101
|
||||
940 "Tax preparers" 0.000977090088479325 1011
|
||||
9650 "Pumping station operators" 0.0000135304265466969 14
|
||||
5530 "Meter readers, utilities" 0.000052188788108688 54
|
||||
3261 "Acupuncturists" 0.000309266892495929 320
|
||||
8250 "Prepress technicians and workers" 0.000244514136879594 253
|
||||
2013 "Mental health and substance abuse social workers" 0.00034599233597982 358
|
||||
3646 "Medical transcriptionists" 0.000237748923606245 246
|
||||
9800 "Military officer special and tactical operations leaders" 0.000290904170753983 301
|
||||
3110 "Physician assistants" 0.00601814043616296 6227
|
||||
510 "Buyers and purchasing agents, farm products" 0.000144968855857467 150
|
||||
4420 "Ushers, lobby attendants, and ticket takers" 0.0000541217061867875 56
|
||||
6220 "Brickmasons, blockmasons, stonemasons, and reinforcing iron and rebar workers" 0.000263843317660589 273
|
||||
3945 "Transportation security screeners" 0.000158499282404164 164
|
||||
5320 "Library assistants, clerical" 0.000482263060485839 499
|
||||
4330 "Supervisors of personal care and service workers" 0.00017396262702896 180
|
||||
4522 "Skincare specialists" 0.000312166269613078 323
|
||||
5300 "Hotel, motel, and resort desk clerks" 0.000245480595918643 254
|
||||
5020 "Telephone operators" 0.000127572593154571 132
|
||||
4140 "Dishwashers" 0.000233883087450046 242
|
||||
3040 "Optometrists" 0.00103797700793946 1074
|
||||
1640 "Conservation scientists and foresters" 0.000345025876940771 357
|
||||
1822 "School psychologists" 0.000730643033521632 756
|
||||
1350 "Chemical engineers" 0.000471632011056291 488
|
||||
1032 "Web and digital interface designers" 0.000506424536462083 524
|
||||
4900 "Models, demonstrators, and product promoters" 0.000288971252675883 299
|
||||
60 "Public relations and fundraising managers" 0.000465833256821993 482
|
||||
3422 "Psychiatric technicians" 0.000247413513996743 256
|
||||
8830 "Photographic process workers and processing machine operators" 0.0000724844279287333 75
|
||||
6460 "Plasterers and stucco masons" 0.0000280273121324435 29
|
||||
2721 "Athletes and sports competitors" 0.0000318931482886427 33
|
||||
2861 "Interpreters and translators" 0.000722911361209234 748
|
||||
4940 "Telemarketers" 0.000276407285168236 286
|
||||
8750 "Jewelers and precious stone and metal workers" 0.0000193291807809955 20
|
||||
3210 "Recreational therapists" 0.000158499282404164 164
|
||||
5920 "Statistical assistants" 0.000278340203246336 288
|
||||
6400 "Insulation workers" 0.000163331577599412 169
|
||||
2631 "Commercial and industrial designers" 0.000078283182163032 81
|
||||
5230 "Credit authorizers, checkers, and clerks" 0.0000115975084685973 12
|
||||
2440 "Library technicians" 0.000101478199100227 105
|
||||
5040 "Communications equipment operators, all other" 0.0000773167231239822 80
|
||||
1520 "Petroleum, mining and geological engineers, including mining safety engineers" 0.000331495450394074 343
|
||||
4930 "Sales engineers" 0.0000241614759762444 25
|
||||
2755 "Disc jockeys, except radio" 0.0000231950169371947 24
|
||||
5360 "Human resources assistants, except payroll and timekeeping" 0.000235816005528146 244
|
||||
360 "Natural sciences managers" 0.000119840920842172 124
|
||||
1005 "Computer and information research scientists" 0.000461000961626744 477
|
||||
3946 "School bus monitors" 0.0000541217061867875 56
|
||||
2920 "Television, video, and film camera operators and editors" 0.0000831154773582809 86
|
||||
3120 "Podiatrists" 0.000445537617001947 461
|
||||
2632 "Fashion designers" 0.000588573554781315 609
|
||||
1306 "Landscape architects" 0.00026191039958249 271
|
||||
1840 "Urban and regional planners" 0.000387550074658961 401
|
||||
1340 "Biomedical and agricultural engineers" 0.000224218497059548 232
|
||||
2770 "Entertainers and performers, sports and related workers, all other" 0.0000657192146553849 68
|
||||
900 "Financial examiners" 0.00025901102246534 268
|
||||
1800 "Economists" 0.000192325348770906 199
|
||||
4530 "Baggage porters, bellhops, and concierges" 0.000183627217419458 190
|
||||
2700 "Actors" 0.000467766174900092 484
|
||||
8450 "Upholsterers" 0.000155599905287014 161
|
||||
2723 "Umpires, referees, and other sports officials" 0.0000802161002411315 83
|
||||
8850 "Adhesive bonding machine operators and tenders" 0.00026191039958249 271
|
||||
|
@@ -0,0 +1,23 @@
|
||||
import matplotlib.pyplot as plt
|
||||
import seaborn as sns
|
||||
import pandas as pd
|
||||
|
||||
# Load data
|
||||
marjobs = pd.read_csv("data/physician-marry.tsv", delimiter="\t")
|
||||
|
||||
# Sort by most common
|
||||
marsorted = marjobs.sort_values(by=['p'], ascending=False)
|
||||
|
||||
# Set figure size and margin
|
||||
sns.set(rc={'figure.figsize':(8,8), 'pdf.fonttype': 42 })
|
||||
subs, axes = plt.subplots(1, 1)
|
||||
plt.subplots_adjust(left=.5)
|
||||
|
||||
p1 = sns.barplot(data=marsorted[0:30],
|
||||
x="p", y="occname", orient="h")
|
||||
fig = p1.get_figure()
|
||||
|
||||
# Save as PDF
|
||||
fig.savefig("bar-mar.pdf")
|
||||
|
||||
|
||||
@@ -0,0 +1,27 @@
|
||||
#
|
||||
# Pie charts
|
||||
#
|
||||
|
||||
# Load data
|
||||
htypes <- read.csv("data/household-types.tsv", sep="\t")
|
||||
h2021 <- htypes[htypes$year == 2021,]
|
||||
h2021_alpha <- h2021[order(h2021$htype, decreasing=TRUE),]
|
||||
h2021_num <- h2021[order(h2021$p),]
|
||||
|
||||
|
||||
#
|
||||
# Pie chart, sorted and unsorted
|
||||
#
|
||||
|
||||
par(mfrow=c(1,2))
|
||||
pie(h2021_alpha$p, labels=h2021_alpha$htype, init.angle=90, col = "gray")
|
||||
pie(h2021_num$p, labels=h2021_num$htype, init.angle=90, col = "gray")
|
||||
|
||||
|
||||
#
|
||||
# Bar chart, sorted and unsorted
|
||||
#
|
||||
|
||||
par(mfrow=c(1,2))
|
||||
barplot(h2021_alpha$p, names.arg=h2021_alpha$htype, horiz=TRUE)
|
||||
barplot(h2021_num$p, names.arg=h2021_num$htype, horiz=TRUE)
|
||||
@@ -0,0 +1,39 @@
|
||||
import matplotlib.pyplot as plt
|
||||
import pandas as pd
|
||||
# import seaborn as sns
|
||||
# import math
|
||||
|
||||
# Load data
|
||||
marjobs = pd.read_csv("data/physician-marry.tsv", delimiter="\t")
|
||||
marsorted = marjobs.sort_values(by=['p'],
|
||||
ascending=False)[0:10] # Top 10.
|
||||
|
||||
# Prepare data for circles using bubble plot
|
||||
mardf = pd.DataFrame({
|
||||
"x": [1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
|
||||
"y": [10, 9, 8, 7, 6, 5, 4, 3, 2, 1],
|
||||
"r": list(marsorted.p * 50000)
|
||||
})
|
||||
|
||||
# sns.set(rc={'pdf.fonttype': 42 })
|
||||
|
||||
# p1 = sns.relplot(x="x", y="y", size="r", sizes=(40,2000), data=mardf)
|
||||
# fig = p1.get_figure()
|
||||
# p1.savefig("symbols-chart-mar.pdf")
|
||||
|
||||
|
||||
# Figure size
|
||||
plt.rcParams['figure.figsize'] = (7, 10)
|
||||
plt.rcParams['pdf.fonttype'] = 42
|
||||
|
||||
# Plot
|
||||
plt.scatter("x", "y", s="r", data=mardf)
|
||||
|
||||
# Text
|
||||
for i in range(0, len(marsorted)):
|
||||
thelabel = str(round(100*marsorted.iloc[i].p)) + "%, "
|
||||
thelabel += marsorted.iloc[i].occname
|
||||
plt.text(1, 10-i, thelabel)
|
||||
|
||||
# Save as PDF
|
||||
plt.savefig("symbols-chart-mar.pdf")
|
||||
@@ -0,0 +1,43 @@
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
# import seaborn as sns
|
||||
|
||||
# Load data
|
||||
marjobs = pd.read_csv("data/physician-marry.tsv", delimiter="\t")
|
||||
marsorted = marjobs.sort_values(by=['p'], ascending=False)[0:49]
|
||||
|
||||
# Grid coordinates for a 7x7 grid
|
||||
x = []
|
||||
for i in range(0, 7):
|
||||
x = x + list(range(0, 7))
|
||||
y = list(reversed(np.repeat(np.arange(0,7), 7)))
|
||||
|
||||
# Prepare data for circles using bubble plot
|
||||
mardf = pd.DataFrame({
|
||||
"x" : x,
|
||||
"y" : y,
|
||||
"r" : list(marsorted.p * 50000),
|
||||
"occname" : list(marsorted.occname),
|
||||
"p" : list(marsorted.p * 100)
|
||||
})
|
||||
|
||||
|
||||
# Figure size
|
||||
plt.rcParams['figure.figsize'] = (13, 13)
|
||||
plt.rcParams['pdf.fonttype'] = 42
|
||||
|
||||
# Plot
|
||||
plt.scatter("x", "y", s="r", data=mardf)
|
||||
|
||||
# Text
|
||||
plt.rcParams['font.size'] = 8
|
||||
plt.rcParams['pdf.fonttype'] = 42
|
||||
for i in range(0, len(mardf)):
|
||||
thelabel = str(round(mardf.p[i], 2)) + "%\n "
|
||||
thelabel += mardf.occname[i]
|
||||
plt.text(mardf.x[i], mardf.y[i], thelabel,
|
||||
horizontalalignment="center")
|
||||
|
||||
# Save as PDF
|
||||
plt.savefig("symbols-grid-mar.pdf")
|
||||
@@ -0,0 +1,24 @@
|
||||
# Install package if have not yet
|
||||
# install.packages("treemap")
|
||||
|
||||
# Load package.
|
||||
library(treemap)
|
||||
|
||||
#
|
||||
# Load data.
|
||||
#
|
||||
howmet2010 <- read.csv("data/how-met-2010s.tsv", sep="\t")
|
||||
|
||||
|
||||
#
|
||||
# Draw treemap.
|
||||
#
|
||||
|
||||
treemap(howmet2010,
|
||||
index = c("category", "waymet"),
|
||||
vSize = "p",
|
||||
algorithm = "squarified",
|
||||
title = "How People Met, 2010s")
|
||||
|
||||
|
||||
|
||||
@@ -0,0 +1,48 @@
|
||||
#
|
||||
# Load data.
|
||||
#
|
||||
|
||||
htypes <- read.csv("data/household-types.tsv", sep="\t")
|
||||
head(htypes)
|
||||
|
||||
|
||||
#
|
||||
# Reformat data.
|
||||
#
|
||||
|
||||
years <- unique(htypes$year)
|
||||
uhtypes <- unique(htypes$htype)
|
||||
|
||||
# Start data frame
|
||||
htypes_new <- data.frame(year = years)
|
||||
|
||||
# Add columns
|
||||
for (uht in uhtypes) {
|
||||
curr <- htypes[htypes$htype == uht,]
|
||||
curr_name <- paste0("p_", gsub("-", "_", uht))
|
||||
htypes_new[, curr_name] <- curr$p[match(htypes_new$year, curr$year)]
|
||||
}
|
||||
|
||||
# Save formatted data
|
||||
write.table(htypes_new,
|
||||
file="data/htypes_rectangular.tsv",
|
||||
sep="\t",
|
||||
row.names=FALSE)
|
||||
|
||||
|
||||
# Transpose?
|
||||
htypes_long <- as.data.frame(t(htypes_new[,-1]))
|
||||
colnames(htypes_long) <- htypes_new$year
|
||||
htypes_long$waymet <- gsub("p_", "", row.names(htypes_long))
|
||||
write.table(htypes_long, file="data/htypes_long.tsv", sep="\t", row.names=FALSE)
|
||||
|
||||
|
||||
|
||||
#
|
||||
# Alluvial diagram
|
||||
#
|
||||
|
||||
# install.packages("alluvial")
|
||||
library(alluvial)
|
||||
alluvial_ts(htypes[,c("htype", "year", "p")],
|
||||
wave = .3, lwd = .5, ygap=1)
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
@@ -0,0 +1,51 @@
|
||||
Rk,Player,Pos,Age,Tm,G,GS,MP,FG,FGA,FGpct,3P,3PA,3Ppct,2P,2PA,2Ppct,eFGpct,FT,FTA,FTpct,ORB,DRB,TRB,AST,STL,BLK,TOV,PF,PTS,Player-additional
|
||||
1,Joel Embiid,C,28,PHI,66,66,34.6,11.0,20.1,.548,1.0,3.0,.330,10.0,17.1,.587,.573,10.0,11.7,.857,1.7,8.4,10.2,4.2,1.0,1.7,3.4,3.1,33.1,embiijo01
|
||||
2,Luka Dončić,PG,23,DAL,66,66,36.2,10.9,22.0,.496,2.8,8.2,.342,8.1,13.8,.588,.560,7.8,10.5,.742,0.8,7.8,8.6,8.0,1.4,0.5,3.6,2.5,32.4,doncilu01
|
||||
3,Damian Lillard,PG,32,POR,58,58,36.3,9.6,20.7,.463,4.2,11.3,.371,5.4,9.4,.574,.564,8.8,9.6,.914,0.8,4.0,4.8,7.3,0.9,0.3,3.3,1.9,32.2,lillada01
|
||||
4,Shai Gilgeous-Alexander,PG,24,OKC,68,68,35.5,10.4,20.3,.510,0.9,2.5,.345,9.5,17.8,.533,.531,9.8,10.9,.905,0.9,4.0,4.8,5.5,1.6,1.0,2.8,2.8,31.4,gilgesh01
|
||||
5,Giannis Antetokounmpo,PF,28,MIL,63,63,32.1,11.2,20.3,.553,0.7,2.7,.275,10.5,17.6,.596,.572,7.9,12.3,.645,2.2,9.6,11.8,5.7,0.8,0.8,3.9,3.1,31.1,antetgi01
|
||||
6,Jayson Tatum,SF,24,BOS,74,74,36.9,9.8,21.1,.466,3.2,9.3,.350,6.6,11.8,.558,.543,7.2,8.4,.854,1.1,7.7,8.8,4.6,1.1,0.7,2.9,2.2,30.1,tatumja01
|
||||
7,Stephen Curry,PG,34,GSW,56,56,34.7,10.0,20.2,.493,4.9,11.4,.427,5.1,8.8,.579,.614,4.6,5.0,.915,0.7,5.4,6.1,6.3,0.9,0.4,3.2,2.1,29.4,curryst01
|
||||
8,Kevin Durant,PF,34,TOT,47,47,35.6,10.3,18.3,.560,2.0,4.9,.404,8.3,13.4,.617,.614,6.5,7.1,.919,0.4,6.3,6.7,5.0,0.7,1.4,3.3,2.1,29.1,duranke01
|
||||
9,LeBron James,PF,38,LAL,55,54,35.5,11.1,22.2,.500,2.2,6.9,.321,8.9,15.3,.580,.549,4.6,5.9,.768,1.2,7.1,8.3,6.8,0.9,0.6,3.2,1.6,28.9,jamesle01
|
||||
10,Donovan Mitchell,SG,26,CLE,68,68,35.8,10.0,20.6,.484,3.6,9.3,.386,6.4,11.3,.566,.572,4.7,5.4,.867,0.9,3.3,4.3,4.4,1.5,0.4,2.6,2.5,28.3,mitchdo01
|
||||
11,Devin Booker,SG,26,PHO,53,53,34.6,9.9,20.1,.494,2.1,6.0,.351,7.8,14.2,.554,.546,5.8,6.8,.855,0.9,3.7,4.5,5.5,1.0,0.3,2.7,3.0,27.8,bookede01
|
||||
12,Kyrie Irving,PG-SG,30,TOT,60,60,37.4,9.9,20.1,.494,3.1,8.3,.379,6.8,11.8,.574,.572,4.1,4.6,.905,1.0,4.1,5.1,5.5,1.1,0.8,2.1,2.8,27.1,irvinky01
|
||||
13,Jaylen Brown,SF,26,BOS,67,67,35.9,10.1,20.6,.491,2.4,7.3,.335,7.7,13.4,.576,.550,3.9,5.1,.765,1.2,5.7,6.9,3.5,1.1,0.4,2.9,2.6,26.6,brownja02
|
||||
14,Ja Morant,PG,23,MEM,61,59,31.9,9.3,19.9,.466,1.5,4.9,.307,7.8,15.0,.519,.504,6.1,8.1,.748,1.0,4.9,5.9,8.1,1.1,0.3,3.4,1.6,26.2,moranja01
|
||||
15,Trae Young,PG,24,ATL,73,73,34.8,8.2,19.0,.429,2.1,6.3,.335,6.1,12.7,.476,.485,7.8,8.8,.886,0.8,2.2,3.0,10.2,1.1,0.1,4.1,1.4,26.2,youngtr01
|
||||
16,Zion Williamson,PF,22,NOP,29,29,33.0,9.8,16.2,.608,0.2,0.7,.368,9.6,15.5,.618,.615,6.1,8.6,.714,2.0,5.0,7.0,4.6,1.1,0.6,3.4,2.2,26.0,willizi01
|
||||
17,Anthony Davis,C,29,LAL,56,54,34.0,9.7,17.2,.563,0.3,1.3,.257,9.3,15.9,.589,.573,6.2,7.9,.784,3.5,9.1,12.5,2.6,1.1,2.0,2.2,2.6,25.9,davisan02
|
||||
18,Lauri Markkanen,PF,25,UTA,66,66,34.4,8.7,17.3,.499,3.0,7.7,.391,5.6,9.6,.585,.586,5.3,6.0,.875,2.0,6.7,8.6,1.9,0.6,0.6,1.9,2.1,25.6,markkla01
|
||||
19,Julius Randle,PF,28,NYK,77,77,35.5,8.5,18.6,.459,2.8,8.3,.343,5.7,10.3,.553,.536,5.2,6.9,.757,1.8,8.1,10.0,4.1,0.6,0.3,2.8,3.0,25.1,randlju01
|
||||
20,De'Aaron Fox,PG,25,SAC,73,73,33.4,9.3,18.2,.512,1.6,5.0,.324,7.7,13.2,.584,.557,4.7,6.0,.780,0.5,3.6,4.2,6.1,1.1,0.3,2.5,2.4,25.0,foxde01
|
||||
21,Zach LaVine,SG,27,CHI,77,77,35.9,8.7,18.0,.485,2.6,7.1,.375,6.1,11.0,.556,.558,4.7,5.6,.848,0.5,3.9,4.5,4.2,0.9,0.2,2.5,2.1,24.8,lavinza01
|
||||
22,Brandon Ingram,SF,25,NOP,45,45,34.2,9.0,18.6,.484,1.4,3.6,.390,7.6,14.9,.507,.522,5.3,6.0,.882,0.5,5.0,5.5,5.8,0.7,0.4,3.3,2.6,24.7,ingrabr01
|
||||
23,Anthony Edwards,SG,21,MIN,79,79,36.0,8.9,19.5,.459,2.7,7.3,.369,6.3,12.2,.513,.528,4.0,5.3,.756,0.6,5.2,5.8,4.4,1.6,0.7,3.3,2.4,24.6,edwaran01
|
||||
24,DeMar DeRozan,SF,33,CHI,74,74,36.2,8.9,17.6,.504,0.6,1.9,.324,8.3,15.7,.526,.522,6.2,7.1,.872,0.5,4.2,4.6,5.1,1.1,0.5,2.1,2.5,24.5,derozde01
|
||||
25,Nikola Jokić,C,27,DEN,69,69,33.7,9.4,14.8,.632,0.8,2.2,.383,8.5,12.7,.675,.660,4.9,6.0,.822,2.4,9.4,11.8,9.8,1.3,0.7,3.6,2.5,24.5,jokicni01
|
||||
26,Pascal Siakam,PF,28,TOR,71,71,37.4,8.9,18.5,.480,1.3,4.0,.324,7.6,14.5,.523,.515,5.2,6.7,.774,1.8,6.0,7.8,5.8,0.9,0.5,2.4,3.2,24.2,siakapa01
|
||||
27,Jalen Brunson,PG,26,NYK,68,68,35.0,8.6,17.6,.491,2.0,4.7,.416,6.7,12.8,.519,.547,4.8,5.8,.829,0.6,3.0,3.5,6.2,0.9,0.2,2.1,2.2,24.0,brunsja01
|
||||
28,Paul George,SF,32,LAC,56,56,34.6,8.2,17.9,.457,2.8,7.6,.371,5.4,10.3,.521,.536,4.6,5.3,.871,0.8,5.3,6.1,5.1,1.5,0.4,3.1,2.8,23.8,georgpa01
|
||||
29,Kawhi Leonard,SF,31,LAC,52,50,33.6,8.6,16.8,.512,2.0,4.8,.416,6.6,11.9,.551,.572,4.7,5.4,.871,1.1,5.4,6.5,3.9,1.4,0.5,1.7,1.6,23.8,leonaka01
|
||||
30,LaMelo Ball,PG,21,CHO,36,36,35.2,8.2,20.0,.411,4.0,10.6,.376,4.2,9.4,.450,.510,2.8,3.4,.836,1.2,5.3,6.4,8.4,1.3,0.3,3.6,3.3,23.3,ballla01
|
||||
31,Kristaps Porziņģis,C,27,WAS,65,65,32.6,7.8,15.7,.498,2.1,5.5,.385,5.7,10.2,.559,.565,5.4,6.4,.851,1.8,6.6,8.4,2.7,0.9,1.5,2.1,3.0,23.2,porzikr01
|
||||
32,Bradley Beal,SG,29,WAS,50,50,33.5,8.9,17.6,.506,1.6,4.4,.365,7.3,13.2,.552,.551,3.8,4.6,.842,0.8,3.1,3.9,5.4,0.9,0.7,2.9,2.1,23.2,bealbr01
|
||||
33,Jimmy Butler,PF,33,MIA,64,64,33.4,7.5,13.9,.539,0.6,1.6,.350,6.9,12.3,.564,.560,7.4,8.7,.850,2.2,3.7,5.9,5.3,1.8,0.3,1.6,1.3,22.9,butleji01
|
||||
34,Jalen Green,SG,20,HOU,76,76,34.2,7.4,17.9,.416,2.5,7.3,.338,5.0,10.6,.471,.485,4.8,6.1,.786,0.6,3.2,3.7,3.7,0.8,0.2,2.6,1.7,22.1,greenja05
|
||||
35,Keldon Johnson,SF,23,SAS,63,63,32.7,8.0,17.7,.452,2.1,6.5,.329,5.9,11.2,.523,.512,3.9,5.2,.749,0.9,4.2,5.0,2.9,0.7,0.2,2.1,2.0,22.0,johnske04
|
||||
36,Klay Thompson,SF,32,GSW,69,69,33.0,7.9,18.1,.436,4.4,10.6,.412,3.6,7.6,.470,.556,1.7,1.9,.879,0.6,3.6,4.1,2.4,0.7,0.4,1.8,1.9,21.9,thompkl01
|
||||
37,Bojan Bogdanović,PF,33,DET,59,59,32.1,7.3,14.9,.488,2.5,6.0,.411,4.8,9.0,.539,.570,4.5,5.1,.884,0.6,3.2,3.8,2.6,0.6,0.1,2.3,1.9,21.6,bogdabo02
|
||||
38,Darius Garland,PG,23,CLE,69,69,35.5,7.6,16.4,.462,2.4,6.0,.410,5.1,10.4,.492,.537,4.0,4.7,.863,0.4,2.3,2.7,7.8,1.2,0.1,2.9,2.1,21.6,garlada01
|
||||
39,Desmond Bane,SG,24,MEM,58,58,31.7,7.8,16.2,.479,2.9,7.0,.408,4.9,9.2,.534,.568,3.1,3.5,.883,0.7,4.3,5.0,4.4,1.0,0.4,2.2,2.6,21.5,banede01
|
||||
40,Kyle Kuzma,PF,27,WAS,64,64,35.0,8.0,17.8,.448,2.5,7.5,.333,5.5,10.3,.533,.518,2.7,3.7,.730,0.9,6.4,7.2,3.7,0.6,0.5,3.0,2.3,21.2,kuzmaky01
|
||||
41,Terry Rozier,SG,28,CHO,63,63,35.3,7.8,18.9,.415,2.6,8.0,.327,5.2,10.8,.480,.484,2.8,3.5,.809,0.8,3.3,4.1,5.1,1.2,0.3,2.1,1.9,21.1,roziete01
|
||||
42,Anfernee Simons,SG,23,POR,62,62,35.0,7.5,16.9,.447,3.4,9.1,.377,4.1,7.8,.528,.548,2.6,2.9,.894,0.3,2.3,2.6,4.1,0.7,0.2,2.1,2.3,21.1,simonan01
|
||||
43,James Harden,PG,33,PHI,58,58,36.8,6.4,14.5,.441,2.8,7.2,.385,3.6,7.3,.495,.536,5.4,6.2,.867,0.7,5.4,6.1,10.7,1.2,0.5,3.4,1.9,21.0,hardeja01
|
||||
44,CJ McCollum,SG,31,NOP,75,75,35.3,7.8,17.9,.437,2.8,7.2,.389,5.0,10.7,.469,.515,2.4,3.2,.769,0.7,3.6,4.4,5.7,0.9,0.5,2.4,2.0,20.9,mccolcj01
|
||||
45,Jordan Clarkson,SG,30,UTA,61,61,32.6,7.5,16.9,.444,2.5,7.5,.338,5.0,9.4,.530,.519,3.3,4.0,.816,1.2,2.9,4.0,4.4,0.5,0.2,3.0,2.0,20.8,clarkjo01
|
||||
46,Karl-Anthony Towns,PF,27,MIN,29,29,33.0,7.3,14.8,.495,2.1,5.7,.366,5.2,9.1,.576,.565,4.1,4.7,.874,1.7,6.5,8.1,4.8,0.7,0.6,3.0,3.8,20.8,townska01
|
||||
47,Tyrese Haliburton,PG,22,IND,56,56,33.6,7.4,15.0,.490,2.9,7.2,.400,4.5,7.8,.572,.586,3.1,3.6,.871,0.6,3.1,3.7,10.4,1.6,0.4,2.5,1.2,20.7,halibty01
|
||||
48,Jerami Grant,PF,28,POR,63,63,35.7,6.9,14.5,.475,2.3,5.7,.401,4.6,8.8,.523,.554,4.4,5.4,.813,0.8,3.7,4.5,2.4,0.8,0.8,1.8,2.4,20.5,grantje01
|
||||
49,Dejounte Murray,SG,26,ATL,74,74,36.4,8.3,17.8,.464,1.8,5.2,.344,6.5,12.6,.514,.514,2.1,2.6,.832,0.7,4.5,5.3,6.1,1.5,0.3,2.2,1.4,20.5,murrade01
|
||||
50,Bam Adebayo,C,25,MIA,75,75,34.6,8.0,14.9,.540,0.0,0.2,.083,8.0,14.7,.545,.541,4.3,5.4,.806,2.5,6.7,9.2,3.2,1.2,0.8,2.5,2.8,20.4,adebaba01
|
||||
|
@@ -0,0 +1,570 @@
|
||||
"code" "name"
|
||||
"0" "N/A (not applicable)"
|
||||
"10" "Chief executives"
|
||||
"20" "General and operations managers"
|
||||
"30" "Legislators"
|
||||
"40" "Advertising and promotions managers"
|
||||
"50" "Marketing and sales managers"
|
||||
"60" "Public relations managers"
|
||||
"100" "Administrative services managers"
|
||||
"110" "Computer and information systems managers"
|
||||
"120" "Financial managers"
|
||||
"135" "Compensation and Benefits Managers"
|
||||
"136" "Human Resources Managers"
|
||||
"137" "Training and Development Managers"
|
||||
"140" "Industrial production managers"
|
||||
"150" "Purchasing managers"
|
||||
"160" "Transportation, storage, and distribution managers"
|
||||
"205" "Farmers, Ranchers, and Other Agricultural Managers"
|
||||
"220" "Construction managers"
|
||||
"230" "Education administrators"
|
||||
"300" "Engineering managers"
|
||||
"310" "Food service managers"
|
||||
"325" "Funeral service managers"
|
||||
"330" "Gaming managers"
|
||||
"340" "Lodging managers"
|
||||
"350" "Medical and health services managers"
|
||||
"360" "Natural sciences managers"
|
||||
"400" "Postmasters and mail superintendents"
|
||||
"410" "Property, real estate, and community association managers"
|
||||
"420" "Social and community service managers"
|
||||
"425" "Emergency Management Directors"
|
||||
"430" "Managers, all other"
|
||||
"500" "Agents and business managers of artists, performers, and athletes"
|
||||
"510" "Purchasing agents and buyers, farm products"
|
||||
"520" "Wholesale and retail buyers, except farm products"
|
||||
"530" "Purchasing agents, except wholesale, retail, and farm products"
|
||||
"540" "Claims adjusters, appraisers, examiners, and investigators"
|
||||
"550" "Not used"
|
||||
"565" "Compliance officers"
|
||||
"600" "Cost estimators"
|
||||
"610" "Not used"
|
||||
"630" "Human resource workers"
|
||||
"640" "Compensation, benefits, and job analysis specialists"
|
||||
"650" "Training and development specialists"
|
||||
"700" "Logisticians"
|
||||
"710" "Management analysts"
|
||||
"725" "Meeting, convention, and event planners"
|
||||
"726" "Fundraisers"
|
||||
"735" "Market research analysts and marketing specialists"
|
||||
"740" "Business operations specialists, all other"
|
||||
"800" "Accountants and auditors"
|
||||
"810" "Appraisers and assessors of real estate"
|
||||
"820" "Budget analysts"
|
||||
"830" "Credit analysts"
|
||||
"840" "Financial analysts"
|
||||
"850" "Personal financial advisors"
|
||||
"860" "Insurance underwriters"
|
||||
"900" "Financial examiners"
|
||||
"910" "Loan counselors and officers"
|
||||
"920" "Not used"
|
||||
"930" "Tax examiners, collectors, and revenue agents"
|
||||
"940" "Tax preparers"
|
||||
"950" "Financial specialists, all other"
|
||||
"1000" "Computer scientists and systems analysts"
|
||||
"1005" "Computer and information research scientists"
|
||||
"1006" "Computer systems analysts"
|
||||
"1007" "Information security analysts"
|
||||
"1010" "Computer programmers"
|
||||
"1020" "Software developers, applications and systems software"
|
||||
"1030" "Web developers"
|
||||
"1050" "Computer support specialists"
|
||||
"1060" "Database administrators"
|
||||
"1105" "Network and computer systems administrators"
|
||||
"1106" "Computer network architects"
|
||||
"1107" "Computer occupations, all other"
|
||||
"1200" "Actuaries"
|
||||
"1210" "Mathematicians"
|
||||
"1220" "Operations research analysts"
|
||||
"1230" "Statisticians"
|
||||
"1240" "Miscellaneous mathematical science occupations"
|
||||
"1300" "Architects, except naval"
|
||||
"1310" "Surveyors, cartographers, and photogrammetrists"
|
||||
"1320" "Aerospace engineers"
|
||||
"1330" "Agricultural engineers"
|
||||
"1340" "Biomedical engineers"
|
||||
"1350" "Chemical engineers"
|
||||
"1360" "Civil engineers"
|
||||
"1400" "Computer hardware engineers"
|
||||
"1410" "Electrical and electronics engineers"
|
||||
"1420" "Environmental engineers"
|
||||
"1430" "Industrial engineers, including health and safety"
|
||||
"1440" "Marine engineers and naval architects"
|
||||
"1450" "Materials engineers"
|
||||
"1460" "Mechanical engineers"
|
||||
"1500" "Mining and geological engineers, including mining safety engineers"
|
||||
"1510" "Nuclear engineers"
|
||||
"1520" "Petroleum engineers"
|
||||
"1530" "Engineers, all other"
|
||||
"1540" "Drafters"
|
||||
"1550" "Engineering technicians, except drafters"
|
||||
"1560" "Surveying and mapping technicians"
|
||||
"1600" "Agricultural and food scientists"
|
||||
"1610" "Biological scientists"
|
||||
"1640" "Conservation scientists and foresters"
|
||||
"1650" "Medical scientists"
|
||||
"1660" "Life scientists, all other"
|
||||
"1700" "Astronomers and physicists"
|
||||
"1710" "Atmospheric and space scientists"
|
||||
"1720" "Chemists and materials scientists"
|
||||
"1730" "Not used"
|
||||
"1740" "Environmental scientists and geoscientists"
|
||||
"1750" "Not used"
|
||||
"1760" "Physical scientists, all other"
|
||||
"1800" "Economists"
|
||||
"1815" "Survey researchers"
|
||||
"1820" "Psychologists"
|
||||
"1830" "Sociologists"
|
||||
"1840" "Urban and regional planners"
|
||||
"1850" "Not used"
|
||||
"1860" "Miscellaneous social scientists and related workers"
|
||||
"1900" "Agricultural and food science technicians"
|
||||
"1910" "Biological technicians"
|
||||
"1920" "Chemical technicians"
|
||||
"1930" "Geological and petroleum technicians"
|
||||
"1940" "Nuclear technicians"
|
||||
"1950" "Social science research assistants"
|
||||
"1965" "Miscellaneous life, physical, and social science technicians"
|
||||
"2000" "Counselors"
|
||||
"2010" "Social workers"
|
||||
"2015" "Probation officers and correctional treatment specialists"
|
||||
"2016" "Social and human service assistants"
|
||||
"2025" "Miscellaneous community and social service specialists, including health educators and community health workers"
|
||||
"2030" "Not used"
|
||||
"2040" "Clergy"
|
||||
"2050" "Directors, religious activities and education"
|
||||
"2060" "Religious workers, all other"
|
||||
"2100" "Lawyers, Judges, magistrates, and other judicial workers"
|
||||
"2105" "Judicial law clerks"
|
||||
"2110" "Judges, magistrates, and other judicial workers"
|
||||
"2145" "Paralegals and legal assistants"
|
||||
"2160" "Miscellaneous legal support workers"
|
||||
"2200" "Postsecondary teachers"
|
||||
"2300" "Preschool and kindergarten teachers"
|
||||
"2310" "Elementary and middle school teachers"
|
||||
"2320" "Secondary school teachers"
|
||||
"2330" "Special education teachers"
|
||||
"2340" "Other teachers and instructors"
|
||||
"2400" "Archivists, curators, and museum technicians"
|
||||
"2430" "Librarians"
|
||||
"2440" "Library technicians"
|
||||
"2540" "Teacher assistants"
|
||||
"2550" "Other education, training, and library workers"
|
||||
"2600" "Artists and related workers"
|
||||
"2630" "Designers"
|
||||
"2700" "Actors"
|
||||
"2710" "Producers and directors"
|
||||
"2720" "Athletes, coaches, umpires, and related workers"
|
||||
"2730" "Not used"
|
||||
"2740" "Dancers and choreographers"
|
||||
"2750" "Musicians, singers, and related workers"
|
||||
"2760" "Entertainers and performers, sports and related workers, all other"
|
||||
"2800" "Announcers"
|
||||
"2810" "News analysts, reporters, and correspondents"
|
||||
"2825" "Public relations specialists"
|
||||
"2830" "Editors"
|
||||
"2840" "Technical writers"
|
||||
"2850" "Writers and authors"
|
||||
"2860" "Miscellaneous media and communications workers"
|
||||
"2900" "Broadcast and sound engineering technicians and radio operators"
|
||||
"2910" "Photographers"
|
||||
"2920" "Television, video, and motion picture camera operators and editors"
|
||||
"2960" "Media and communications workers, all other"
|
||||
"3000" "Chiropractors"
|
||||
"3010" "Dentists"
|
||||
"3020" "Not used"
|
||||
"3030" "Dietitians and nutritionists"
|
||||
"3040" "Optometrists"
|
||||
"3050" "Pharmacists"
|
||||
"3060" "Physicians and surgeons"
|
||||
"3110" "Physician assistants"
|
||||
"3120" "Podiatrists"
|
||||
"3140" "Audiologists"
|
||||
"3150" "Occupational therapists"
|
||||
"3160" "Physical therapists"
|
||||
"3200" "Radiation therapists"
|
||||
"3210" "Recreational therapists"
|
||||
"3220" "Respiratory therapists"
|
||||
"3230" "Speech-language pathologists"
|
||||
"3235" "Exercise Physiologists"
|
||||
"3245" "Therapists, all other"
|
||||
"3250" "Veterinarians"
|
||||
"3255" "Registered nurses"
|
||||
"3256" "Nurse anesthetists"
|
||||
"3257" "Nurse midwives"
|
||||
"3258" "Nurse practitioners"
|
||||
"3260" "Health diagnosing and treating practitioners, all other"
|
||||
"3300" "Clinical laboratory technologists and technicians"
|
||||
"3310" "Dental hygienists"
|
||||
"3320" "Diagnostic related technologists and technicians"
|
||||
"3400" "Emergency medical technicians and paramedics"
|
||||
"3420" "Health practitioner support technologists and technicians "
|
||||
"3500" "Licensed practical and licensed vocational nurses"
|
||||
"3510" "Medical records and health information technicians"
|
||||
"3520" "Opticians, dispensing"
|
||||
"3535" "Miscellaneous health technologists and technicians"
|
||||
"3540" "Other healthcare practitioners and technical occupations"
|
||||
"3600" "Nursing, psychiatric, and home health aides"
|
||||
"3610" "Occupational therapist assistants and aides"
|
||||
"3620" "Physical therapist assistants and aides"
|
||||
"3630" "Massage therapists"
|
||||
"3640" "Dental assistants"
|
||||
"3645" "Medical assistants"
|
||||
"3646" "Medical transcriptionists"
|
||||
"3647" "Pharmacy aides"
|
||||
"3648" "Veterinary assistants and labratory animal caretakers"
|
||||
"3649" "Phlebotmists"
|
||||
"3655" "Miscellaneous healthcare support occupations, including medical equipment preparers"
|
||||
"3700" "First-line supervisors/managers of correctional officers"
|
||||
"3710" "First-line supervisors/managers of police and detectives"
|
||||
"3720" "First-line supervisors/managers of fire fighting and preventions workers"
|
||||
"3730" "Supervisors, protective service workers, all other"
|
||||
"3740" "Fire fighters"
|
||||
"3750" "Fire inspectors"
|
||||
"3800" "Bailiffs, correctional officers, and jailers"
|
||||
"3810" "Not used"
|
||||
"3820" "Detectives and criminal investigators"
|
||||
"3830" "Fish and game wardens"
|
||||
"3840" "Parking enforcement workers"
|
||||
"3850" "Police and sheriff's patrol officers"
|
||||
"3860" "Transit and railroad police"
|
||||
"3900" "Animal control workers"
|
||||
"3910" "Private detectives and investigators"
|
||||
"3930" "Security guards and gaming surveillance officers"
|
||||
"3940" "Crossing guards"
|
||||
"3945" "Transportation security screeners"
|
||||
"3955" "Lifeguards and other recreational, and all other protective service workers"
|
||||
"4000" "Chefs and head cooks"
|
||||
"4010" "First-line supervisors/managers of food preparation and serving workers"
|
||||
"4020" "Cooks"
|
||||
"4030" "Food preparation workers"
|
||||
"4040" "Bartenders"
|
||||
"4050" "Combined food preparation and serving workers, including fast food"
|
||||
"4060" "Counter attendants, cafeteria, food concession, and coffee shop"
|
||||
"4110" "Waiters and waitresses"
|
||||
"4120" "Food servers, nonrestaurant"
|
||||
"4130" "Dining room, cafeteria attendants, and misc. food preparation workers"
|
||||
"4140" "Dishwashers"
|
||||
"4150" "Hosts and hostesses, restaurant, lounge, and coffee shop"
|
||||
"4160" "Food preparation and serving related workers, all other"
|
||||
"4200" "First-line supervisors/managers of housekeeping and janitorial workers"
|
||||
"4210" "First-line supervisors/managers of landscaping workers"
|
||||
"4220" "Janitors and building cleaners"
|
||||
"4230" "Maids and housekeeping cleaners"
|
||||
"4240" "Pest control workers"
|
||||
"4250" "Grounds maintenance workers"
|
||||
"4300" "First-line supervisors/managers of gaming workers"
|
||||
"4310" "Not used"
|
||||
"4320" "First-line supervisors/managers of personal service workers"
|
||||
"4330" "Not used"
|
||||
"4340" "Animal trainers"
|
||||
"4350" "Nonfarm animal caretakers"
|
||||
"4400" "Gaming services workers"
|
||||
"4410" "Motion picture projectionists"
|
||||
"4420" "Ushers, lobby attendants, and ticket takers"
|
||||
"4430" "Miscellaneous entertainment attendants and related workers"
|
||||
"4460" "Funeral service workers "
|
||||
"4465" "Morticians, undertakers, and funeral directors (2011 forward)"
|
||||
"4500" "Barbers"
|
||||
"4510" "Hairdressers, hairstylists, and cosmetologists"
|
||||
"4520" "Miscellaneous personal appearance workers"
|
||||
"4530" "Baggage porters, bellhops, and concierges"
|
||||
"4540" "Tour and travel guides"
|
||||
"4550" "Transportation attendants"
|
||||
"4600" "Child care workers"
|
||||
"4610" "Personal and home care aides"
|
||||
"4620" "Recreation and fitness workers"
|
||||
"4630" "Not used"
|
||||
"4640" "Residential advisors"
|
||||
"4650" "Personal care and service workers, all other"
|
||||
"4700" "First-line supervisors/managers of retail sales workers"
|
||||
"4710" "First-line supervisors/managers of non-retail sales workers"
|
||||
"4720" "Cashiers"
|
||||
"4730" "Not used"
|
||||
"4740" "Counter and rental clerks"
|
||||
"4750" "Parts salespersons"
|
||||
"4760" "Retail salespersons"
|
||||
"4800" "Advertising sales agents"
|
||||
"4810" "Insurance sales agents"
|
||||
"4820" "Securities, commodities, and financial services sales agents"
|
||||
"4830" "Travel agents"
|
||||
"4840" "Sales representatives, services, all other"
|
||||
"4850" "Sales representatives, wholesale and manufacturing"
|
||||
"4900" "Models, demonstrators, and product promoters"
|
||||
"4910" "Not used"
|
||||
"4920" "Real estate brokers and sales agents"
|
||||
"4930" "Sales engineers"
|
||||
"4940" "Telemarketers"
|
||||
"4950" "Door-to-door sales workers, news and street vendors, and related workers"
|
||||
"4965" "Sales and related workers, all other"
|
||||
"5000" "First-line supervisors/managers of office and administrative support workers"
|
||||
"5010" "Switchboard operators, including answering service"
|
||||
"5020" "Telephone operators"
|
||||
"5030" "Communications equipment operators, all other"
|
||||
"5100" "Bill and account collectors"
|
||||
"5110" "Billing and posting clerks and machine operators"
|
||||
"5120" "Bookkeeping, accounting, and auditing clerks"
|
||||
"5130" "Gaming cage workers"
|
||||
"5140" "Payroll and timekeeping clerks"
|
||||
"5150" "Procurement clerks"
|
||||
"5160" "Tellers"
|
||||
"5165" "Financial clerks, all other"
|
||||
"5200" "Brokerage clerks"
|
||||
"5210" "Correspondence clerks"
|
||||
"5220" "Court, municipal, and license clerks"
|
||||
"5230" "Credit authorizers, checkers, and clerks"
|
||||
"5240" "Customer service representatives"
|
||||
"5250" "Eligibility interviewers, government programs"
|
||||
"5260" "File clerks"
|
||||
"5300" "Hotel, motel, and resort desk clerks"
|
||||
"5310" "Interviewers, except eligibility and loan"
|
||||
"5320" "Library assistants, clerical"
|
||||
"5330" "Loan interviewers and clerks"
|
||||
"5340" "New accounts clerks"
|
||||
"5350" "Order clerks"
|
||||
"5360" "Human resources assistants, except payroll and timekeeping"
|
||||
"5400" "Receptionists and information clerks"
|
||||
"5410" "Reservation and transportation ticket agents and travel clerks"
|
||||
"5420" "Information and record clerks, all other"
|
||||
"5500" "Cargo and freight agents"
|
||||
"5510" "Couriers and messengers"
|
||||
"5520" "Dispatchers"
|
||||
"5530" "Meter readers, utilities"
|
||||
"5540" "Postal service clerks"
|
||||
"5550" "Postal service mail carriers"
|
||||
"5560" "Postal service mail sorters, processors, and processing machine operators"
|
||||
"5600" "Production, planning and expediting clerks"
|
||||
"5610" "Shipping, receiving, and traffic clerks"
|
||||
"5620" "Stock clerks and order fillers"
|
||||
"5630" "Weighers, measurers, checkers, and samplers, record keeping"
|
||||
"5700" "Secretaries and administrative assistants"
|
||||
"5800" "Computer operators"
|
||||
"5810" "Data entry keyers"
|
||||
"5820" "Word processors and typists"
|
||||
"5830" "Desktop publishers"
|
||||
"5840" "Insurance claims and policy processing clerks"
|
||||
"5850" "Mail clerks and mail machine operators, except postal service"
|
||||
"5860" "Office clerks, general"
|
||||
"5900" "Office machine operators, except computer"
|
||||
"5910" "Proofreaders and copy markers"
|
||||
"5920" "Statistical assistants"
|
||||
"5940" "Office and administrative support workers, all other"
|
||||
"6005" "First-line supervisors of farming, fishing, and forestry workers"
|
||||
"6010" "Agricultural inspectors"
|
||||
"6020" "Animal breeders"
|
||||
"6030" "Not used"
|
||||
"6040" "Graders and sorters, agricultural products"
|
||||
"6050" "Miscellaneous agricultural workers"
|
||||
"6100" "Fishers and related fishing workers"
|
||||
"6110" "Hunters and trappers"
|
||||
"6120" "Forest and conservation workers"
|
||||
"6130" "Logging workers"
|
||||
"6200" "First-line supervisors/managers of construction trades and extraction workers"
|
||||
"6210" "Boilermakers"
|
||||
"6220" "Brickmasons, blockmasons, and stonemasons"
|
||||
"6230" "Carpenters"
|
||||
"6240" "Carpet, floor, and tile installers and finishers"
|
||||
"6250" "Cement masons, concrete finishers, and terrazzo workers"
|
||||
"6260" "Construction laborers"
|
||||
"6300" "Paving, surfacing, and tamping equipment operators"
|
||||
"6310" "Pile-driver operators"
|
||||
"6320" "Operating engineers and other construction equipment operators"
|
||||
"6330" "Drywall installers, ceiling tile installers, and tapers"
|
||||
"6340" "Not used"
|
||||
"6355" "Electricians"
|
||||
"6360" "Glaziers"
|
||||
"6400" "Insulation workers"
|
||||
"6410" "Not used"
|
||||
"6420" "Painters, construction and maintenance"
|
||||
"6430" "Paperhangers"
|
||||
"6440" "Pipelayers, plumbers, pipefitters, and steamfitters"
|
||||
"6450" "Not used"
|
||||
"6460" "Plasterers and stucco masons"
|
||||
"6500" "Reinforcing iron and rebar workers"
|
||||
"6515" "Roofers"
|
||||
"6520" "Sheet metal workers"
|
||||
"6530" "Solar Photovoltaic Installers"
|
||||
"6540" "Structural iron and steel workers"
|
||||
"6600" "Helpers, construction trades"
|
||||
"6660" "Construction and building inspectors"
|
||||
"6700" "Elevator installers and repairers"
|
||||
"6710" "Fence erectors"
|
||||
"6720" "Hazardous materials removal workers"
|
||||
"6730" "Highway maintenance workers"
|
||||
"6740" "Rail-track laying and maintenance equipment operators"
|
||||
"6750" "Septic tank servicers and sewer pipe cleaners"
|
||||
"6765" "Miscellaneous construction and related workers"
|
||||
"6800" "Derrick, rotary drill, and service unit operators, oil, gas, and mining"
|
||||
"6810" "Not used"
|
||||
"6820" "Earth drillers, except oil and gas"
|
||||
"6830" "Explosives workers, ordnance handling experts, and blasters"
|
||||
"6840" "Mining machine operators"
|
||||
"6910" "Roof bolters, mining"
|
||||
"6920" "Roustabouts, oil and gas"
|
||||
"6930" "Helpers -- extraction workers"
|
||||
"6940" "Other extraction workers"
|
||||
"7000" "First-line supervisors/managers of mechanics, installers, and repairers"
|
||||
"7010" "Computer, automated teller, and office machine repairers"
|
||||
"7020" "Radio and telecommunications equipment installers and repairers"
|
||||
"7030" "Avionics technicians"
|
||||
"7040" "Electric motor, power tool, and related repairers"
|
||||
"7050" "Electrical and electronics installers and repairers, transportation equipment"
|
||||
"7100" "Electrical and electronics repairers, industrial and utility"
|
||||
"7110" "Electronic equipment installers and repairers, motor vehicles"
|
||||
"7120" "Electronic home entertainment equipment installers and repairers"
|
||||
"7130" "Security and fire alarm systems installers"
|
||||
"7140" "Aircraft mechanics and service technicians"
|
||||
"7150" "Automotive body and related repairers"
|
||||
"7160" "Automotive glass installers and repairers"
|
||||
"7200" "Automotive service technicians and mechanics"
|
||||
"7210" "Bus and truck mechanics and diesel engine specialists"
|
||||
"7220" "Heavy vehicle and mobile equipment service technicians and mechanics"
|
||||
"7230" "Not used"
|
||||
"7240" "Small engine mechanics"
|
||||
"7250" "Not used"
|
||||
"7260" "Miscellaneous vehicle and mobile equipment mechanics, installers, and repairers"
|
||||
"7300" "Control and valve installers and repairers"
|
||||
"7315" "Heating, air conditioning, and refrigeration mechanics and installers"
|
||||
"7320" "Home appliance repairers"
|
||||
"7330" "Industrial and refractory machinery mechanics"
|
||||
"7340" "Maintenance and repair workers, general"
|
||||
"7350" "Maintenance workers, machinery"
|
||||
"7360" "Millwrights"
|
||||
"7410" "Electrical power-line installers and repairers"
|
||||
"7420" "Telecommunications line installers and repairers"
|
||||
"7430" "Precision instrument and equipment repairers"
|
||||
"7440" "Wind turbine service technicians"
|
||||
"7510" "Coin, vending, and amusement machine servicers and repairers"
|
||||
"7520" "Commercial divers"
|
||||
"7530" "Not used"
|
||||
"7540" "Locksmiths and safe repairers"
|
||||
"7550" "Manufactured building and mobile home installers"
|
||||
"7560" "Riggers"
|
||||
"7600" "Signal and track switch repairers"
|
||||
"7610" "Helpers--installation, maintenance, and repair workers"
|
||||
"7630" "Other installation, maintenance, and repair workers"
|
||||
"7700" "First-line supervisors/managers of production and operating workers"
|
||||
"7710" "Aircraft structure, surfaces, rigging, and systems assemblers"
|
||||
"7720" "Electrical, electronics, and electromechanical assemblers"
|
||||
"7730" "Engine and other machine assemblers"
|
||||
"7740" "Structural metal fabricators and fitters"
|
||||
"7750" "Miscellaneous assemblers and fabricators"
|
||||
"7800" "Bakers"
|
||||
"7810" "Butchers and other meat, poultry, and fish processing workers"
|
||||
"7820" "Not used"
|
||||
"7830" "Food and tobacco roasting, baking, and drying machine operators and tenders"
|
||||
"7840" "Food batchmakers"
|
||||
"7850" "Food cooking machine operators and tenders"
|
||||
"7855" "Food processing workers, all other"
|
||||
"7900" "Computer control programmers and operators"
|
||||
"7910" "Not used"
|
||||
"7920" "Extruding and drawing machine setters, operators, and tenders, metal and plastic"
|
||||
"7930" "Forging machine setters, operators, and tenders, metal and plastic"
|
||||
"7940" "Rolling machine setters, operators, and tenders, metal and plastic"
|
||||
"7950" "Cutting, punching, and press machine setters, operators, and tenders, metal and plastic"
|
||||
"7960" "Drilling and boring machine tool setters, operators, and tenders, metal and plastic"
|
||||
"8000" "Grinding, lapping, polishing, and buffing machine tool setters, operators, and tenders, metal and plastic"
|
||||
"8010" "Lathe and turning machine tool setters, operators, and tenders, metal and plastic"
|
||||
"8020" "Milling and planing machine setters, operators, and tenders, metal and plastic"
|
||||
"8030" "Machinists"
|
||||
"8040" "Metal furnace and kiln operators and tenders"
|
||||
"8050" "Not used"
|
||||
"8060" "Model makers and patternmakers, metal and plastic"
|
||||
"8100" "Molders and molding machine setters, operators, and tenders, metal and plastic"
|
||||
"8110" "Not used"
|
||||
"8120" "Multiple machine tool setters, operators, and tenders, metal and plastic"
|
||||
"8130" "Tool and die makers"
|
||||
"8140" "Welding, soldering, and brazing workers"
|
||||
"8150" "Heat treating equipment setters, operators, and tenders, metal and plastic"
|
||||
"8160" "Lay-out workers, metal and plastic"
|
||||
"8200" "Plating and coating machine setters, operators, and tenders, metal and plastic"
|
||||
"8210" "Tool grinders, filers, and sharpeners"
|
||||
"8220" "Metalworkers and plastic workers,all others"
|
||||
"8250" "Prepress technicians and workers"
|
||||
"8255" "Printing machine operators"
|
||||
"8256" "Print binding and finishing workers"
|
||||
"8300" "Laundry and dry-cleaning workers"
|
||||
"8310" "Pressers, textile, garment, and related materials"
|
||||
"8320" "Sewing machine operators"
|
||||
"8330" "Shoe and leather workers and repairers"
|
||||
"8340" "Shoe machine operators and tenders"
|
||||
"8350" "Tailors, dressmakers, and sewers"
|
||||
"8360" "Textile bleaching and dyeing machine operators and tenders"
|
||||
"8400" "Textile cutting machine setters, operators, and tenders"
|
||||
"8410" "Textile knitting and weaving machine setters, operators, and tenders"
|
||||
"8420" "Textile winding, twisting, and drawing out machine setters, operators, and tenders"
|
||||
"8430" "Extruding and forming machine setters, operators, and tenders, synthetic and glass fibers"
|
||||
"8440" "Fabric and apparel patternmakers"
|
||||
"8450" "Upholsterers"
|
||||
"8460" "Textile, apparel, and furnishings workers, all others"
|
||||
"8500" "Cabinetmakers and bench carpenters"
|
||||
"8510" "Furniture finishers"
|
||||
"8520" "Model makers and patternmakers, wood"
|
||||
"8530" "Sawing machine setters, operators, and tenders, wood"
|
||||
"8540" "Woodworking machine setters, operators, and tenders, except sawing"
|
||||
"8550" "Woodworkers, all others"
|
||||
"8600" "Power plant operators, distributors, and dispatchers"
|
||||
"8610" "Stationary engineers and boiler operators"
|
||||
"8620" "Water and liquid waste treatment plant and system operators"
|
||||
"8630" "Miscellaneous plant and system operators"
|
||||
"8640" "Chemical processing machine setters, operators, and tenders"
|
||||
"8650" "Crushing, grinding, polishing, mixing, and blending workers"
|
||||
"8710" "Cutting workers"
|
||||
"8720" "Extruding, forming, pressing, and compacting machine setters, operators, and tenders"
|
||||
"8730" "Furnace, kiln, oven, drier, and kettle operators and tenders"
|
||||
"8740" "Inspectors, testers, sorters, samplers, and weighers"
|
||||
"8750" "Jewelers and precious stone and metal workers"
|
||||
"8760" "Medical, dental, and ophthalmic laboratory technicians"
|
||||
"8800" "Packaging and filling machine operators and tenders"
|
||||
"8810" "Painting workers"
|
||||
"8820" "Not used"
|
||||
"8830" "Photographic process workers and processing machine operators"
|
||||
"8840" "Semiconductor processors"
|
||||
"8850" "Cementing and gluing machine operators and tenders"
|
||||
"8860" "Cleaning, washing, and metal pickling equipment operators and tenders"
|
||||
"8900" "Cooling and freezing equipment operators and tenders"
|
||||
"8910" "Etchers and engravers"
|
||||
"8920" "Molders, shapers, and casters, except metal and plastic"
|
||||
"8930" "Paper goods machine setters, operators, and tenders"
|
||||
"8940" "Tire builders"
|
||||
"8950" "Helpers--production workers"
|
||||
"8965" "Production workers, all other"
|
||||
"9000" "Supervisors, transportation and material moving workers"
|
||||
"9030" "Aircraft pilots and flight engineers"
|
||||
"9040" "Air traffic controllers and airfield operations specialists"
|
||||
"9050" "Flight attendants"
|
||||
"9110" "Ambulance drivers and attendants, except emergency medical technicians"
|
||||
"9120" "Bus drivers"
|
||||
"9130" "Driver/sales workers and truck drivers"
|
||||
"9140" "Taxi drivers and chauffeurs"
|
||||
"9150" "Motor vehicle operators, all other"
|
||||
"9200" "Locomotive engineers and operators"
|
||||
"9230" "Railroad brake, signal, and switch operators"
|
||||
"9240" "Railroad conductors and yardmasters"
|
||||
"9250" "Not used"
|
||||
"9260" "Subway, streetcar, and other rail transportation workers"
|
||||
"9300" "Sailors and marine oilers"
|
||||
"9310" "Ship and boat captains and operators"
|
||||
"9320" "Not used"
|
||||
"9330" "Ship engineers"
|
||||
"9340" "Bridge and lock tenders"
|
||||
"9350" "Parking lot attendants"
|
||||
"9360" "Service station attendants"
|
||||
"9410" "Transportation inspectors"
|
||||
"9415" "Transportation attendants, except flight attendants"
|
||||
"9420" "Other transportation workers"
|
||||
"9500" "Conveyor operators and tenders"
|
||||
"9510" "Crane and tower operators"
|
||||
"9520" "Dredge, excavating, and loading machine operators"
|
||||
"9560" "Hoist and winch operators"
|
||||
"9600" "Industrial truck and tractor operators"
|
||||
"9610" "Cleaners of vehicles and equipment"
|
||||
"9620" "Laborers and freight, stock, and material movers, hand"
|
||||
"9630" "Machine feeders and offbearers"
|
||||
"9640" "Packers and packagers, hand"
|
||||
"9650" "Pumping station operators"
|
||||
"9720" "Refuse and recyclable material collectors"
|
||||
"9730" "Shuttle car operators"
|
||||
"9740" "Tank car, truck, and ship loaders"
|
||||
"9750" "Material moving workers, all other"
|
||||
"9840" "Armed forces"
|
||||
|
File diff suppressed because it is too large.
Load diff
@@ -0,0 +1,521 @@
|
||||
"id","grp","nwt"
|
||||
"530","Business Operations",3249.4
|
||||
"4720","Sales and Related",32032.3
|
||||
"4760","Sales and Related",29531.3
|
||||
"4700","Sales and Related",27463.5
|
||||
"430","Management",33320.7
|
||||
"4710","Sales and Related",9713.4
|
||||
"4220","Building and Grounds Cleaning and Maintenance",20360.4
|
||||
"4020","Food Preparation and Serving",18940.5
|
||||
"4230","Building and Grounds Cleaning and Maintenance",13073.6
|
||||
"9130","Transportation and Material Moving",28642.3
|
||||
"9620","Transportation and Material Moving",17218.6
|
||||
"5700","Office and Administrative Support",25750.9
|
||||
"310","Management",9200.1
|
||||
"4030","Food Preparation and Serving",8313.4
|
||||
"4010","Food Preparation and Serving",4952
|
||||
"20","Management",8041.3
|
||||
"4110","Food Preparation and Serving",19203.9
|
||||
"2310","Education, Training, and Library",27008.8
|
||||
"4250","Building and Grounds Cleaning and Maintenance",12301.9
|
||||
"10","Management",12449.8
|
||||
"5240","Office and Administrative Support",18948.3
|
||||
"4850","Sales and Related",10785.1
|
||||
"4610","Personal Care and Service",11144.6
|
||||
"2320","Education, Training, and Library",9598
|
||||
"4600","Personal Care and Service",11797.6
|
||||
"3600","Healthcare Support",17944.7
|
||||
"5860","Office and Administrative Support",10749.4
|
||||
"2340","Education, Training, and Library",7791.7
|
||||
"4000","Food Preparation and Serving",3515.2
|
||||
"5400","Office and Administrative Support",11378.5
|
||||
"3645","Healthcare Support",3868.9
|
||||
"2010","Community and Social Services",6455.6
|
||||
"3420","Healthcare Practitioners and Technicians",4821.3
|
||||
"2000","Community and Social Services",6475
|
||||
"5620","Office and Administrative Support",14086.5
|
||||
"6320","Construction",3297.8
|
||||
"205","Management",7331.7
|
||||
"4510","Personal Care and Service",6357.5
|
||||
"120","Management",10195.4
|
||||
"3255","Healthcare Practitioners and Technicians",24520.9
|
||||
"2300","Education, Training, and Library",6052.8
|
||||
"9640","Transportation and Material Moving",5039.9
|
||||
"50","Management",8098.4
|
||||
"230","Management",7283.6
|
||||
"4810","Sales and Related",5092.2
|
||||
"4920","Sales and Related",7038.5
|
||||
"5120","Office and Administrative Support",10748.2
|
||||
"6260","Construction",14730.5
|
||||
"410","Management",5415.9
|
||||
"220","Management",6818
|
||||
"4040","Food Preparation and Serving",3625.9
|
||||
"350","Management",4901.2
|
||||
"3655",NA,1392.3
|
||||
"9120","Transportation and Material Moving",4999.3
|
||||
"710","Business Operations",7044.1
|
||||
"110","Management",5328.8
|
||||
"1020","Computer and Mathematical",10129.6
|
||||
"4050","Food Preparation and Serving",3378
|
||||
"9600","Transportation and Material Moving",4966
|
||||
"4840","Sales and Related",3958.6
|
||||
"3640","Healthcare Support",2458
|
||||
"2630","Arts, Design, Entertainment, Sports, and Media",7155.8
|
||||
"5610","Office and Administrative Support",4996.7
|
||||
"3500","Healthcare Practitioners and Technicians",5085
|
||||
"4300","Personal Care and Service",1325.7
|
||||
"2160",NA,1642
|
||||
"2550","Education, Training, and Library",1546.4
|
||||
"6420","Construction",4952.5
|
||||
"2145","Legal",3457.2
|
||||
"2540","Education, Training, and Library",8392.3
|
||||
"3060","Healthcare Practitioners and Technicians",7573.6
|
||||
"6440","Construction",5117.7
|
||||
"420","Management",3193.6
|
||||
"7200","Installation, Maintenance, and Repair",7290.3
|
||||
"9140","Transportation and Material Moving",3630
|
||||
"4200","Building and Grounds Cleaning and Maintenance",2445.7
|
||||
"2040","Community and Social Services",3602.3
|
||||
"3930","Protective Service",8288.2
|
||||
"4320","Personal Care and Service",1588.9
|
||||
"4620","Personal Care and Service",4094.6
|
||||
"4210","Building and Grounds Cleaning and Maintenance",1819.6
|
||||
"2720","Arts, Design, Entertainment, Sports, and Media",3010.2
|
||||
"2600","Arts, Design, Entertainment, Sports, and Media",1676.9
|
||||
"3050","Healthcare Practitioners and Technicians",2358.6
|
||||
"4130","Food Preparation and Serving",3270.9
|
||||
"4140","Food Preparation and Serving",2639.2
|
||||
"4800","Sales and Related",2046.9
|
||||
"5550","Office and Administrative Support",2781.5
|
||||
"8140","Production",5152.8
|
||||
"5940","Office and Administrative Support",4557.6
|
||||
"6330","Construction",1330.6
|
||||
"3820","Protective Service",1339.6
|
||||
"8740","Production",6374.1
|
||||
"8965","Production",7954.9
|
||||
"1050","Computer and Mathematical",4327.2
|
||||
"3630","Healthcare Support",1467.3
|
||||
"7750","Production",8789.7
|
||||
"6040","Farming, Fishing, and Forestry",1109.7
|
||||
"5160","Office and Administrative Support",3023.8
|
||||
"4150","Food Preparation and Serving",2631.9
|
||||
"4060","Food Preparation and Serving",2374.7
|
||||
"140","Management",2236.8
|
||||
"3010","Healthcare Practitioners and Technicians",1416.3
|
||||
"6240","Construction",1351.1
|
||||
"3150","Healthcare Practitioners and Technicians",1030.5
|
||||
"1550","Technicians",3143.6
|
||||
"4965","Sales and Related",2138.6
|
||||
"850","Financial Specialists",3780.8
|
||||
"1540","Architecture and Engineering",1117.5
|
||||
"910","Financial Specialists",2857.5
|
||||
"2430","Education, Training, and Library",1586.9
|
||||
"3800","Protective Service",3359.1
|
||||
"630","Business Operations",5179.6
|
||||
"2330","Education, Training, and Library",2946.8
|
||||
"1006","Computer and Mathematical",4280.2
|
||||
"840","Financial Specialists",1634.1
|
||||
"4520","Personal Care and Service",2435.5
|
||||
"3160","Healthcare Practitioners and Technicians",1969.3
|
||||
"3910","Protective Service",737.8
|
||||
"1530","Architecture and Engineering",3418.6
|
||||
"5510","Office and Administrative Support",1923.4
|
||||
"800","Financial Specialists",14715.4
|
||||
"5110","Office and Administrative Support",3934
|
||||
"2830","Arts, Design, Entertainment, Sports, and Media",1529
|
||||
"3245","Healthcare Practitioners and Technicians",1428.5
|
||||
"160","Management",2154.1
|
||||
"9000","Transportation and Material Moving",1639.7
|
||||
"1010","Computer and Mathematical",3690.6
|
||||
"3300","Healthcare Practitioners and Technicians",2980.9
|
||||
"9610","Transportation and Material Moving",3007
|
||||
"5540","Office and Administrative Support",1025.8
|
||||
"7340","Installation, Maintenance, and Repair",4101.2
|
||||
"5810","Office and Administrative Support",2809.2
|
||||
"2016","Community and Social Services",1499.9
|
||||
"4120","Food Preparation and Serving",1768.2
|
||||
"5520","Office and Administrative Support",2280.5
|
||||
"3710","Protective Service",950.8
|
||||
"8220","Production",3348.8
|
||||
"7420","Installation, Maintenance, and Repair",1669
|
||||
"5260","Office and Administrative Support",2305.7
|
||||
"7810","Production",2685.6
|
||||
"3700","Protective Service",412.5
|
||||
"3320","Healthcare Practitioners and Technicians",2646.4
|
||||
"5600","Office and Administrative Support",2145.1
|
||||
"7210","Installation, Maintenance, and Repair",2717.9
|
||||
"7800","Production",1931.6
|
||||
"1107","Computer and Mathematical",3637.7
|
||||
"7720","Production",1358.5
|
||||
"1410","Architecture and Engineering",2566.5
|
||||
"7330","Installation, Maintenance, and Repair",3579.5
|
||||
"6050","Farming, Fishing, and Forestry",7606.1
|
||||
"5300","Office and Administrative Support",1098.8
|
||||
"340","Management",1179.3
|
||||
"8950","Production",350.4
|
||||
"100","Management",1287.4
|
||||
"9150","Transportation and Material Moving",613.4
|
||||
"5100","Office and Administrative Support",1490.5
|
||||
"6940","Extraction",664.9
|
||||
"1360","Architecture and Engineering",2969.5
|
||||
"1460","Architecture and Engineering",2555.7
|
||||
"1560","Technicians",597
|
||||
"3730","Protective Service",743.5
|
||||
"5000","Office and Administrative Support",11775.6
|
||||
"6250","Construction",547.4
|
||||
"1030","Computer and Mathematical",1682.3
|
||||
"540","Business Operations",2732.2
|
||||
"6230","Construction",11326.7
|
||||
"300","Management",916
|
||||
"2050","Community and Social Services",569
|
||||
"740",NA,2138.5
|
||||
"9840",NA,6353.6
|
||||
"3400","Healthcare Practitioners and Technicians",1695.4
|
||||
"1105","Computer and Mathematical",1854.6
|
||||
"2825","Arts, Design, Entertainment, Sports, and Media",1237.8
|
||||
"735",NA,2133.8
|
||||
"2025","Community and Social Services",865.8
|
||||
"2850","Arts, Design, Entertainment, Sports, and Media",1930
|
||||
"6130","Farming, Fishing, and Forestry",633.8
|
||||
"8030","Production",3262.8
|
||||
"1965","Life, Physical, and Social Science",1383.5
|
||||
"3649","Healthcare Support",875.9
|
||||
"1860","Life, Physical, and Social Science",537.8
|
||||
"5360","Office and Administrative Support",714.1
|
||||
"4740","Sales and Related",1018.5
|
||||
"8800","Production",2236.2
|
||||
"1920","Life, Physical, and Social Science",575
|
||||
"4820","Sales and Related",2275.4
|
||||
"4430","Personal Care and Service",1903.7
|
||||
"4350","Personal Care and Service",1654.3
|
||||
"4950","Sales and Related",1567.9
|
||||
"2750","Arts, Design, Entertainment, Sports, and Media",1641.9
|
||||
"3647","Healthcare Support",444.4
|
||||
"136","Management",2048.1
|
||||
"6800","Extraction",428.6
|
||||
"565","Business Operations",1792.6
|
||||
"5840","Office and Administrative Support",2291.6
|
||||
"810","Financial Specialists",659.2
|
||||
"4940","Sales and Related",794.5
|
||||
"6515","Construction",1953.9
|
||||
"950","Financial Specialists",632.9
|
||||
"4400","Personal Care and Service",865.6
|
||||
"2810","Arts, Design, Entertainment, Sports, and Media",695
|
||||
"2200","Education, Training, and Library",11838.2
|
||||
"5560","Office and Administrative Support",571.3
|
||||
"5140","Office and Administrative Support",1215.9
|
||||
"9350","Transportation and Material Moving",707.4
|
||||
"2400","Education, Training, and Library",468.8
|
||||
"3955",NA,1850.6
|
||||
"2710","Arts, Design, Entertainment, Sports, and Media",1349
|
||||
"7220","Installation, Maintenance, and Repair",1709.6
|
||||
"1650","Life, Physical, and Social Science",1275.4
|
||||
"725","Business Operations",1228.3
|
||||
"8320","Production",1670.9
|
||||
"3510","Healthcare Practitioners and Technicians",1110.7
|
||||
"3220","Healthcare Practitioners and Technicians",773.9
|
||||
"7315","Installation, Maintenance, and Repair",3203.5
|
||||
"9420","Transportation and Material Moving",261.5
|
||||
"5310","Office and Administrative Support",1593.8
|
||||
"3310","Healthcare Practitioners and Technicians",1459.7
|
||||
"3535","Healthcare Practitioners and Technicians",956.2
|
||||
"9050","Transportation and Material Moving",713.4
|
||||
"8640","Production",469.3
|
||||
"3540","Healthcare Practitioners and Technicians",817.8
|
||||
"1760","Life, Physical, and Social Science",1723
|
||||
"3230","Healthcare Practitioners and Technicians",1206.3
|
||||
"4750","Sales and Related",850
|
||||
"6460","Construction",272.1
|
||||
"7630","Installation, Maintenance, and Repair",1709.3
|
||||
"6100","Farming, Fishing, and Forestry",376.1
|
||||
"860","Financial Specialists",865.9
|
||||
"7010","Installation, Maintenance, and Repair",2290.4
|
||||
"9720","Transportation and Material Moving",726.1
|
||||
"6520","Construction",1018.4
|
||||
"2015","Community and Social Services",811.9
|
||||
"5850","Office and Administrative Support",764.2
|
||||
"1240","Computer and Mathematical",623.2
|
||||
"8300","Production",1540.3
|
||||
"2910","Arts, Design, Entertainment, Sports, and Media",1450.2
|
||||
"2900","Arts, Design, Entertainment, Sports, and Media",929.8
|
||||
"1106","Computer and Mathematical",918
|
||||
"7020","Installation, Maintenance, and Repair",1302.8
|
||||
"3258","Healthcare Practitioners and Technicians",1148.4
|
||||
"9030","Transportation and Material Moving",895.3
|
||||
"150","Management",1733.2
|
||||
"4900","Sales and Related",717
|
||||
"3648","Healthcare Support",387.7
|
||||
"5820","Office and Administrative Support",873.1
|
||||
"1430","Architecture and Engineering",1439.2
|
||||
"3720","Protective Service",423.4
|
||||
"1610","Life, Physical, and Social Science",840.5
|
||||
"600","Business Operations",1004.9
|
||||
"4650","Personal Care and Service",1066.1
|
||||
"9510","Transportation and Material Moving",584.3
|
||||
"7840","Production",821.8
|
||||
"2860","Arts, Design, Entertainment, Sports, and Media",858.8
|
||||
"650","Business Operations",1131.2
|
||||
"940","Financial Specialists",1295.5
|
||||
"6840","Extraction",549.8
|
||||
"4240","Building and Grounds Cleaning and Maintenance",581.3
|
||||
"3620","Healthcare Support",602.8
|
||||
"5350","Office and Administrative Support",860.6
|
||||
"2920","Arts, Design, Entertainment, Sports, and Media",579.6
|
||||
"2700","Arts, Design, Entertainment, Sports, and Media",525
|
||||
"4500","Personal Care and Service",868.4
|
||||
"8810","Production",1214.5
|
||||
"2800","Arts, Design, Entertainment, Sports, and Media",424
|
||||
"4530","Personal Care and Service",655.4
|
||||
"1220","Computer and Mathematical",1086.8
|
||||
"3030","Healthcare Practitioners and Technicians",947.7
|
||||
"2100","Legal",8809.5
|
||||
"6710","Construction",333.2
|
||||
"520","Business Operations",844.3
|
||||
"3110","Healthcare Practitioners and Technicians",795.3
|
||||
"6730","Construction",1014.1
|
||||
"1060","Computer and Mathematical",904.4
|
||||
"1350","Architecture and Engineering",571.7
|
||||
"3840","Protective Service",117.7
|
||||
"5410","Office and Administrative Support",871.7
|
||||
"4540","Personal Care and Service",453.2
|
||||
"7855","Production",974.3
|
||||
"9750","Transportation and Material Moving",451.4
|
||||
"1820","Life, Physical, and Social Science",1644.8
|
||||
"8650","Production",688.3
|
||||
"1007","Computer and Mathematical",483.5
|
||||
"1310","Architecture and Engineering",327.3
|
||||
"6400","Construction",392.7
|
||||
"8710","Production",633.9
|
||||
"6200","Construction",5730.6
|
||||
"1720","Life, Physical, and Social Science",851.5
|
||||
"5020","Office and Administrative Support",295.1
|
||||
"4830","Sales and Related",622.6
|
||||
"1320","Architecture and Engineering",1148.7
|
||||
"6355","Construction",6414.2
|
||||
"5800","Office and Administrative Support",727.1
|
||||
"5420","Office and Administrative Support",1132.5
|
||||
"5330","Office and Administrative Support",1111.1
|
||||
"2440","Education, Training, and Library",370.5
|
||||
"8750","Production",406.1
|
||||
"1200","Computer and Mathematical",195.8
|
||||
"7410","Installation, Maintenance, and Repair",964.7
|
||||
"7260","Installation, Maintenance, and Repair",837.6
|
||||
"8760","Production",754.5
|
||||
"1400","Architecture and Engineering",678.2
|
||||
"8255","Production",1541
|
||||
"4640","Personal Care and Service",459.5
|
||||
"8620","Production",643.1
|
||||
"2760","Arts, Design, Entertainment, Sports, and Media",348.6
|
||||
"4340","Personal Care and Service",320.4
|
||||
"3940","Protective Service",653.5
|
||||
"820","Financial Specialists",459.9
|
||||
"40","Management",499.8
|
||||
"8500","Production",473.9
|
||||
"7360","Installation, Maintenance, and Repair",514.2
|
||||
"7140","Installation, Maintenance, and Repair",1216.4
|
||||
"726","Business Operations",603.5
|
||||
"1420","Architecture and Engineering",389
|
||||
"3646","Healthcare Support",423.9
|
||||
"5220","Office and Administrative Support",775.2
|
||||
"7150","Installation, Maintenance, and Repair",1187.4
|
||||
"5500","Office and Administrative Support",187.2
|
||||
"5165","Office and Administrative Support",516.7
|
||||
"8350","Production",827.8
|
||||
"6220","Construction",1284.3
|
||||
"6820","Extraction",215.5
|
||||
"2840","Arts, Design, Entertainment, Sports, and Media",513.5
|
||||
"9360","Transportation and Material Moving",819.6
|
||||
"640","Business Operations",569.9
|
||||
"7120","Installation, Maintenance, and Repair",392.1
|
||||
"6765","Construction",371
|
||||
"930","Financial Specialists",582.6
|
||||
"6600","Construction",498.8
|
||||
"1005","Computer and Mathematical",178.9
|
||||
"1900","Life, Physical, and Social Science",206
|
||||
"6120","Farming, Fishing, and Forestry",207.8
|
||||
"4420","Personal Care and Service",483.6
|
||||
"2060","Community and Social Services",636.7
|
||||
"60","Management",541.4
|
||||
"6360","Construction",389.4
|
||||
"7040","Installation, Maintenance, and Repair",240.3
|
||||
"8130","Production",548.9
|
||||
"7830","Production",160.1
|
||||
"1520","Architecture and Engineering",302.5
|
||||
"8600","Production",366
|
||||
"3945","Protective Service",296.3
|
||||
"5900","Office and Administrative Support",386
|
||||
"1840","Life, Physical, and Social Science",210.3
|
||||
"1740","Life, Physical, and Social Science",802.7
|
||||
"9040","Transportation and Material Moving",286.6
|
||||
"8000","Production",456.7
|
||||
"7000","Installation, Maintenance, and Repair",2368.6
|
||||
"5320","Office and Administrative Support",792.5
|
||||
"6720","Construction",271.9
|
||||
"6210","Construction",193.6
|
||||
"3520","Healthcare Practitioners and Technicians",404
|
||||
"7110","Installation, Maintenance, and Repair",182.3
|
||||
"3040","Healthcare Practitioners and Technicians",331.1
|
||||
"6530","Construction",598.9
|
||||
"7950","Production",723.1
|
||||
"8830","Production",345.8
|
||||
"7350","Installation, Maintenance, and Repair",259.3
|
||||
"7700","Production",6384.5
|
||||
"7240","Installation, Maintenance, and Repair",405.6
|
||||
"8930","Production",326.2
|
||||
"500","Business Operations",370.3
|
||||
"700","Business Operations",716.3
|
||||
"5630","Office and Administrative Support",586.3
|
||||
"1700","Life, Physical, and Social Science",172.5
|
||||
"7130","Installation, Maintenance, and Repair",504.4
|
||||
"137","Management",370.3
|
||||
"7710","Production",108.1
|
||||
"8400","Production",60
|
||||
"7900","Production",670.1
|
||||
"5250","Office and Administrative Support",636
|
||||
"900","Financial Specialists",128
|
||||
"6830","Extraction",98.4
|
||||
"7320","Installation, Maintenance, and Repair",404.5
|
||||
"8730","Production",97.2
|
||||
"8310","Production",379.6
|
||||
"1340","Architecture and Engineering",120.3
|
||||
"5920","Office and Administrative Support",202.3
|
||||
"4930","Sales and Related",374.2
|
||||
"5010","Office and Administrative Support",234.2
|
||||
"3750","Protective Service",120.7
|
||||
"7430","Installation, Maintenance, and Repair",522.1
|
||||
"6660","Construction",749.9
|
||||
"7850","Production",144.1
|
||||
"8100","Production",344.8
|
||||
"7540","Installation, Maintenance, and Repair",214.8
|
||||
"6010","Farming, Fishing, and Forestry",201
|
||||
"9415","Transportation and Material Moving",252.6
|
||||
"9310","Transportation and Material Moving",365.9
|
||||
"3850","Protective Service",5540.5
|
||||
"8630","Production",322.5
|
||||
"1600","Life, Physical, and Social Science",336.2
|
||||
"3140","Healthcare Practitioners and Technicians",129
|
||||
"3610","Healthcare Support",163.1
|
||||
"3740","Protective Service",2370.3
|
||||
"1440","Architecture and Engineering",94.1
|
||||
"7510","Installation, Maintenance, and Repair",333.9
|
||||
"360","Management",126.3
|
||||
"6740","Construction",79.2
|
||||
"1930","Life, Physical, and Social Science",204.8
|
||||
"9630","Transportation and Material Moving",212.5
|
||||
"7100","Installation, Maintenance, and Repair",172
|
||||
"4465","Personal Care and Service",255.7
|
||||
"2105","Legal",98.7
|
||||
"7610","Installation, Maintenance, and Repair",153.5
|
||||
"8450","Production",316.2
|
||||
"6300","Construction",130.6
|
||||
"6700","Construction",241.2
|
||||
"8530","Production",221.9
|
||||
"3000","Healthcare Practitioners and Technicians",377.2
|
||||
"8540","Production",214.6
|
||||
"1640","Life, Physical, and Social Science",219.7
|
||||
"330","Management",140.4
|
||||
"5530","Office and Administrative Support",214.2
|
||||
"9240","Transportation and Material Moving",432.3
|
||||
"1450","Architecture and Engineering",297.7
|
||||
"5200","Office and Administrative Support",34.2
|
||||
"9200","Transportation and Material Moving",336.8
|
||||
"9300","Transportation and Material Moving",249.6
|
||||
"8720","Production",273
|
||||
"8610","Production",687.5
|
||||
"8040","Production",199.3
|
||||
"8940","Production",100.4
|
||||
"8256","Production",151.2
|
||||
"3260","Healthcare Practitioners and Technicians",197.2
|
||||
"5340","Office and Administrative Support",186.2
|
||||
"8410","Production",133.1
|
||||
"3900","Protective Service",75.7
|
||||
"1300","Architecture and Engineering",1645.6
|
||||
"9520","Transportation and Material Moving",313
|
||||
"5230","Office and Administrative Support",349.1
|
||||
"425","Management",47.9
|
||||
"8250","Production",262.7
|
||||
"7160","Installation, Maintenance, and Repair",181.3
|
||||
"8330","Production",97.9
|
||||
"7730","Production",131.9
|
||||
"8420","Production",96
|
||||
"7920","Production",112.3
|
||||
"135","Management",174.9
|
||||
"8200","Production",154.4
|
||||
"8510","Production",113.1
|
||||
"9650","Transportation and Material Moving",167.1
|
||||
"8920","Production",322.8
|
||||
"5030","Office and Administrative Support",90.4
|
||||
"9110","Transportation and Material Moving",120.7
|
||||
"6005","Farming, Fishing, and Forestry",429.5
|
||||
"7300","Installation, Maintenance, and Repair",194.5
|
||||
"9560","Transportation and Material Moving",89.8
|
||||
"830","Financial Specialists",227.5
|
||||
"7740","Production",236.9
|
||||
"7550","Installation, Maintenance, and Repair",52.6
|
||||
"8550","Production",225
|
||||
"9410","Transportation and Material Moving",328.1
|
||||
"2740","Arts, Design, Entertainment, Sports, and Media",143.8
|
||||
"5150","Office and Administrative Support",223.8
|
||||
"3250","Healthcare Practitioners and Technicians",648.1
|
||||
"5910","Office and Administrative Support",70.2
|
||||
"1800","Life, Physical, and Social Science",284.1
|
||||
"7940","Production",111.7
|
||||
"8860","Production",65.1
|
||||
"5130","Office and Administrative Support",82.5
|
||||
"8020","Production",11.8
|
||||
"1710","Life, Physical, and Social Science",90.7
|
||||
"3200","Healthcare Practitioners and Technicians",136.9
|
||||
"7560","Installation, Maintenance, and Repair",112.4
|
||||
"1910","Life, Physical, and Social Science",180.4
|
||||
"8910","Production",93.3
|
||||
"6920","Extraction",91.2
|
||||
"8850","Production",63.5
|
||||
"4460","Personal Care and Service",120
|
||||
"8460","Production",209.4
|
||||
"8060","Production",15.8
|
||||
"7030","Installation, Maintenance, and Repair",59
|
||||
"4410","Personal Care and Service",43.5
|
||||
"8010","Production",99.4
|
||||
"6500","Construction",54.3
|
||||
"8340","Production",19.8
|
||||
"7960","Production",16.3
|
||||
"6750","Construction",59.4
|
||||
"7440","Installation, Maintenance, and Repair",4
|
||||
"1500","Architecture and Engineering",98.9
|
||||
"1230","Computer and Mathematical",78.7
|
||||
"7930","Production",15
|
||||
"6540","Construction",9.9
|
||||
"5210","Office and Administrative Support",19
|
||||
"3210","Healthcare Practitioners and Technicians",80.1
|
||||
"3256","Healthcare Practitioners and Technicians",196.9
|
||||
"8210","Production",42.9
|
||||
"3830","Protective Service",6.8
|
||||
"510","Business Operations",121
|
||||
"7050","Installation, Maintenance, and Repair",11.5
|
||||
"9740","Transportation and Material Moving",8.2
|
||||
"9260","Transportation and Material Moving",94.7
|
||||
"1330","Architecture and Engineering",8
|
||||
"4160",NA,6
|
||||
"6020","Farming, Fishing, and Forestry",12
|
||||
"6430","Construction",2.4
|
||||
"325","Management",32.4
|
||||
"3120","Healthcare Practitioners and Technicians",13.3
|
||||
"8900","Production",5.3
|
||||
"3257","Healthcare Practitioners and Technicians",6.1
|
||||
"1830","Life, Physical, and Social Science",3.8
|
||||
"5830","Office and Administrative Support",1.9
|
||||
"6930","Extraction",9.4
|
||||
"9340","Transportation and Material Moving",9.3
|
||||
"9500","Transportation and Material Moving",9.6
|
||||
"1950","Life, Physical, and Social Science",0.8
|
||||
"8120","Production",4.2
|
||||
"1510","Architecture and Engineering",70
|
||||
"9230","Transportation and Material Moving",21.5
|
||||
"8440","Production",5.8
|
||||
"8840","Production",9.5
|
||||
"9330","Transportation and Material Moving",17.8
|
||||
"6910","Extraction",5.7
|
||||
"8360","Production",6.2
|
||||
"7520","Installation, Maintenance, and Repair",1.2
|
||||
"7600","Installation, Maintenance, and Repair",9.1
|
||||
"1815","Life, Physical, and Social Science",12.7
|
||||
|
Whitespace-only changes.
Whitespace-only changes.
Whitespace-only changes.
@@ -0,0 +1,42 @@
|
||||
|
||||
#
|
||||
# Load data
|
||||
#
|
||||
|
||||
players <- read.csv("data/nba-top50scorers-2022-23.csv")
|
||||
head(players)
|
||||
|
||||
play20 <- players[1:20,]
|
||||
|
||||
#
|
||||
# Heatmap
|
||||
#
|
||||
|
||||
# Four columns
|
||||
heatmap(as.matrix(play20[,c("MP", "FG", "FGpct", "PTS")]),
|
||||
scale = "column",
|
||||
Rowv = NA, Colv = NA)
|
||||
|
||||
# Names
|
||||
heatmap(as.matrix(play20[,c("MP", "FG", "FGpct", "PTS")]),
|
||||
scale = "column",
|
||||
labRow = play20$Player,
|
||||
Rowv = NA, Colv = NA)
|
||||
|
||||
# Change order
|
||||
playrev <- play20[order(play20$PTS, decreasing = FALSE),]
|
||||
heatmap(as.matrix(playrev[,c("MP", "FG", "FGpct", "PTS")]),
|
||||
scale = "column",
|
||||
labRow = playrev$Player,
|
||||
Rowv = NA, Colv = NA)
|
||||
|
||||
|
||||
# Color
|
||||
playrev <- play20[order(play20$PTS, decreasing = FALSE),]
|
||||
heatmap(as.matrix(playrev[,c("MP", "FG", "FGpct", "X2Ppct", "X3Ppct", "FTpct", "PTS")]),
|
||||
scale = "column",
|
||||
labRow = playrev$Player,
|
||||
cexCol = 1,
|
||||
col = rev(hcl.colors(20, palette = "Blues 3")),
|
||||
Rowv = NA, Colv = NA)
|
||||
|
||||
@@ -0,0 +1,98 @@
|
||||
# install.packages("igraph")
|
||||
library(igraph)
|
||||
|
||||
# Empty graph
|
||||
g <- make_empty_graph(directed=FALSE)
|
||||
|
||||
#
|
||||
# Add vertices
|
||||
#
|
||||
|
||||
g <- g %>% add_vertices(1, color="#a3b8a3", size=50)
|
||||
g <- g %>% add_vertices(1, color = "#d7c668", size=50)
|
||||
g <- g %>% add_vertices(10, color = "#cccccc", size=20)
|
||||
plot(g)
|
||||
|
||||
|
||||
|
||||
#
|
||||
# Add edges (to connect vertices)
|
||||
#
|
||||
|
||||
# Connect the two first vertices
|
||||
g <- g %>% add_edges(c(1,2), weight=0.01, color="#cccccc")
|
||||
plot(g)
|
||||
|
||||
# Connect 8 to 10 and 7
|
||||
g <- g %>% add_edges(c(8,10, 8,7), weight=0.01, color="#cccccc")
|
||||
plot(g)
|
||||
|
||||
# Connect 3, 4, and 5 to 1
|
||||
g <- g %>% add_edges(c(3,1, 4,1, 5,1), weight=0.01, color="#cccccc")
|
||||
plot(g)
|
||||
|
||||
# Connect 11 and 12 to 2 with more weight
|
||||
g <- g %>% add_edges(c(12,2, 11,2), weight=1, color="#cccccc")
|
||||
plot(g)
|
||||
|
||||
# Layouts
|
||||
par(mfrow=c(2,2), mar=c(2,0,4,0))
|
||||
plot(g, vertex.label=NA, layout=layout_with_fr, main="Force-directed")
|
||||
plot(g, vertex.label=NA, layout=layout_on_grid, main="Grid")
|
||||
plot(g, vertex.label=NA, layout=layout_in_circle, main="Circle")
|
||||
plot(g, vertex.label=NA, layout=layout_nicely, main="Nicely")
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
#
|
||||
# Example with more data: Job Switching Network
|
||||
#
|
||||
|
||||
# Load data
|
||||
occs <- read.csv("data/occ_codes.tsv", sep="\t")
|
||||
occverts <- read.csv("data/occverts.csv")
|
||||
occlinks <- read.csv("data/occlinks.csv")
|
||||
occgrps <- unique(occverts$grp)
|
||||
|
||||
head(occverts)
|
||||
head(occlinks)
|
||||
|
||||
# Subsetting and weights
|
||||
occlinks$relwt <- occlinks$value / max(occlinks$value)
|
||||
occlinks_sub <- occlinks[occlinks$relwt >= .01,]
|
||||
occverts_sub <- occverts[occverts$id %in% occlinks_sub$source | occverts$id %in% occlinks_sub$target,]
|
||||
|
||||
# Vertices colors
|
||||
occverts_sub$color <- colors()[match(occverts_sub$grp, occgrps)*2]
|
||||
|
||||
# Form the graph
|
||||
g <- make_empty_graph(directed=FALSE)
|
||||
g <- g %>%
|
||||
add_vertices(dim(occverts_sub)[1], color=occverts_sub$color, size=sqrt(occverts_sub$nwt)/10) %>%
|
||||
set_vertex_attr("occid", value = occverts_sub$id) %>%
|
||||
set_vertex_attr("grp", value = occverts_sub$grp)
|
||||
|
||||
# Get id of added vertices
|
||||
occverts_sub$vid <- match(occverts_sub$id, V(g)$occid)
|
||||
occverts_sub$name <- occs$name[match(occverts_sub$id, occs$code)]
|
||||
g <- g %>% set_vertex_attr("name", value = occverts_sub$name)
|
||||
|
||||
# Join ids
|
||||
occlinks_sub$vid_source <- occverts_sub$vid[match(occlinks_sub$source, occverts_sub$id)]
|
||||
occlinks_sub$vid_target <- occverts_sub$vid[match(occlinks_sub$target, occverts_sub$id)]
|
||||
|
||||
# Add edges
|
||||
for (i in 1:dim(occlinks_sub)[1]) {
|
||||
g <- g %>% add_edges(c(occlinks_sub$vid_source[i], occlinks_sub$vid_target[i]),
|
||||
weight=occlinks_sub$relwt[i]*20,
|
||||
color="#f0f0f0")
|
||||
}
|
||||
|
||||
# Plot
|
||||
plot(g, vertex.label = NA)
|
||||
|
||||
|
||||
@@ -0,0 +1,40 @@
|
||||
# install.packages("MASS")
|
||||
library(MASS)
|
||||
|
||||
|
||||
#
|
||||
# Load data
|
||||
#
|
||||
|
||||
players <- read.csv("data/nba-top50scorers-2022-23.csv")
|
||||
head(players)
|
||||
|
||||
|
||||
#
|
||||
# Parallel coordinates
|
||||
#
|
||||
|
||||
fnames <- c("MP", "FG", "FGpct", "X2Ppct", "X3Ppct", "FTpct", "PTS")
|
||||
psub <- players[,fnames]
|
||||
|
||||
# Parallel coordinates
|
||||
parcoord(psub)
|
||||
|
||||
# Pick out player
|
||||
curr_players <- c("Joel Embiid", "Giannis Antetokounmpo",
|
||||
"Stephen Curry", "LeBron James")
|
||||
par(mfrow=c(2,2))
|
||||
for (pl in curr_players) {
|
||||
col <- rep("gray", dim(players)[1])
|
||||
lwd <- rep(.5, dim(players)[1])
|
||||
i <- which(players$Player == pl)
|
||||
col[i] <- "blue"
|
||||
lwd[i] <- 3
|
||||
parcoord(psub, col=col, lwd=lwd, main=pl)
|
||||
}
|
||||
|
||||
|
||||
|
||||
# Scatterplot Matrix
|
||||
par(las=1)
|
||||
plot(psub)
|
||||
@@ -0,0 +1,16 @@
|
||||
"code" "pctnokidsf" "pctkidsf" "pctnokidsm" "pctkidsm" "desc" "durmedkidsf" "durmednokidsf" "durmedkidsm" "durmednokidsm"
|
||||
30201 0.2 20.7 0.2 10.3 "Homework" 45 0 45 0
|
||||
30101 0.9 71.2 0.6 46.8 "Physical care" 50 0 31 0
|
||||
30103 0.8 21.6 0.3 21.4 "Playing, not sports" 70 0 60 0
|
||||
30112 0.9 48 0.3 27.2 "Picking up/dropping off" 10 0 10 0
|
||||
30102 0.2 14.5 0 9.1 "Reading to/with" 20 0 20 0
|
||||
30302 0.1 3 0 0.6 "Obtaining medical care" 60 0 50 0
|
||||
30301 0.1 3 0 0.8 "Providing medical care" 15 0 30 0
|
||||
30111 0.2 11.7 0.2 4.9 "Waiting for/with" 15 0 15 0
|
||||
30202 0 1.7 0 0.5 "Meetings and school conferences" 25 0 30 0
|
||||
30106 0.3 13.8 0.2 5.7 "Talking with/listening" 25 0 25 0
|
||||
30110 0.1 4.8 0 2.6 "Attending events" 71 0 85 0
|
||||
30109 0.3 12.1 0.1 5.1 "Looking after (as a pri. activity)" 40 0 45 0
|
||||
30105 0 1.3 0 1 "Playing sports" 43 0 60 0
|
||||
30108 0 6.4 0 1.6 "Organization and planning" 10 0 15 0
|
||||
30303 0.1 1.4 0 0.3 "Waiting for children's health" 20 0 30 0
|
||||
|
@@ -0,0 +1,14 @@
|
||||
<!DOCTYPE html>
|
||||
<head>
|
||||
<meta charset="utf-8">
|
||||
<title>Who Takes Care of the Kids</title>
|
||||
<link rel="stylesheet" href="style/style.css" type="text/css" media="screen" />
|
||||
</head>
|
||||
|
||||
<div id="main-wrapper">
|
||||
<h1>Time with the Kids</h1>
|
||||
<div id="chart"></div>
|
||||
</div>
|
||||
|
||||
<script src="js/d3.v7.min.js"></script>
|
||||
<script src="js/barbell.js"></script>
|
||||
@@ -0,0 +1,114 @@
|
||||
// Dimensions of chart.
|
||||
let margin = { top: 20, right: 20, bottom: 50, left: 290 },
|
||||
// width = parseInt(d3.select('#chart').style('width'), 10) - margin.left - margin.right,
|
||||
width = 650 - margin.left - margin.right,
|
||||
height = 550 - margin.top - margin.bottom;
|
||||
|
||||
// Start SVG
|
||||
let svg = d3.select("#chart").append("svg")
|
||||
.attr("width", width + margin.left + margin.right)
|
||||
.attr("height", height + margin.top + margin.bottom)
|
||||
.append("g")
|
||||
.attr("transform", "translate(" + margin.left + "," + margin.top + ")");
|
||||
|
||||
// Scales: x and y
|
||||
let x = d3.scaleLinear()
|
||||
.domain([0, 80])
|
||||
.range([0, width]);
|
||||
let y = d3.scaleBand()
|
||||
// .domain([3, 6])
|
||||
.range([height, 0]);
|
||||
|
||||
|
||||
let activities;
|
||||
let xAxis, yAxis, xAxisEl, yAxisEl;
|
||||
let barbell;
|
||||
|
||||
|
||||
// Load data
|
||||
const activitiesData = Promise.all([
|
||||
d3.tsv("data/hh-activities-withkids.tsv", d3.autoType)
|
||||
]);
|
||||
activitiesData.then(function(data) {
|
||||
activities = data[0].sort((a, b) => a.pctkidsf - b.pctkidsf);
|
||||
// console.log(activities);
|
||||
|
||||
// Initialize chart now that data is loaded.
|
||||
initChart();
|
||||
});
|
||||
|
||||
|
||||
function initChart() {
|
||||
|
||||
// x-axis
|
||||
xAxis = d3.axisBottom(x)
|
||||
.tickFormat(d => d + "%")
|
||||
.ticks(5)
|
||||
.tickSize(-height-8)
|
||||
.tickPadding(5);
|
||||
xAxisEl = svg.append("g")
|
||||
.attr("class", "x axis bottom")
|
||||
.attr("transform", "translate(0,"+(height+8)+")");
|
||||
xAxisEl.append("text")
|
||||
.attr("class", "axistitle")
|
||||
.attr("text-anchor", "start")
|
||||
.attr("x", 0).attr("y", 0)
|
||||
.attr("dx", "-.75em").attr("dy", "2.5em")
|
||||
.text("Engaged in Activity");
|
||||
xAxisEl.call(xAxis);
|
||||
|
||||
|
||||
// y-axis
|
||||
y.domain(activities.map(d => d.desc));
|
||||
yAxis = d3.axisLeft(y)
|
||||
.tickSize(0);
|
||||
yAxisEl = svg.append("g")
|
||||
.attr("class", "y axis left")
|
||||
.attr("transform", "translate("+(-8)+",0)");
|
||||
yAxisEl.call(yAxis);
|
||||
|
||||
|
||||
// barbells
|
||||
barbell = svg.selectAll(".barbell")
|
||||
.data(activities)
|
||||
.join("g")
|
||||
.attr("class", "barbell")
|
||||
.attr("transform", d =>
|
||||
"translate(0,"+(y(d.desc)+(y.bandwidth()/2))+")")
|
||||
.attr("id", d => "act"+d.code);
|
||||
|
||||
// connecting lines
|
||||
barbell.append("line")
|
||||
.attr("x1", d => x(d.pctkidsm))
|
||||
.attr("x2", d => x(d.pctkidsf))
|
||||
.attr("y1", 0).attr("y2", 0)
|
||||
.attr("stroke", "#000000");
|
||||
|
||||
// circles
|
||||
barbell.append("circle")
|
||||
.attr("class", "men")
|
||||
.attr("cx", d => x(d.pctkidsm))
|
||||
.attr("cy", 0)
|
||||
.attr("r", 6);
|
||||
barbell.append("circle")
|
||||
.attr("class", "women")
|
||||
.attr("cx", d => x(d.pctkidsf))
|
||||
.attr("cy", 0)
|
||||
.attr("r", 6);
|
||||
|
||||
// labels
|
||||
svg.append("text")
|
||||
.attr("x", x(activities[14].pctkidsm))
|
||||
.attr("y", y(activities[14].desc))
|
||||
.attr("text-anchor", "middle")
|
||||
.text("MEN");
|
||||
svg.append("text")
|
||||
.attr("x", x(activities[14].pctkidsf))
|
||||
.attr("y", y(activities[14].desc))
|
||||
.attr("text-anchor", "middle")
|
||||
.text("WOMEN");
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
@@ -0,0 +1,2 @@
|
||||
// https://d3js.org v7.4.0 Copyright 2010-2022 Mike Bostock
|
||||
!function(t,n){"object"==typeof exports&&"undefined"!=typeof module?n(exports):"function"==typeof define&&define.amd?define(["exports"],n):n((t="undefined"!=typeof globalThis?globalThis:t||self).d3=t.d3||{})}(this,(function(t){"use strict";function n(t,n){return null==t||null==n?NaN:t<n?-1:t>n?1:t>=n?0:NaN}function e(t){let e=t,r=t,i=t;function o(t,n,e=0,o=t.length){if(e<o){if(0!==r(n,n))return o;do{const r=e+o>>>1;i(t[r],n)<0?e=r+1:o=r}while(e<o)}return e}return 2!==t.length&&(e=(n,e)=>t(n)-e,r=n,i=(e,r)=>n(t(e),r)),{left:o,center:function(t,n,r=0,i=t.length){const a=o(t,n,r,i-1);return a>r&&e(t[a-1],n)>-e(t[a],n)?a-1:a},right:function(t,n,e=0,o=t.length){if(e<o){if(0!==r(n,n))return o;do{const r=e+o>>>1;i(t[r],n)<=0?e=r+1:o=r}while(e<o)}return e}}}function r(t){return null===t?NaN:+t}const i=e(n),o=i.right,a=i.left,u=e(r).center;var c=o;function f(t,n){let e=0;if(void 0===n)for(let n of t)null!=n&&(n=+n)>=n&&++e;else{let r=-1;for(let i of t)null!=(i=n(i,++r,t))&&(i=+i)>=i&&++e}return e}function s(t){return 0|t.length}function l(t){return!(t>0)}function h(t){return"object"!=typeof t||"length"in t?t:Array.from(t)}function d(t,n){let e,r=0,i=0,o=0;if(void 0===n)for(let n of t)null!=n&&(n=+n)>=n&&(e=n-i,i+=e/++r,o+=e*(n-i));else{let a=-1;for(let u of t)null!=(u=n(u,++a,t))&&(u=+u)>=u&&(e=u-i,i+=e/++r,o+=e*(u-i))}if(r>1)return o/(r-1)}function p(t,n){const e=d(t,n);return e?Math.sqrt(e):e}function g(t,n){let e,r;if(void 0===n)for(const n of t)null!=n&&(void 0===e?n>=n&&(e=r=n):(e>n&&(e=n),r<n&&(r=n)));else{let i=-1;for(let o of t)null!=(o=n(o,++i,t))&&(void 0===e?o>=o&&(e=r=o):(e>o&&(e=o),r<o&&(r=o)))}return[e,r]}class y{constructor(){this._partials=new Float64Array(32),this._n=0}add(t){const n=this._partials;let e=0;for(let r=0;r<this._n&&r<32;r++){const i=n[r],o=t+i,a=Math.abs(t)<Math.abs(i)?t-(o-i):i-(o-t);a&&(n[e++]=a),t=o}return n[e]=t,this._n=e+1,this}valueOf(){const t=this._partials;let n,e,r,i=this._n,o=0;if(i>0){for(o=t[--i];i>0&&(n=o,e=t[--i],o=n+e,r=e-(o-n),!r););i>0&&(r<0&&t[i-1]<0||r>0&&t[i-1]>0)&&(e=2*r,n=o+e,e==n-o&&(o=n))}return o}}class InternMap extends Map{constructor(t,n=m){if(super(),Object.defineProperties(this,{_intern:{value:new Map},_key:{value:n}}),null!=t)for(const[n,e]of t)this.set(n,e)}get(t){return super.get(v(this,t))}has(t){return super.has(v(this,t))}set(t,n){return super.set(_(this,t),n)}delete(t){return super.delete(b(this,t))}}class InternSet extends Set{constructor(t,n=m){if(super(),Object.defineProperties(this,{_intern:{value:new Map},_key:{value:n}}),null!=t)for(const n of t)this.add(n)}has(t){return super.has(v(this,t))}add(t){return super.add(_(this,t))}delete(t){return super.delete(b(this,t))}}function v({_intern:t,_key:n},e){const r=n(e);return t.has(r)?t.get(r):e}function _({_intern:t,_key:n},e){const r=n(e);return t.has(r)?t.get(r):(t.set(r,e),e)}function b({_intern:t,_key:n},e){const r=n(e);return t.has(r)&&(e=t.get(r),t.delete(r)),e}function m(t){return null!==t&&"object"==typeof t?t.valueOf():t}function x(t){return t}function w(t,...n){return k(t,x,x,n)}function M(t,...n){return k(t,Array.from,x,n)}function A(t,n){for(let e=1,r=n.length;e<r;++e)t=t.flatMap((t=>t.pop().map((([n,e])=>[...t,n,e]))));return t}function T(t,n,...e){return k(t,x,n,e)}function S(t,n,...e){return k(t,Array.from,n,e)}function E(t){if(1!==t.length)throw new Error("duplicate key");return t[0]}function k(t,n,e,r){return function t(i,o){if(o>=r.length)return e(i);const a=new InternMap,u=r[o++];let c=-1;for(const t of i){const n=u(t,++c,i),e=a.get(n);e?e.push(t):a.set(n,[t])}for(const[n,e]of a)a.set(n,t(e,o));return n(a)}(t,0)}function N(t,n){return Array.from(n,(n=>t[n]))}function C(t,...n){if("function"!=typeof t[Symbol.iterator])throw new TypeError("values is not iterable");t=Array.from(t);let[e]=n;if(e&&2!==e.length||n.length>1){const r=Uint32Array.from(t,((t,n)=>n));return n.length>1?(n=n.map((n=>t.map(n))),r.sort(((t,e)=>{for(const r of n){const n=z(r[t],r[e]);if(n)return n}}))):(e=t.map(e),r.sort(((t,n)=>z(e[t],e[n])))),N(t,r)}return t.sort(P(e))}function P(t=n){if(t===n)return z;if("function"!=typeof t)throw new TypeError("compare is not a function");return(n,e)=>{const r=t(n,e);return r||0===r?r:(0===t(e,e))-(0===t(n,n))}}function z(t,n){return(null==t||!(t>=t))-(null==n||!(n>=n))||(t<n?-1:t>n?1:0)}var D=Array.prototype.slice;function R(t){return()=>t}var F=Math.sqrt(50),q=Math.sqrt(10),O=Math.sqrt(2);function U(t,n,e){var r,i,o,a,u=-1;if(e=+e,(t=+t)===(n=+n)&&e>0)return[t];if((r=n<t)&&(i=t,t=n,n=i),0===(a=I(t,n,e))||!isFinite(a))return[];if(a>0){let e=Math.round(t/a),r=Math.round(n/a);for(e*a<t&&++e,r*a>n&&--r,o=new Array(i=r-e+1);++u<i;)o[u]=(e+u)*a}else{a=-a;let e=Math.round(t*a),r=Math.round(n*a);for(e/a<t&&++e,r/a>n&&--r,o=new Array(i=r-e+1);++u<i;)o[u]=(e+u)/a}return r&&o.reverse(),o}function I(t,n,e){var r=(n-t)/Math.max(0,e),i=Math.floor(Math.log(r)/Math.LN10),o=r/Math.pow(10,i);return i>=0?(o>=F?10:o>=q?5:o>=O?2:1)*Math.pow(10,i):-Math.pow(10,-i)/(o>=F?10:o>=q?5:o>=O?2:1)}funLine truncated
|
||||
@@ -0,0 +1,91 @@
|
||||
/* #Reset & Basics (Inspired by E. Meyers)
|
||||
================================================== */
|
||||
html, body, div, span, applet, object, iframe, h1, h2, h3, h4, h5, h6, p, blockquote, pre, a, abbr, acronym, address, big, cite, code, del, dfn, em, img, ins, kbd, q, s, samp, small, strike, strong, sub, sup, tt, var, b, u, i, center, dl, dt, dd, ol, ul, li, fieldset, form, label, legend, table, caption, tbody, tfoot, thead, tr, th, td, article, aside, canvas, details, embed, figure, figcaption, footer, header, hgroup, menu, nav, output, ruby, section, summary, time, mark, audio, video {
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
border: 0;
|
||||
font-size: 100%;
|
||||
font: inherit;
|
||||
vertical-align: baseline; }
|
||||
article, aside, details, figcaption, figure, footer, header, hgroup, menu, nav, section {
|
||||
display: block; }
|
||||
body {
|
||||
line-height: 1; }
|
||||
ol, ul {
|
||||
list-style: none; }
|
||||
blockquote, q {
|
||||
quotes: none; }
|
||||
blockquote:before, blockquote:after,
|
||||
q:before, q:after {
|
||||
content: '';
|
||||
content: none; }
|
||||
table {
|
||||
border-collapse: collapse;
|
||||
border-spacing: 0; }
|
||||
|
||||
|
||||
/* Main layout
|
||||
============================ */
|
||||
|
||||
#main-wrapper {
|
||||
width: 600px;
|
||||
margin: 40px auto;
|
||||
font-family: Georgia, serif;
|
||||
}
|
||||
h1 {
|
||||
font-family: Georgia, serif;
|
||||
font-size: 1.45em;
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
|
||||
/* Chart
|
||||
============================ */
|
||||
|
||||
#chart {
|
||||
position: relative;
|
||||
margin: 0 auto;
|
||||
}
|
||||
text {
|
||||
font-family: "Courier New", Courier, monospace;
|
||||
font-size: .8rem;
|
||||
}
|
||||
|
||||
.axis .axistitle {
|
||||
text-transform: uppercase;
|
||||
fill: #333;
|
||||
font-size: .8rem;
|
||||
}
|
||||
.axis path,
|
||||
.axis line {
|
||||
fill: none;
|
||||
stroke: #e0e0e0;
|
||||
stroke-width: .5px;
|
||||
shape-rendering: crispEdges;
|
||||
}
|
||||
.x.axis path, .y.axis path {
|
||||
display: none;
|
||||
}
|
||||
.barbell line {
|
||||
stroke-width: 1px;
|
||||
}
|
||||
.barbell circle {
|
||||
stroke: #000;
|
||||
stroke-width: 1px;
|
||||
}
|
||||
.barbell circle.men {
|
||||
fill: #317e7f;
|
||||
}
|
||||
.barbell circle.women {
|
||||
fill: #f98e1a;
|
||||
}
|
||||
|
||||
|
||||
/* Interaction
|
||||
============================ */
|
||||
|
||||
circle.current {
|
||||
stroke: #000;
|
||||
stroke-width: 3px;
|
||||
}
|
||||
|
||||
@@ -0,0 +1,292 @@
|
||||
"activity" "schappy_mean" "meaning_mean" "descrip" "relwt"
|
||||
"010301" 3.65 5.2875 "Health-related self care" 0.3437
|
||||
"010399" 0.4441 4.332 "Self care, misc." 0.0022
|
||||
"020101" 4.3016 5.0383 "Interior cleaning" 1.362
|
||||
"020102" 4.1979 4.866 "Laundry" 0.806
|
||||
"020103" 4.8934 5.4284 "Sewing, repairing, and maintaining textiles" 0.076
|
||||
"020104" 4.5711 4.8468 "Storing interior household items, inc. food" 0.2002
|
||||
"020201" 4.6729 5.1604 "Food and drink prep." 3.8685
|
||||
"020202" 4.9016 5.5208 "Food presentation" 0.0659
|
||||
"020203" 4.3252 4.9249 "Kitchen and food clean-up" 0.9425
|
||||
"020301" 4.5569 5.2724 "Interior arrangement, decoration, and repairs" 0.1527
|
||||
"020302" 4.7587 4.8901 "Building and repairing furniture" 0.0073
|
||||
"020303" 4.2926 5.29 "Heating and cooling" 0.0446
|
||||
"020401" 4.1507 5.0967 "Exterior cleaning" 0.1179
|
||||
"020402" 4.8953 5.3774 "Exterior repair, improvements, and decoration" 0.0696
|
||||
"020501" 4.6695 5.2066 "Lawn, garden, and houseplant care" 0.6958
|
||||
"020502" 4.0334 5.083 "Ponds, pools, and hot tubs" 0.0143
|
||||
"020602" 4.591 5.3077 "Care for animals and pets" 0.6464
|
||||
"020603" 4.9233 5.2797 "Walking, exercising, playing with animals" 0.4182
|
||||
"020699" 4.4816 4.6297 "Pet and animal care, misc." 0.0032
|
||||
"020701" 4.3308 5.1412 "Vehicle repair and maintenance (by self)" 0.14
|
||||
"020801" 4.3562 5.1824 "App, tool, toy set-up, repair, and maint (by self)" 0.0589
|
||||
"020901" 3.715 4.999 "Financial management" 0.1445
|
||||
"020902" 4.386 4.9614 "Household and personal organization" 0.6869
|
||||
"020903" 4.3574 4.8634 "Household and personal mail and messages (except e-mail)" 0.1483
|
||||
"020904" 4.1977 4.3381 "Household and personal e-mail and messages" 0.2182
|
||||
"020905" 4.0463 4.9778 "Home security" 0.023
|
||||
"029999" 4.4219 4.895 "Household activities, misc." 0.0023
|
||||
"030101" 4.8037 5.4819 "Care for household children" 1.7066
|
||||
"030102" 5.3559 5.7285 "Reading to/with household children" 0.1706
|
||||
"030103" 5.5047 5.7429 "Playing with household children" 0.5338
|
||||
"030104" 5.4589 5.6239 "Arts and crafts with household children" 0.0131
|
||||
"030105" 5.3366 5.712 "Playing sports with household children" 0.0246
|
||||
"030106" 4.997 5.5712 "Talking with/listening to household children" 0.1503
|
||||
"030108" 4.4771 5.0912 "Organization for household children" 0.0445
|
||||
"030109" 5.0333 5.5065 "Looking after household children" 0.1501
|
||||
"030110" 5.0778 5.615 "Attending household children's events" 0.0925
|
||||
"030111" 4.7433 5.3825 "Waiting for/with household children" 0.0482
|
||||
"030112" 4.7327 5.3525 "Picking up/dropping off household children" 0.3373
|
||||
"030199" 5.0626 5.4164 "Caring for and helping household children, misc." 0.0058
|
||||
"030201" 4.5065 5.5892 "Homework (household children)" 0.1711
|
||||
"030202" 4.062 5.6243 "Meetings and school conferences (household children)" 0.0058
|
||||
"030203" 5.0198 5.808 "Home schooling of household children" 0.0062
|
||||
"030299" 3.4516 5.3227 "Activities related to household child's education, misc." 0.0037
|
||||
"030301" 3.2966 5.5604 "Providing medical care to household children" 0.0218
|
||||
"030302" 3.484 5.545 "Obtaining medical care for household children" 0.0127
|
||||
"030303" 2.7979 5.6905 "Waiting associated with household children's health" 0.0101
|
||||
"030401" 4.3313 5.5832 "Care for household adults" 0.0634
|
||||
"030402" 4.6669 5.0003 "Looking after household adult (as a primary activity)" 0.0043
|
||||
"030403" 3.7147 5.525 "Providing medical care to household adult" 0.021
|
||||
"030404" 4.71 5.7405 "Obtaining medical and care services for household adult" 0.0075
|
||||
"030405" 4.234 5.476 "Waiting associated with caring for household adults" 0.006
|
||||
"030501" 4.3418 5.0822 "Helping household adults" 0.0088
|
||||
"030502" 3.9261 5.5183 "Organization and planning for household adults" 0.0032
|
||||
"030503" 4.6838 5.0713 "Picking up/dropping off household adult" 0.0368
|
||||
"030504" 4.8728 5.4733 "Waiting associated with helping household adults" 0.0247
|
||||
"030599" 4.7353 5.1179 "Helping household adults, misc." 0.0041
|
||||
"040101" 5.3144 5.6892 "Care for non-household children" 0.0835
|
||||
"040102" 5.632 5.8949 "Reading to/with non-household children" 0.0091
|
||||
"040103" 5.7316 5.8642 "Playing with non-household children" 0.116
|
||||
"040105" 4.7162 6 "Playing sports with non-household children" 0.005
|
||||
"040106" 5.632 5.8326 "Talking with/listening to non-household children" 0.0251
|
||||
"040108" 4.6278 5.5581 "Organization and planning for non-household children" 0.0052
|
||||
"040109" 5.3345 5.8355 "Looking after non-household children (as primary activity)" 0.033
|
||||
"040110" 5.5768 5.7883 "Attending non-household children's events" 0.0165
|
||||
"040111" 5.1291 5.322 "Waiting for/with non-household children" 0.0074
|
||||
"040112" 5.0798 5.5207 "Dropping off/picking up non-household children" 0.0691
|
||||
"040199" 5.5774 5.7106 "Caring for and helping non-household children, misc." 0.0054
|
||||
"040201" 4.8287 5.8439 "Homework (non-household children)" 0.0077
|
||||
"040401" 4.5175 5.6303 "Care for non-household adults" 0.0244
|
||||
"040402" 3.6183 5.4763 "Looking after non-household adult" 0.005
|
||||
"040403" 4.3324 5.7824 "Providing medical care to non-household adult" 0.0083
|
||||
"040404" 3.697 5.7815 "Obtaining medical and care svcs for non-household adult" 0.0028
|
||||
"040405" 3.8136 5.5421 "Waiting associated with caring for non-household adults" 0.0045
|
||||
"040501" 4.7363 5.3113 "Hswrk, cooking, and shopping asst, non-household adults" 0.0447
|
||||
"040502" 4.6688 5.368 "House and lawn maint and repair asst, non-household adults" 0.0436
|
||||
"040503" 5.3119 4.9995 "Animal and pet care assistance for non-household adults" 0.0134
|
||||
"040504" 4.5605 5.2475 "Vehicle/appliance maint/repair asst, non-household adults" 0.0201
|
||||
"040505" 4.4638 4.9507 "Financial mgmt asst for non-household adults" 0.0049
|
||||
"040506" 4.1688 5.3376 "household mgmt and paperwork asst, non-household adults" 0.0255
|
||||
"040507" 4.9319 5.3192 "Picking up/dropping off non-household adult" 0.1284
|
||||
"040508" 4.2182 5.2695 "Waiting associated with helping non-household adults" 0.023
|
||||
"040599" 4.3443 5.2868 "Helping non-household adults, misc." 0.015
|
||||
"050101" 4.2106 5.0372 "Work, main job" 3.8671
|
||||
"050102" 4.2169 5.0135 "Work, other job(s)" 0.1346
|
||||
"050104" 4.1585 4.952 "Waiting associated with working" 0.0258
|
||||
"050199" 3.502 3.8063 "Working, misc." 0.0012
|
||||
"050201" 4.8683 4.8224 "Socializing, relaxing, and leisure as part of job" 0.0028
|
||||
"050202" 4.6143 4.9853 "Eating and drinking as part of job" 0.0178
|
||||
"050301" 5.1982 5.486 "Income-generating hobbies, crafts, and food" 0.0079
|
||||
"050303" 4.7095 4.9767 "Income-generating services" 0.0307
|
||||
"050304" 3.7731 5.3123 "Income-generating rental property activities" 0.0053
|
||||
"050399" 4.5872 5.2503 "Other income-generating activities, misc." 0.0391
|
||||
"050401" 3.4136 5.4454 "Job search activities" 0.1018
|
||||
"050403" 4.4473 5.6315 "Job interviewing" 0.0046
|
||||
"060101" 4.0938 4.9396 "Taking class for degree, certification, or lic" 0.1708
|
||||
"060102" 4.8102 5.4599 "Taking class for personal interest" 0.0199
|
||||
"060103" 3.7852 5.4278 "Waiting associated with taking classes" 0.005
|
||||
"060201" 5.3468 5.7823 "Extracurricular club activities" 0.0028
|
||||
"060202" 4.7063 5.0467 "Extracurricular music and performance activities" 0.0049
|
||||
"060299" 4.8569 3.7138 "Education-related extracurricular activities, misc." 0.0017
|
||||
"060301" 3.3418 4.9021 "Homework for class, for degree" 0.2883
|
||||
"060302" 4.9457 5.6787 "Homework for class, for personal interest" 0.0067
|
||||
"060399" 3.0733 4.7988 "Research/homework misc." 0.0048
|
||||
"060401" 5.1 5.8001 "Admin activities: class for degree, cert, or lic" 0.0048
|
||||
"069999" 3.8977 5.3269 "Education, misc." 0.0103
|
||||
"070101" 4.3286 4.8367 "Grocery shopping" 0.5658
|
||||
"070102" 4.2173 4.872 "Purchasing gas" 0.0943
|
||||
"070103" 4.6715 4.8424 "Purchasing food (not groceries)" 0.3922
|
||||
"070104" 4.6217 4.9111 "Shopping" 1.0884
|
||||
"070105" 3.8775 5.1629 "Waiting associated with shopping" 0.0118
|
||||
"070201" 4.6118 4.9319 "Comparison shopping" 0.0037
|
||||
"080101" 5.0985 5.5574 "Using paid childcare services" 0.0073
|
||||
"080201" 4.2378 4.9952 "Banking" 0.0579
|
||||
"080202" 4.6522 5.3043 "Using other financial services" 0.0055
|
||||
"080203" 4.5258 5.3144 "Waiting associated w/banking/financial services" 0.0023
|
||||
"080401" 3.5839 5.4735 "Using health and care services outside the home" 0.1335
|
||||
"080402" 3.5935 4.8952 "Using in-home health and care services" 0.0068
|
||||
"080403" 3.3676 5.2215 "Waiting associated with medical services" 0.031
|
||||
"080501" 4.8617 5.0354 "Using personal care services" 0.0583
|
||||
"080502" 4.809 3.6661 "Waiting associated w/personal care services" 0.0025
|
||||
"080601" 3.9619 5.0571 "Activities rel. to purchasing/selling real estate" 0.0125
|
||||
"080701" 3.0977 5.7036 "Using veterinary services" 0.0085
|
||||
"080702" 4.4371 5.4764 "Waiting associated with veterinary services" 0.003
|
||||
"089999" 4.8267 5.1165 "Professional and personal services, misc." 0.0083
|
||||
"090103" 4.9078 5.18 "Using clothing repair and cleaning services" 0.0066
|
||||
"090201" 4.0885 5.0779 "Using home maint/repair/décor/construction svcs" 0.0121
|
||||
"090202" 4.866 5.2007 "Wtg assoc w/ home main/repair/décor/constr" 0.0058
|
||||
"090301" 4.139 4.4996 "Using pet services" 0.0043
|
||||
"090401" 5.0353 5.5002 "Using lawn and garden services" 0.0034
|
||||
"090501" 3.5476 4.8717 "Using vehicle maintenance or repair services" 0.021
|
||||
"090502" 4.4548 4.9964 "Waiting assoc with vehicle main. or repair svcs" 0.0087
|
||||
"100102" 4.036 5.3569 "Using social services" 0.0034
|
||||
"100103" 3.6129 5.5428 "Obtaining licenses and paying fines, fees, taxes" 0.0071
|
||||
"100201" 3.8247 5.8242 "Civic obligations and participation" 0.0055
|
||||
"100304" 4.2609 4.9115 "Waiting associated with using government services" 0.0028
|
||||
"110101" 4.8524 5.1731 "Eating and drinking" 10
|
||||
"110201" 4.6021 4.9123 "Waiting associated w/eating and drinking" 0.0332
|
||||
"120101" 5.0809 5.424 "Socializing and communicating" 2.5822
|
||||
"120201" 5.4271 5.486 "Attending or hosting parties/receptions/ceremonies" 0.164
|
||||
"120202" 4.4307 5.3018 "Attending meetings for personal interest (not volunteering)" 0.0262
|
||||
"120301" 4.6856 5.1863 "Relaxing, thinking" 1.0886
|
||||
"120302" 4.5497 5.0903 "Tobacco and drug use" 0.0602
|
||||
"120303" 4.634 4.7545 "Television and movies" 5.058
|
||||
"120304" 4.6446 5.4465 "Television (religious)" 0.0193
|
||||
"120305" 4.5594 5.1203 "Listening to the radio" 0.0842
|
||||
"120306" 4.9839 5.1187 "Listening to/playing music" 0.112
|
||||
"120307" 4.9215 4.6528 "Playing games" 0.4886
|
||||
"120308" 4.274 4.4493 "Computer use for leisure (exc. Games)" 0.5267
|
||||
"120309" 4.9311 5.2819 "Arts and crafts as a hobby" 0.0832
|
||||
"120311" 4.9605 5.5621 "Hobbies, except arts and crafts and collecting" 0.0094
|
||||
"120312" 4.5865 4.8958 "Reading for personal interest" 1.1138
|
||||
"120313" 4.8226 5.2921 "Writing for personal interest" 0.0148
|
||||
"120399" 5.3157 5.4208 "Relaxing and leisure, misc." 0.0091
|
||||
"120401" 5.2838 5.2415 "Attending performing arts" 0.0313
|
||||
"120402" 5.2915 5.4177 "Attending museums" 0.019
|
||||
"120403" 5.1679 5.0339 "Attending movies/film" 0.0597
|
||||
"120404" 4.9542 4.7208 "Attending gambling establishments" 0.0142
|
||||
"120499" 5.3123 5.3884 "Arts and entertainment, misc." 0.0612
|
||||
"120504" 5.3712 5.571 "Waiting associated with arts and entertainment" 0.0042
|
||||
"130101" 5.1623 5.4596 "Doing aerobics" 0.0089
|
||||
"130102" 5.2133 4.9253 "Playing baseball" 0.0034
|
||||
"130103" 5.3224 5.1499 "Playing basketball" 0.0297
|
||||
"130104" 5.3086 5.3288 "Biking" 0.0459
|
||||
"130105" 5.1553 4.7978 "Playing billiards" 0.0084
|
||||
"130106" 5.5945 5.2725 "Boating" 0.0158
|
||||
"130107" 4.257 4.9967 "Bowling" 0.0098
|
||||
"130109" 5.2666 5.6163 "Dancing" 0.0144
|
||||
"130110" 4.1328 5.5767 "Participating in equestrian sports" 0.0054
|
||||
"130112" 5.1375 5.3017 "Fishing" 0.0328
|
||||
"130113" 5.1277 4.4822 "Playing football" 0.0075
|
||||
"130114" 5.1526 5.1615 "Golfing" 0.0337
|
||||
"130116" 5.3033 5.4277 "Hiking" 0.0162
|
||||
"130117" 4.9474 5.6306 "Playing hockey" 0.0046
|
||||
"130118" 4.6138 5.5714 "Hunting" 0.0177
|
||||
"130119" 5 5.878 "Participating in martial arts" 0.0049
|
||||
"130120" 5.2921 5.1088 "Playing racquet sports" 0.0087
|
||||
"130122" 5.2786 4.8898 "Rollerblading" 0.0065
|
||||
"130124" 4.8552 5.4258 "Running" 0.0721
|
||||
"130125" 5.7289 5.2832 "Skiing, ice skating, snowboarding" 0.0084
|
||||
"130126" 5.3031 5.3535 "Playing soccer" 0.0116
|
||||
"130127" 4.7308 5.2851 "Playing softball" 0.0067
|
||||
"130128" 4.4901 5.4879 "Using cardiovascular equipment" 0.0678
|
||||
"130129" 5.8696 5.5908 "Vehicle touring/racing" 0.0065
|
||||
"130130" 5.8128 5.4136 "Playing volleyball" 0.0058
|
||||
"130131" 4.9928 5.4046 "Walking" 0.3685
|
||||
"130132" 5.4465 5.4959 "Participating in water sports" 0.0895
|
||||
"130133" 4.8286 5.4693 "Weightlifting/strength training" 0.0689
|
||||
"130134" 4.6372 5.3806 "Working out, unspecified" 0.2212
|
||||
"130136" 4.567 5.4904 "Doing yoga" 0.0186
|
||||
"130199" 5.1362 5.4151 "Playing sports misc." 0.0416
|
||||
"130202" 4.9877 5.1101 "Watching baseball" 0.0108
|
||||
"130203" 5.5753 5.0357 "Watching basketball" 0.0063
|
||||
"130213" 5.238 5.4997 "Watching football" 0.0096
|
||||
"130216" 4.6272 5.2029 "Watching hockey" 0.0071
|
||||
"130218" 4.8914 4.4692 "Watching racquet sports" 0.0023
|
||||
"130224" 5.5379 5.3283 "Watching soccer" 0.0081
|
||||
"130227" 5.499 4.9985 "Watching volleyball" 0.0022
|
||||
"130299" 4.818 5.182 "Attending sporting events, misc." 0.0053
|
||||
"140101" 5.1801 5.7656 "Attending religious services" 0.5128
|
||||
"140102" 5.1242 5.8226 "Participation in religious practices" 0.3447
|
||||
"140103" 5.3894 5.4142 "Waiting assoc w/religious and spiritual activities" 0.0098
|
||||
"140105" 5.294 5.8076 "Religious education activities" 0.0787
|
||||
"149999" 5.4999 6 "Religious and spiritual activities, misc." 0.0029
|
||||
"150101" 4.3872 5.1186 "Computer use" 0.0465
|
||||
"150102" 4.892 5.3698 "Organizing and preparing" 0.0538
|
||||
"150103" 5.1465 5.8767 "Reading" 0.0049
|
||||
"150104" 3.9379 5.2894 "Telephone calls (except hotline counseling)" 0.0174
|
||||
"150105" 5.0888 4.8161 "Writing" 0.0026
|
||||
"150106" 5.5408 5.6845 "Fundraising" 0.0133
|
||||
"150199" 5.2515 5.4781 "Administrative and support activities, misc." 0.0196
|
||||
"150201" 5.0504 5.6601 "Food preparation, presentation, clean-up" 0.036
|
||||
"150202" 4.4875 5.4283 "Collecting and delivering clothing and other goods" 0.0101
|
||||
"150203" 5.1426 5.5682 "Providing care" 0.0195
|
||||
"150204" 5.2749 5.6544 "Teaching, leading, counseling, mentoring" 0.0525
|
||||
"150299" 4.7265 5.6233 "Social service and care activities, misc." 0.0093
|
||||
"150302" 4.833 5.3045 "Indoor and outdoor maintenance, repair, and clean-up" 0.0173
|
||||
"150401" 5.2987 5.6969 "Performing" 0.0265
|
||||
"150402" 5.037 5.5589 "Serving at volunteer events and cultural activities" 0.0194
|
||||
"150501" 4.5845 5.3972 "Attending meetings, conferences, and training" 0.0507
|
||||
"150701" 4.5999 5.2999 "Waiting associated with volunteer activities" 0.0024
|
||||
"159999" 5.2785 5.6518 "Volunteer activities, misc." 0.1119
|
||||
"160101" 4.7783 5.5471 "Telephone calls to/from family members" 0.3752
|
||||
"160102" 4.795 5.1776 "Phone calls to/from friends, neighbors" 0.2003
|
||||
"160103" 2.2221 5.5185 "Telephone calls to/from education svcs providers" 0.0032
|
||||
"160104" 3.4873 5.4081 "Telephone calls to/from salespeople" 0.0059
|
||||
"160105" 2.6467 4.8562 "Phone calls to/from prof, personal svcs providers" 0.0167
|
||||
"160106" 2.1017 5.3628 "Phone calls to/from household services providers" 0.0106
|
||||
"160108" 3.7003 5.8925 "Telephone calls to/from government officials" 0.0056
|
||||
"160199" 4.5566 5.211 "Telephone calls (to or from), misc." 0.1438
|
||||
"180101" 4.674 5.1188 "Travel for personal care" 0.0959
|
||||
"180201" 4.4686 5.0219 "Travel for housework" 0.0524
|
||||
"180202" 4.8177 5.1817 "Travel for food and drink prep" 0.0526
|
||||
"180203" 4.4063 5.4387 "Travel for int. maint, repair, and decoration" 0.0109
|
||||
"180204" 4.6292 4.7371 "Travel for ext. maint, repair, and decoration" 0.0055
|
||||
"180205" 4.7036 5.5364 "Travel for lawn, garden, and houseplants" 0.013
|
||||
"180206" 4.7082 5.0638 "Travel for care for animals (not vet care)" 0.0486
|
||||
"180207" 5.0427 5.0209 "Travel for vehicle care and maint (by self)" 0.0223
|
||||
"180208" 5.8333 6 "Travel for tool, repair, and maintenance" 0.0043
|
||||
"180209" 4.6447 5.0846 "Travel for household management" 0.2689
|
||||
"180302" 4.797 5.2995 "Travel for caring for and helping household children" 0.859
|
||||
"180303" 4.2 5.0188 "Travel for household children's education" 0.0126
|
||||
"180304" 4.1476 5.2791 "Travel for household children's health" 0.0163
|
||||
"180305" 3.8614 5.8019 "Travel for caring for household adults" 0.0206
|
||||
"180306" 4.5551 5.1211 "Travel for helping household adults" 0.1177
|
||||
"180402" 4.8915 5.2767 "Travel for helping non-household kids" 0.1991
|
||||
"180404" 3.6108 5.3335 "Travel for non-household children's health" 0.0043
|
||||
"180405" 4.352 5.2076 "Travel for caring for non-household adults" 0.015
|
||||
"180406" 4.8412 5.1668 "Travel for helping non-household adults" 0.4152
|
||||
"180501" 4.433 4.9649 "Travel for working" 2.2379
|
||||
"180502" 3.9999 4.9312 "Travel for work-related activities" 0.007
|
||||
"180503" 4.5506 5.4222 "Travel for income-generating activities" 0.0318
|
||||
"180504" 3.8844 5.2982 "Travel for job search and interviewing" 0.0322
|
||||
"180601" 4.2031 4.8203 "Travel for taking class" 0.125
|
||||
"180602" 4.9581 4.6657 "Travel for extracurricular activities (ex. Sports)" 0.0058
|
||||
"180603" 4.4433 4.6157 "Travel for research/homework" 0.0171
|
||||
"180604" 4.1596 4.7597 "Travel for registration/admin activities" 0.003
|
||||
"180701" 4.596 4.8843 "Traveling to/from the grocery store" 0.8789
|
||||
"180703" 4.7388 4.952 "Travel for purchasing food (not groceries)" 0.5882
|
||||
"180704" 4.6983 5.0044 "Travel for shopping, not groceries" 1.433
|
||||
"180705" 4.5856 5.0456 "Traveling to/from gas station" 0.1591
|
||||
"180801" 4.8568 6 "Travel for using childcare services" 0.005
|
||||
"180802" 4.3214 5.0572 "Travel for using financial svcs and banking" 0.0787
|
||||
"180804" 3.6482 5.3131 "Travel for using medical services" 0.1596
|
||||
"180805" 4.8084 4.9991 "Travel for using personal care services" 0.057
|
||||
"180806" 4.1981 4.8519 "Travel for using real estate services" 0.0163
|
||||
"180807" 3.4253 5.2574 "Travel for using veterinary services" 0.013
|
||||
"180899" 5.0215 4.9994 "Travel rel. to using prof, personal care svcs misc." 0.0055
|
||||
"180901" 4.4148 5.1697 "Travel for using household services" 0.0113
|
||||
"180902" 3.6941 5.7827 "Travel for home maintenance" 0.0028
|
||||
"180903" 4.5553 4.2484 "Travel for using pet services (not vet)" 0.0086
|
||||
"180905" 4.3643 5.0414 "Travel for vehicle maintenance" 0.0455
|
||||
"181001" 4.543 5.2496 "Travel for using government services" 0.0124
|
||||
"181002" 4.9754 5.6815 "Travel for civic obligations and participation" 0.0049
|
||||
"181101" 4.9796 5.0953 "Travel for eating and drinking" 1.4294
|
||||
"181201" 4.8021 5.1563 "Travel for socializing" 1.1308
|
||||
"181202" 5.1019 5.1226 "Trvl related to attending or hosting social events" 0.1871
|
||||
"181204" 5.0067 5.073 "Travel for arts and entertainment" 0.1724
|
||||
"181205" 5.1206 5.0307 "Travel as a form of entertainment" 0.0582
|
||||
"181206" 4.7928 5.0097 "Travel for relaxing and leisure" 0.3648
|
||||
"181301" 4.8777 5.071 "Travel for sports, exercise, or recreation" 0.5078
|
||||
"181302" 4.8429 5.0556 "Travel for attending sporting events" 0.0643
|
||||
"181401" 5.0299 5.5472 "Travel for religious practices" 0.5638
|
||||
"181501" 4.8462 5.2251 "Travel for volunteering" 0.2669
|
||||
"181599" 5.0713 5.285 "Travel for volunteer activities, misc." 0.0084
|
||||
"181601" 4.356 4.9264 "Travel for phone calls" 0.0229
|
||||
"181801" 4.7595 4.3052 "Security procedures related to traveling" 0.009
|
||||
"189999" 4.6894 5.1014 "Traveling, misc." 0.2231
|
||||
"500101" 4.5424 5.223 "Insufficient detail in verbatim" 0.5265
|
||||
"500103" 4.907 5.2302 "Missing travel or destination" 0.0964
|
||||
"500104" 4.4997 5.2727 "Recorded simultaneous activities incorrectly" 0.0315
|
||||
"500107" 4.6635 5.3266 "Unable to code activity at 1st tier" 0.0125
|
||||
|
@@ -0,0 +1,14 @@
|
||||
<!DOCTYPE html>
|
||||
<head>
|
||||
<meta charset="utf-8">
|
||||
<title>Activities, Happiness, and Meaning</title>
|
||||
<link rel="stylesheet" href="style/style.css" type="text/css" media="screen" />
|
||||
</head>
|
||||
|
||||
<div id="main-wrapper">
|
||||
<h1>Meaningfulness with Happiness</h1>
|
||||
<div id="chart"></div>
|
||||
</div>
|
||||
|
||||
<script src="js/d3.v7.min.js"></script>
|
||||
<script src="js/bubbleplot.js"></script>
|
||||
@@ -0,0 +1,139 @@
|
||||
// Dimensions of chart.
|
||||
let margin = { top: 20, right: 30, bottom: 50, left: 55 },
|
||||
// width = parseInt(d3.select('#chart').style('width'), 10) - margin.left - margin.right,
|
||||
width = 600 - margin.left - margin.right,
|
||||
// height = width/.8 - margin.top - margin.bottom;
|
||||
height = width - margin.top - margin.bottom;
|
||||
|
||||
let svg = d3.select("#chart").append("svg")
|
||||
.attr("width", width + margin.left + margin.right)
|
||||
.attr("height", height + margin.top + margin.bottom)
|
||||
.append("g")
|
||||
.attr("transform", "translate(" + margin.left + "," + margin.top + ")");
|
||||
|
||||
// Scales: x and y and r
|
||||
let x = d3.scaleLinear()
|
||||
// .domain([3, 6])
|
||||
.domain([4, 6])
|
||||
.range([0, width]);
|
||||
let y = d3.scaleLinear()
|
||||
// .domain([2, 6])
|
||||
.domain([3, 6])
|
||||
.range([height, 0]);
|
||||
let r = d3.scaleSqrt()
|
||||
.domain([0, 10])
|
||||
.range([0, 25]);
|
||||
|
||||
// Point color
|
||||
let ptcolor = "#5a8171";
|
||||
|
||||
|
||||
|
||||
// x-axis
|
||||
let xAxis = d3.axisBottom(x)
|
||||
// .ticks(7)
|
||||
.ticks(4)
|
||||
.tickSize(-height-8)
|
||||
.tickPadding(5);
|
||||
let xAxisEl = svg.append("g")
|
||||
.attr("class", "x axis bottom")
|
||||
.attr("transform", "translate(0,"+(height+8)+")");
|
||||
xAxisEl.append("text")
|
||||
.attr("class", "axistitle")
|
||||
.attr("text-anchor", "start")
|
||||
.attr("x", 0).attr("y", 0)
|
||||
// .attr("dx", "-.25em")
|
||||
.attr("dx", "-.8em")
|
||||
.attr("dy", "2.5em")
|
||||
.text("Meaningfulness Score Average");
|
||||
xAxisEl.call(xAxis);
|
||||
|
||||
|
||||
// y-axis
|
||||
let yAxis = d3.axisLeft(y)
|
||||
// .ticks(7)
|
||||
.ticks(5)
|
||||
.tickSize(-width-8)
|
||||
.tickPadding(5);
|
||||
let yAxisEl = svg.append("g")
|
||||
.attr("class", "y axis left")
|
||||
.attr("transform", "translate("+(-8)+",0)");
|
||||
yAxisEl.append("text")
|
||||
.attr("class", "axistitle")
|
||||
.attr("x", 0).attr("y", 0)
|
||||
.attr("dx", "4px")
|
||||
// .attr("dy", "-2em")
|
||||
.attr("dy", "-3em")
|
||||
.style("text-anchor", "end")
|
||||
.attr("transform", "rotate(-90)")
|
||||
.text("Happiness Score Average");
|
||||
yAxisEl.call(yAxis);
|
||||
|
||||
|
||||
let activities;
|
||||
let circle, labeltext;
|
||||
|
||||
// Load data
|
||||
const activitiesData = Promise.all([
|
||||
d3.tsv("data/act_means.tsv", d3.autoType)
|
||||
]);
|
||||
activitiesData.then(function(data) {
|
||||
|
||||
activities = data[0].sort((a, b) => b.relwt - a.relwt);
|
||||
console.log(activities);
|
||||
|
||||
// Initialize chart now that data is loaded.
|
||||
initChart();
|
||||
});
|
||||
|
||||
|
||||
function initChart() {
|
||||
// Circle for each node.
|
||||
circle = svg.append("g")
|
||||
.selectAll("circle")
|
||||
.data(activities)
|
||||
.join("circle")
|
||||
.attr("id", d => "circle"+d.activity)
|
||||
.attr("cx", d => x(d.meaning_mean))
|
||||
.attr("cy", d => y(d.schappy_mean))
|
||||
.attr("fill", ptcolor)
|
||||
.attr("fill-opacity", .75)
|
||||
.attr("r", d => r(d.relwt))
|
||||
.attr("stroke", "#fff")
|
||||
.attr("stroke-width", ".5px");
|
||||
|
||||
setInteraction();
|
||||
}
|
||||
|
||||
|
||||
|
||||
function setInteraction() {
|
||||
|
||||
// Create label
|
||||
labeltext = svg.append("text")
|
||||
.attr("text-anchor", "middle");
|
||||
|
||||
// Hover events
|
||||
circle.on("mouseover", function(e,d) {
|
||||
d3.selectAll(".current").classed("current", false);
|
||||
d3.select(this).classed("current", true);
|
||||
|
||||
let curract = d3.select(this).datum();
|
||||
|
||||
labeltext.text(curract.descrip)
|
||||
.attr("x", x(curract.meaning_mean))
|
||||
.attr("y", y(curract.schappy_mean)-r(curract.relwt)-5);
|
||||
})
|
||||
// .on("mousemove", function(e,d) {
|
||||
// d3.select(this).classed("current", true);
|
||||
// })
|
||||
.on('mouseout', function(d) {
|
||||
d3.select(this).classed('current', false);
|
||||
labeltext.text('');
|
||||
}); // @end mouseover
|
||||
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
@@ -0,0 +1,2 @@
|
||||
// https://d3js.org v7.4.0 Copyright 2010-2022 Mike Bostock
|
||||
!function(t,n){"object"==typeof exports&&"undefined"!=typeof module?n(exports):"function"==typeof define&&define.amd?define(["exports"],n):n((t="undefined"!=typeof globalThis?globalThis:t||self).d3=t.d3||{})}(this,(function(t){"use strict";function n(t,n){return null==t||null==n?NaN:t<n?-1:t>n?1:t>=n?0:NaN}function e(t){let e=t,r=t,i=t;function o(t,n,e=0,o=t.length){if(e<o){if(0!==r(n,n))return o;do{const r=e+o>>>1;i(t[r],n)<0?e=r+1:o=r}while(e<o)}return e}return 2!==t.length&&(e=(n,e)=>t(n)-e,r=n,i=(e,r)=>n(t(e),r)),{left:o,center:function(t,n,r=0,i=t.length){const a=o(t,n,r,i-1);return a>r&&e(t[a-1],n)>-e(t[a],n)?a-1:a},right:function(t,n,e=0,o=t.length){if(e<o){if(0!==r(n,n))return o;do{const r=e+o>>>1;i(t[r],n)<=0?e=r+1:o=r}while(e<o)}return e}}}function r(t){return null===t?NaN:+t}const i=e(n),o=i.right,a=i.left,u=e(r).center;var c=o;function f(t,n){let e=0;if(void 0===n)for(let n of t)null!=n&&(n=+n)>=n&&++e;else{let r=-1;for(let i of t)null!=(i=n(i,++r,t))&&(i=+i)>=i&&++e}return e}function s(t){return 0|t.length}function l(t){return!(t>0)}function h(t){return"object"!=typeof t||"length"in t?t:Array.from(t)}function d(t,n){let e,r=0,i=0,o=0;if(void 0===n)for(let n of t)null!=n&&(n=+n)>=n&&(e=n-i,i+=e/++r,o+=e*(n-i));else{let a=-1;for(let u of t)null!=(u=n(u,++a,t))&&(u=+u)>=u&&(e=u-i,i+=e/++r,o+=e*(u-i))}if(r>1)return o/(r-1)}function p(t,n){const e=d(t,n);return e?Math.sqrt(e):e}function g(t,n){let e,r;if(void 0===n)for(const n of t)null!=n&&(void 0===e?n>=n&&(e=r=n):(e>n&&(e=n),r<n&&(r=n)));else{let i=-1;for(let o of t)null!=(o=n(o,++i,t))&&(void 0===e?o>=o&&(e=r=o):(e>o&&(e=o),r<o&&(r=o)))}return[e,r]}class y{constructor(){this._partials=new Float64Array(32),this._n=0}add(t){const n=this._partials;let e=0;for(let r=0;r<this._n&&r<32;r++){const i=n[r],o=t+i,a=Math.abs(t)<Math.abs(i)?t-(o-i):i-(o-t);a&&(n[e++]=a),t=o}return n[e]=t,this._n=e+1,this}valueOf(){const t=this._partials;let n,e,r,i=this._n,o=0;if(i>0){for(o=t[--i];i>0&&(n=o,e=t[--i],o=n+e,r=e-(o-n),!r););i>0&&(r<0&&t[i-1]<0||r>0&&t[i-1]>0)&&(e=2*r,n=o+e,e==n-o&&(o=n))}return o}}class InternMap extends Map{constructor(t,n=m){if(super(),Object.defineProperties(this,{_intern:{value:new Map},_key:{value:n}}),null!=t)for(const[n,e]of t)this.set(n,e)}get(t){return super.get(v(this,t))}has(t){return super.has(v(this,t))}set(t,n){return super.set(_(this,t),n)}delete(t){return super.delete(b(this,t))}}class InternSet extends Set{constructor(t,n=m){if(super(),Object.defineProperties(this,{_intern:{value:new Map},_key:{value:n}}),null!=t)for(const n of t)this.add(n)}has(t){return super.has(v(this,t))}add(t){return super.add(_(this,t))}delete(t){return super.delete(b(this,t))}}function v({_intern:t,_key:n},e){const r=n(e);return t.has(r)?t.get(r):e}function _({_intern:t,_key:n},e){const r=n(e);return t.has(r)?t.get(r):(t.set(r,e),e)}function b({_intern:t,_key:n},e){const r=n(e);return t.has(r)&&(e=t.get(r),t.delete(r)),e}function m(t){return null!==t&&"object"==typeof t?t.valueOf():t}function x(t){return t}function w(t,...n){return k(t,x,x,n)}function M(t,...n){return k(t,Array.from,x,n)}function A(t,n){for(let e=1,r=n.length;e<r;++e)t=t.flatMap((t=>t.pop().map((([n,e])=>[...t,n,e]))));return t}function T(t,n,...e){return k(t,x,n,e)}function S(t,n,...e){return k(t,Array.from,n,e)}function E(t){if(1!==t.length)throw new Error("duplicate key");return t[0]}function k(t,n,e,r){return function t(i,o){if(o>=r.length)return e(i);const a=new InternMap,u=r[o++];let c=-1;for(const t of i){const n=u(t,++c,i),e=a.get(n);e?e.push(t):a.set(n,[t])}for(const[n,e]of a)a.set(n,t(e,o));return n(a)}(t,0)}function N(t,n){return Array.from(n,(n=>t[n]))}function C(t,...n){if("function"!=typeof t[Symbol.iterator])throw new TypeError("values is not iterable");t=Array.from(t);let[e]=n;if(e&&2!==e.length||n.length>1){const r=Uint32Array.from(t,((t,n)=>n));return n.length>1?(n=n.map((n=>t.map(n))),r.sort(((t,e)=>{for(const r of n){const n=z(r[t],r[e]);if(n)return n}}))):(e=t.map(e),r.sort(((t,n)=>z(e[t],e[n])))),N(t,r)}return t.sort(P(e))}function P(t=n){if(t===n)return z;if("function"!=typeof t)throw new TypeError("compare is not a function");return(n,e)=>{const r=t(n,e);return r||0===r?r:(0===t(e,e))-(0===t(n,n))}}function z(t,n){return(null==t||!(t>=t))-(null==n||!(n>=n))||(t<n?-1:t>n?1:0)}var D=Array.prototype.slice;function R(t){return()=>t}var F=Math.sqrt(50),q=Math.sqrt(10),O=Math.sqrt(2);function U(t,n,e){var r,i,o,a,u=-1;if(e=+e,(t=+t)===(n=+n)&&e>0)return[t];if((r=n<t)&&(i=t,t=n,n=i),0===(a=I(t,n,e))||!isFinite(a))return[];if(a>0){let e=Math.round(t/a),r=Math.round(n/a);for(e*a<t&&++e,r*a>n&&--r,o=new Array(i=r-e+1);++u<i;)o[u]=(e+u)*a}else{a=-a;let e=Math.round(t*a),r=Math.round(n*a);for(e/a<t&&++e,r/a>n&&--r,o=new Array(i=r-e+1);++u<i;)o[u]=(e+u)/a}return r&&o.reverse(),o}function I(t,n,e){var r=(n-t)/Math.max(0,e),i=Math.floor(Math.log(r)/Math.LN10),o=r/Math.pow(10,i);return i>=0?(o>=F?10:o>=q?5:o>=O?2:1)*Math.pow(10,i):-Math.pow(10,-i)/(o>=F?10:o>=q?5:o>=O?2:1)}funLine truncated
|
||||
@@ -0,0 +1,77 @@
|
||||
/* #Reset & Basics (Inspired by E. Meyers)
|
||||
================================================== */
|
||||
html, body, div, span, applet, object, iframe, h1, h2, h3, h4, h5, h6, p, blockquote, pre, a, abbr, acronym, address, big, cite, code, del, dfn, em, img, ins, kbd, q, s, samp, small, strike, strong, sub, sup, tt, var, b, u, i, center, dl, dt, dd, ol, ul, li, fieldset, form, label, legend, table, caption, tbody, tfoot, thead, tr, th, td, article, aside, canvas, details, embed, figure, figcaption, footer, header, hgroup, menu, nav, output, ruby, section, summary, time, mark, audio, video {
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
border: 0;
|
||||
font-size: 100%;
|
||||
font: inherit;
|
||||
vertical-align: baseline; }
|
||||
article, aside, details, figcaption, figure, footer, header, hgroup, menu, nav, section {
|
||||
display: block; }
|
||||
body {
|
||||
line-height: 1; }
|
||||
ol, ul {
|
||||
list-style: none; }
|
||||
blockquote, q {
|
||||
quotes: none; }
|
||||
blockquote:before, blockquote:after,
|
||||
q:before, q:after {
|
||||
content: '';
|
||||
content: none; }
|
||||
table {
|
||||
border-collapse: collapse;
|
||||
border-spacing: 0; }
|
||||
|
||||
|
||||
/* Main layout
|
||||
============================ */
|
||||
|
||||
#main-wrapper {
|
||||
width: 600px;
|
||||
margin: 40px auto;
|
||||
font-family: Georgia, serif;
|
||||
}
|
||||
h1 {
|
||||
font-family: Georgia, serif;
|
||||
font-size: 1.45em;
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
|
||||
/* Chart
|
||||
============================ */
|
||||
|
||||
#chart {
|
||||
position: relative;
|
||||
margin: 0 auto;
|
||||
}
|
||||
.axis text {
|
||||
font-family: "Courier New", Courier, monospace;
|
||||
font-size: .8rem;
|
||||
}
|
||||
.axis .axistitle {
|
||||
text-transform: uppercase;
|
||||
fill: #333;
|
||||
font-size: .8rem;
|
||||
}
|
||||
.axis path,
|
||||
.axis line {
|
||||
fill: none;
|
||||
stroke: #ccc;
|
||||
stroke-width: 1px;
|
||||
shape-rendering: crispEdges;
|
||||
}
|
||||
.x.axis path, .y.axis path {
|
||||
display: none;
|
||||
}
|
||||
|
||||
|
||||
/* Interaction
|
||||
============================ */
|
||||
|
||||
circle.current {
|
||||
stroke: #000;
|
||||
stroke-width: 3px;
|
||||
}
|
||||
|
||||
+110
@@ -0,0 +1,110 @@
|
||||
Year,Beef,Chicken
|
||||
1909,51.1,10.4
|
||||
1910,48.5,11.0
|
||||
1911,47.2,11.1
|
||||
1912,44.5,10.6
|
||||
1913,43.6,10.3
|
||||
1914,42.7,10.3
|
||||
1915,38.8,10.2
|
||||
1916,40.6,9.6
|
||||
1917,44.6,9.4
|
||||
1918,47.2,9.4
|
||||
1919,42.4,10.1
|
||||
1920,40.7,9.7
|
||||
1921,38.2,9.5
|
||||
1922,40.7,10.1
|
||||
1923,41.1,10.4
|
||||
1924,41.0,9.7
|
||||
1925,41.0,10.1
|
||||
1926,41.5,10.1
|
||||
1927,37.5,10.8
|
||||
1928,33.6,10.4
|
||||
1929,34.2,10.1
|
||||
1930,33.7,11.1
|
||||
1931,33.4,10.0
|
||||
1932,32.1,10.2
|
||||
1933,35.5,10.4
|
||||
1934,43.9,9.6
|
||||
1935,36.6,9.3
|
||||
1936,41.6,9.6
|
||||
1937,38.0,9.7
|
||||
1938,37.4,9.0
|
||||
1939,37.6,10.0
|
||||
1940,37.8,10.0
|
||||
1941,42.6,11.0
|
||||
1942,45.9,12.7
|
||||
1943,43.0,16.0
|
||||
1944,46.6,15.3
|
||||
1945,48.0,15.1
|
||||
1946,44.2,13.9
|
||||
1947,49.2,12.5
|
||||
1948,44.2,12.6
|
||||
1949,44.7,13.5
|
||||
1950,44.6,14.3
|
||||
1951,41.2,15.0
|
||||
1952,43.9,15.2
|
||||
1953,54.5,15.1
|
||||
1954,56.0,15.6
|
||||
1955,57.2,14.7
|
||||
1956,59.5,16.8
|
||||
1957,58.7,17.5
|
||||
1958,55.9,19.2
|
||||
1959,56.6,19.7
|
||||
1960,59.1,19.1
|
||||
1961,61.0,20.5
|
||||
1962,61.7,20.5
|
||||
1963,65.4,21.0
|
||||
1964,70.6,21.3
|
||||
1965,70.4,22.8
|
||||
1966,73.7,24.5
|
||||
1967,75.3,25.1
|
||||
1968,77.3,25.2
|
||||
1969,77.8,26.3
|
||||
1970,79.8,27.4
|
||||
1971,79.2,27.4
|
||||
1972,80.5,28.3
|
||||
1973,76.0,27.1
|
||||
1974,80.7,27.0
|
||||
1975,83.2,26.4
|
||||
1976,88.8,28.5
|
||||
1977,86.3,29.0
|
||||
1978,82.2,30.4
|
||||
1979,73.5,32.8
|
||||
1980,72.1,32.7
|
||||
1981,72.8,33.7
|
||||
1982,72.5,33.9
|
||||
1983,74.1,34.0
|
||||
1984,73.8,35.3
|
||||
1985,74.6,36.4
|
||||
1986,74.4,37.2
|
||||
1987,69.5,39.4
|
||||
1988,68.6,39.6
|
||||
1989,65.1,40.5
|
||||
1990,63.9,42.5
|
||||
1991,62.9,44.2
|
||||
1992,62.4,46.5
|
||||
1993,61.0,48.1
|
||||
1994,62.9,48.7
|
||||
1995,63.5,48.2
|
||||
1996,64.0,48.6
|
||||
1997,62.6,50.0
|
||||
1998,63.6,50.4
|
||||
1999,64.3,53.6
|
||||
2000,64.5,54.2
|
||||
2001,63.1,54.0
|
||||
2002,64.5,56.8
|
||||
2003,61.9,57.6
|
||||
2004,63.0,59.3
|
||||
2005,62.5,60.5
|
||||
2006,62.8,60.9
|
||||
2007,62.1,59.9
|
||||
2008,59.4,58.7
|
||||
2009,58.1,56.1
|
||||
2010,56.7,58.0
|
||||
2011,54.4,58.4
|
||||
2012,54.5,56.7
|
||||
2013,53.6,57.7
|
||||
2014,51.5,58.8
|
||||
2015,51.4,62.6
|
||||
2016,52.9,63.2
|
||||
2017,54.3,64.1
|
||||
|
@@ -0,0 +1,14 @@
|
||||
<!DOCTYPE html>
|
||||
<head>
|
||||
<meta charset="utf-8">
|
||||
<title>Beef vs. Chicken</title>
|
||||
<link rel="stylesheet" href="style/style.css" type="text/css" media="screen" />
|
||||
</head>
|
||||
|
||||
<div id="main-wrapper">
|
||||
<h1>Beef vs. Chicken</h1>
|
||||
<div id="chart"></div>
|
||||
</div>
|
||||
|
||||
<script src="js/d3.v7.min.js"></script>
|
||||
<script src="js/differencechart.js"></script>
|
||||
@@ -0,0 +1,2 @@
|
||||
// https://d3js.org v7.4.0 Copyright 2010-2022 Mike Bostock
|
||||
!function(t,n){"object"==typeof exports&&"undefined"!=typeof module?n(exports):"function"==typeof define&&define.amd?define(["exports"],n):n((t="undefined"!=typeof globalThis?globalThis:t||self).d3=t.d3||{})}(this,(function(t){"use strict";function n(t,n){return null==t||null==n?NaN:t<n?-1:t>n?1:t>=n?0:NaN}function e(t){let e=t,r=t,i=t;function o(t,n,e=0,o=t.length){if(e<o){if(0!==r(n,n))return o;do{const r=e+o>>>1;i(t[r],n)<0?e=r+1:o=r}while(e<o)}return e}return 2!==t.length&&(e=(n,e)=>t(n)-e,r=n,i=(e,r)=>n(t(e),r)),{left:o,center:function(t,n,r=0,i=t.length){const a=o(t,n,r,i-1);return a>r&&e(t[a-1],n)>-e(t[a],n)?a-1:a},right:function(t,n,e=0,o=t.length){if(e<o){if(0!==r(n,n))return o;do{const r=e+o>>>1;i(t[r],n)<=0?e=r+1:o=r}while(e<o)}return e}}}function r(t){return null===t?NaN:+t}const i=e(n),o=i.right,a=i.left,u=e(r).center;var c=o;function f(t,n){let e=0;if(void 0===n)for(let n of t)null!=n&&(n=+n)>=n&&++e;else{let r=-1;for(let i of t)null!=(i=n(i,++r,t))&&(i=+i)>=i&&++e}return e}function s(t){return 0|t.length}function l(t){return!(t>0)}function h(t){return"object"!=typeof t||"length"in t?t:Array.from(t)}function d(t,n){let e,r=0,i=0,o=0;if(void 0===n)for(let n of t)null!=n&&(n=+n)>=n&&(e=n-i,i+=e/++r,o+=e*(n-i));else{let a=-1;for(let u of t)null!=(u=n(u,++a,t))&&(u=+u)>=u&&(e=u-i,i+=e/++r,o+=e*(u-i))}if(r>1)return o/(r-1)}function p(t,n){const e=d(t,n);return e?Math.sqrt(e):e}function g(t,n){let e,r;if(void 0===n)for(const n of t)null!=n&&(void 0===e?n>=n&&(e=r=n):(e>n&&(e=n),r<n&&(r=n)));else{let i=-1;for(let o of t)null!=(o=n(o,++i,t))&&(void 0===e?o>=o&&(e=r=o):(e>o&&(e=o),r<o&&(r=o)))}return[e,r]}class y{constructor(){this._partials=new Float64Array(32),this._n=0}add(t){const n=this._partials;let e=0;for(let r=0;r<this._n&&r<32;r++){const i=n[r],o=t+i,a=Math.abs(t)<Math.abs(i)?t-(o-i):i-(o-t);a&&(n[e++]=a),t=o}return n[e]=t,this._n=e+1,this}valueOf(){const t=this._partials;let n,e,r,i=this._n,o=0;if(i>0){for(o=t[--i];i>0&&(n=o,e=t[--i],o=n+e,r=e-(o-n),!r););i>0&&(r<0&&t[i-1]<0||r>0&&t[i-1]>0)&&(e=2*r,n=o+e,e==n-o&&(o=n))}return o}}class InternMap extends Map{constructor(t,n=m){if(super(),Object.defineProperties(this,{_intern:{value:new Map},_key:{value:n}}),null!=t)for(const[n,e]of t)this.set(n,e)}get(t){return super.get(v(this,t))}has(t){return super.has(v(this,t))}set(t,n){return super.set(_(this,t),n)}delete(t){return super.delete(b(this,t))}}class InternSet extends Set{constructor(t,n=m){if(super(),Object.defineProperties(this,{_intern:{value:new Map},_key:{value:n}}),null!=t)for(const n of t)this.add(n)}has(t){return super.has(v(this,t))}add(t){return super.add(_(this,t))}delete(t){return super.delete(b(this,t))}}function v({_intern:t,_key:n},e){const r=n(e);return t.has(r)?t.get(r):e}function _({_intern:t,_key:n},e){const r=n(e);return t.has(r)?t.get(r):(t.set(r,e),e)}function b({_intern:t,_key:n},e){const r=n(e);return t.has(r)&&(e=t.get(r),t.delete(r)),e}function m(t){return null!==t&&"object"==typeof t?t.valueOf():t}function x(t){return t}function w(t,...n){return k(t,x,x,n)}function M(t,...n){return k(t,Array.from,x,n)}function A(t,n){for(let e=1,r=n.length;e<r;++e)t=t.flatMap((t=>t.pop().map((([n,e])=>[...t,n,e]))));return t}function T(t,n,...e){return k(t,x,n,e)}function S(t,n,...e){return k(t,Array.from,n,e)}function E(t){if(1!==t.length)throw new Error("duplicate key");return t[0]}function k(t,n,e,r){return function t(i,o){if(o>=r.length)return e(i);const a=new InternMap,u=r[o++];let c=-1;for(const t of i){const n=u(t,++c,i),e=a.get(n);e?e.push(t):a.set(n,[t])}for(const[n,e]of a)a.set(n,t(e,o));return n(a)}(t,0)}function N(t,n){return Array.from(n,(n=>t[n]))}function C(t,...n){if("function"!=typeof t[Symbol.iterator])throw new TypeError("values is not iterable");t=Array.from(t);let[e]=n;if(e&&2!==e.length||n.length>1){const r=Uint32Array.from(t,((t,n)=>n));return n.length>1?(n=n.map((n=>t.map(n))),r.sort(((t,e)=>{for(const r of n){const n=z(r[t],r[e]);if(n)return n}}))):(e=t.map(e),r.sort(((t,n)=>z(e[t],e[n])))),N(t,r)}return t.sort(P(e))}function P(t=n){if(t===n)return z;if("function"!=typeof t)throw new TypeError("compare is not a function");return(n,e)=>{const r=t(n,e);return r||0===r?r:(0===t(e,e))-(0===t(n,n))}}function z(t,n){return(null==t||!(t>=t))-(null==n||!(n>=n))||(t<n?-1:t>n?1:0)}var D=Array.prototype.slice;function R(t){return()=>t}var F=Math.sqrt(50),q=Math.sqrt(10),O=Math.sqrt(2);function U(t,n,e){var r,i,o,a,u=-1;if(e=+e,(t=+t)===(n=+n)&&e>0)return[t];if((r=n<t)&&(i=t,t=n,n=i),0===(a=I(t,n,e))||!isFinite(a))return[];if(a>0){let e=Math.round(t/a),r=Math.round(n/a);for(e*a<t&&++e,r*a>n&&--r,o=new Array(i=r-e+1);++u<i;)o[u]=(e+u)*a}else{a=-a;let e=Math.round(t*a),r=Math.round(n*a);for(e/a<t&&++e,r/a>n&&--r,o=new Array(i=r-e+1);++u<i;)o[u]=(e+u)/a}return r&&o.reverse(),o}function I(t,n,e){var r=(n-t)/Math.max(0,e),i=Math.floor(Math.log(r)/Math.LN10),o=r/Math.pow(10,i);return i>=0?(o>=F?10:o>=q?5:o>=O?2:1)*Math.pow(10,i):-Math.pow(10,-i)/(o>=F?10:o>=q?5:o>=O?2:1)}funLine truncated
|
||||
@@ -0,0 +1,156 @@
|
||||
// Dimensions of chart.
|
||||
let margin = { top: 30, right: 10, bottom: 30, left: 45 },
|
||||
// width = parseInt(d3.select('#chart').style('width'), 10) - margin.left - margin.right,
|
||||
width = 600 - margin.left - margin.right,
|
||||
height = width*.8 - margin.top - margin.bottom;
|
||||
|
||||
let svg = d3.select("#chart").append("svg")
|
||||
.attr("width", width + margin.left + margin.right)
|
||||
.attr("height", height + margin.top + margin.bottom)
|
||||
.append("g")
|
||||
.attr("transform", "translate(" + margin.left + "," + margin.top + ")");
|
||||
|
||||
|
||||
// Scales: x and y
|
||||
let x = d3.scaleLinear()
|
||||
.domain([1909, 2017])
|
||||
.range([0, width]);
|
||||
let y = d3.scaleLinear()
|
||||
.domain([0, 100])
|
||||
.range([height, 0]);
|
||||
|
||||
|
||||
// Geometries
|
||||
let area = d3.area()
|
||||
.x(d => x(d.year))
|
||||
.y1(d => y(d.amt));
|
||||
let line = d3.line()
|
||||
.x(d => x(d.year))
|
||||
.y(d => y(d.amt));
|
||||
|
||||
|
||||
let xAxis, yAxis, xAxisEl, yAxisEL;
|
||||
|
||||
let meats, beef, chicken;
|
||||
|
||||
|
||||
// Load data
|
||||
const meatData = Promise.all([
|
||||
d3.csv("data/beef-vs-chicken-difference.csv", d3.autoType)
|
||||
]);
|
||||
meatData.then(function(data) {
|
||||
|
||||
meats = data[0];
|
||||
console.log(meats);
|
||||
|
||||
svg.datum(meats);
|
||||
|
||||
// Initialize chart now that data is loaded.
|
||||
initChart();
|
||||
});
|
||||
|
||||
|
||||
|
||||
function initChart() {
|
||||
|
||||
// x-axis
|
||||
xAxis = d3.axisBottom(x)
|
||||
.ticks(4)
|
||||
.tickFormat(d => d)
|
||||
.tickSize(-height-8)
|
||||
.tickPadding(5);
|
||||
xAxisEl = svg.append("g")
|
||||
.attr("class", "x axis bottom")
|
||||
.attr("transform", "translate(0,"+(height+8)+")");
|
||||
xAxisEl.call(xAxis);
|
||||
|
||||
// y-axis
|
||||
yAxis = d3.axisLeft(y)
|
||||
// .ticks(7)
|
||||
.ticks(5)
|
||||
.tickSize(-width-8)
|
||||
.tickPadding(5);
|
||||
yAxisEl = svg.append("g")
|
||||
.attr("class", "y axis left")
|
||||
.attr("transform", "translate("+(-8)+",0)");
|
||||
yAxisEl.append("text")
|
||||
.attr("class", "axistitle")
|
||||
.attr("x", 0).attr("y", 0)
|
||||
.attr("dx", "-2.25em")
|
||||
.attr("dy", "-1.5em")
|
||||
.style("text-anchor", "start")
|
||||
.text("Pounds per capita");
|
||||
yAxisEl.call(yAxis);
|
||||
|
||||
// Area clipping paths
|
||||
svg.append("clipPath")
|
||||
.attr("id", "clip-above")
|
||||
.append("path")
|
||||
.attr("d", d3.area()
|
||||
.x(d => x(d.Year))
|
||||
.y0(0)
|
||||
.y1(d => y(d.Chicken)));
|
||||
svg.append("clipPath")
|
||||
.attr("id", "clip-below")
|
||||
.append("path")
|
||||
.attr("d", d3.area()
|
||||
.x(d => x(d.Year))
|
||||
.y0(height)
|
||||
.y1(d => y(d.Chicken)));
|
||||
|
||||
// Area differences
|
||||
svg.append("path")
|
||||
.attr("class", "area above")
|
||||
.attr("clip-path", "url(#clip-above)")
|
||||
.attr("fill", "#fdad94")
|
||||
.attr("d", d3.area()
|
||||
.x(d => x(d.Year)).y0(height).y1(d => y(d.Beef)));
|
||||
svg.append("path")
|
||||
.attr("class", "area below")
|
||||
.attr("fill", "#f9e59f")
|
||||
.attr("clip-path", "url(#clip-below)")
|
||||
.attr("d", d3.area()
|
||||
.x(d => x(d.Year)).y0(0).y1(d => y(d.Beef)));
|
||||
|
||||
// Lines
|
||||
svg.append("path")
|
||||
.attr("class", "line chicken")
|
||||
.attr("fill", "none")
|
||||
.attr("stroke", "#bf980d")
|
||||
.attr("stroke-width", "2px")
|
||||
.attr("d", d3.line()
|
||||
.x(d => x(d.Year))
|
||||
.y(d => y(d.Chicken)));
|
||||
svg.append("path")
|
||||
.attr("class", "line beef")
|
||||
.attr("fill", "none")
|
||||
.attr("stroke", "#fb470e")
|
||||
.attr("stroke-width", "2px")
|
||||
.attr("d", d3.line()
|
||||
.x(d => x(d.Year))
|
||||
.y(d => y(d.Beef)));
|
||||
|
||||
|
||||
setAnnotation();
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
function setAnnotation() {
|
||||
svg.append("text")
|
||||
.attr("class", "mainlab")
|
||||
.attr("fill", "#fb470e")
|
||||
.attr("x", x(1962))
|
||||
.attr("y", y(40))
|
||||
.text("BEEF");
|
||||
|
||||
svg.append("text")
|
||||
.attr("text-anchor", "end")
|
||||
.attr("class", "mainlab")
|
||||
.attr("fill", "#bf980d")
|
||||
.attr("x", x(2017))
|
||||
.attr("y", y(65))
|
||||
.text("CHICKEN");
|
||||
}
|
||||
|
||||
@@ -0,0 +1,69 @@
|
||||
/* #Reset & Basics (Inspired by E. Meyers)
|
||||
================================================== */
|
||||
html, body, div, span, applet, object, iframe, h1, h2, h3, h4, h5, h6, p, blockquote, pre, a, abbr, acronym, address, big, cite, code, del, dfn, em, img, ins, kbd, q, s, samp, small, strike, strong, sub, sup, tt, var, b, u, i, center, dl, dt, dd, ol, ul, li, fieldset, form, label, legend, table, caption, tbody, tfoot, thead, tr, th, td, article, aside, canvas, details, embed, figure, figcaption, footer, header, hgroup, menu, nav, output, ruby, section, summary, time, mark, audio, video {
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
border: 0;
|
||||
font-size: 100%;
|
||||
font: inherit;
|
||||
vertical-align: baseline; }
|
||||
article, aside, details, figcaption, figure, footer, header, hgroup, menu, nav, section {
|
||||
display: block; }
|
||||
body {
|
||||
line-height: 1; }
|
||||
ol, ul {
|
||||
list-style: none; }
|
||||
blockquote, q {
|
||||
quotes: none; }
|
||||
blockquote:before, blockquote:after,
|
||||
q:before, q:after {
|
||||
content: '';
|
||||
content: none; }
|
||||
table {
|
||||
border-collapse: collapse;
|
||||
border-spacing: 0; }
|
||||
|
||||
|
||||
/* Main layout
|
||||
============================ */
|
||||
|
||||
#main-wrapper {
|
||||
width: 600px;
|
||||
margin: 40px auto;
|
||||
}
|
||||
h1 {
|
||||
font-family: Georgia, serif;
|
||||
font-size: 1.45em;
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
|
||||
/* Chart
|
||||
============================ */
|
||||
|
||||
#chart {
|
||||
position: relative;
|
||||
margin: 0 auto;
|
||||
}
|
||||
text {
|
||||
font-family: "Courier New", Courier, monospace;
|
||||
font-size: .8rem;
|
||||
}
|
||||
text.mainlab {
|
||||
font-weight: bold;
|
||||
}
|
||||
.axis .axistitle {
|
||||
text-transform: uppercase;
|
||||
fill: #333;
|
||||
font-size: .8rem;
|
||||
}
|
||||
.axis path,
|
||||
.axis line {
|
||||
fill: none;
|
||||
stroke: #ccc;
|
||||
stroke-width: 1px;
|
||||
shape-rendering: crispEdges;
|
||||
}
|
||||
.x.axis path, .y.axis path {
|
||||
display: none;
|
||||
}
|
||||
@@ -0,0 +1,292 @@
|
||||
"activity" "schappy_mean" "meaning_mean" "descrip" "relwt"
|
||||
"010301" 3.65 5.2875 "Health-related self care" 0.3437
|
||||
"010399" 0.4441 4.332 "Self care, misc." 0.0022
|
||||
"020101" 4.3016 5.0383 "Interior cleaning" 1.362
|
||||
"020102" 4.1979 4.866 "Laundry" 0.806
|
||||
"020103" 4.8934 5.4284 "Sewing, repairing, and maintaining textiles" 0.076
|
||||
"020104" 4.5711 4.8468 "Storing interior household items, inc. food" 0.2002
|
||||
"020201" 4.6729 5.1604 "Food and drink prep." 3.8685
|
||||
"020202" 4.9016 5.5208 "Food presentation" 0.0659
|
||||
"020203" 4.3252 4.9249 "Kitchen and food clean-up" 0.9425
|
||||
"020301" 4.5569 5.2724 "Interior arrangement, decoration, and repairs" 0.1527
|
||||
"020302" 4.7587 4.8901 "Building and repairing furniture" 0.0073
|
||||
"020303" 4.2926 5.29 "Heating and cooling" 0.0446
|
||||
"020401" 4.1507 5.0967 "Exterior cleaning" 0.1179
|
||||
"020402" 4.8953 5.3774 "Exterior repair, improvements, and decoration" 0.0696
|
||||
"020501" 4.6695 5.2066 "Lawn, garden, and houseplant care" 0.6958
|
||||
"020502" 4.0334 5.083 "Ponds, pools, and hot tubs" 0.0143
|
||||
"020602" 4.591 5.3077 "Care for animals and pets" 0.6464
|
||||
"020603" 4.9233 5.2797 "Walking, exercising, playing with animals" 0.4182
|
||||
"020699" 4.4816 4.6297 "Pet and animal care, misc." 0.0032
|
||||
"020701" 4.3308 5.1412 "Vehicle repair and maintenance (by self)" 0.14
|
||||
"020801" 4.3562 5.1824 "App, tool, toy set-up, repair, and maint (by self)" 0.0589
|
||||
"020901" 3.715 4.999 "Financial management" 0.1445
|
||||
"020902" 4.386 4.9614 "Household and personal organization" 0.6869
|
||||
"020903" 4.3574 4.8634 "Household and personal mail and messages (except e-mail)" 0.1483
|
||||
"020904" 4.1977 4.3381 "Household and personal e-mail and messages" 0.2182
|
||||
"020905" 4.0463 4.9778 "Home security" 0.023
|
||||
"029999" 4.4219 4.895 "Household activities, misc." 0.0023
|
||||
"030101" 4.8037 5.4819 "Care for household children" 1.7066
|
||||
"030102" 5.3559 5.7285 "Reading to/with household children" 0.1706
|
||||
"030103" 5.5047 5.7429 "Playing with household children" 0.5338
|
||||
"030104" 5.4589 5.6239 "Arts and crafts with household children" 0.0131
|
||||
"030105" 5.3366 5.712 "Playing sports with household children" 0.0246
|
||||
"030106" 4.997 5.5712 "Talking with/listening to household children" 0.1503
|
||||
"030108" 4.4771 5.0912 "Organization for household children" 0.0445
|
||||
"030109" 5.0333 5.5065 "Looking after household children" 0.1501
|
||||
"030110" 5.0778 5.615 "Attending household children's events" 0.0925
|
||||
"030111" 4.7433 5.3825 "Waiting for/with household children" 0.0482
|
||||
"030112" 4.7327 5.3525 "Picking up/dropping off household children" 0.3373
|
||||
"030199" 5.0626 5.4164 "Caring for and helping household children, misc." 0.0058
|
||||
"030201" 4.5065 5.5892 "Homework (household children)" 0.1711
|
||||
"030202" 4.062 5.6243 "Meetings and school conferences (household children)" 0.0058
|
||||
"030203" 5.0198 5.808 "Home schooling of household children" 0.0062
|
||||
"030299" 3.4516 5.3227 "Activities related to household child's education, misc." 0.0037
|
||||
"030301" 3.2966 5.5604 "Providing medical care to household children" 0.0218
|
||||
"030302" 3.484 5.545 "Obtaining medical care for household children" 0.0127
|
||||
"030303" 2.7979 5.6905 "Waiting associated with household children's health" 0.0101
|
||||
"030401" 4.3313 5.5832 "Care for household adults" 0.0634
|
||||
"030402" 4.6669 5.0003 "Looking after household adult (as a primary activity)" 0.0043
|
||||
"030403" 3.7147 5.525 "Providing medical care to household adult" 0.021
|
||||
"030404" 4.71 5.7405 "Obtaining medical and care services for household adult" 0.0075
|
||||
"030405" 4.234 5.476 "Waiting associated with caring for household adults" 0.006
|
||||
"030501" 4.3418 5.0822 "Helping household adults" 0.0088
|
||||
"030502" 3.9261 5.5183 "Organization and planning for household adults" 0.0032
|
||||
"030503" 4.6838 5.0713 "Picking up/dropping off household adult" 0.0368
|
||||
"030504" 4.8728 5.4733 "Waiting associated with helping household adults" 0.0247
|
||||
"030599" 4.7353 5.1179 "Helping household adults, misc." 0.0041
|
||||
"040101" 5.3144 5.6892 "Care for non-household children" 0.0835
|
||||
"040102" 5.632 5.8949 "Reading to/with non-household children" 0.0091
|
||||
"040103" 5.7316 5.8642 "Playing with non-household children" 0.116
|
||||
"040105" 4.7162 6 "Playing sports with non-household children" 0.005
|
||||
"040106" 5.632 5.8326 "Talking with/listening to non-household children" 0.0251
|
||||
"040108" 4.6278 5.5581 "Organization and planning for non-household children" 0.0052
|
||||
"040109" 5.3345 5.8355 "Looking after non-household children (as primary activity)" 0.033
|
||||
"040110" 5.5768 5.7883 "Attending non-household children's events" 0.0165
|
||||
"040111" 5.1291 5.322 "Waiting for/with non-household children" 0.0074
|
||||
"040112" 5.0798 5.5207 "Dropping off/picking up non-household children" 0.0691
|
||||
"040199" 5.5774 5.7106 "Caring for and helping non-household children, misc." 0.0054
|
||||
"040201" 4.8287 5.8439 "Homework (non-household children)" 0.0077
|
||||
"040401" 4.5175 5.6303 "Care for non-household adults" 0.0244
|
||||
"040402" 3.6183 5.4763 "Looking after non-household adult" 0.005
|
||||
"040403" 4.3324 5.7824 "Providing medical care to non-household adult" 0.0083
|
||||
"040404" 3.697 5.7815 "Obtaining medical and care svcs for non-household adult" 0.0028
|
||||
"040405" 3.8136 5.5421 "Waiting associated with caring for non-household adults" 0.0045
|
||||
"040501" 4.7363 5.3113 "Hswrk, cooking, and shopping asst, non-household adults" 0.0447
|
||||
"040502" 4.6688 5.368 "House and lawn maint and repair asst, non-household adults" 0.0436
|
||||
"040503" 5.3119 4.9995 "Animal and pet care assistance for non-household adults" 0.0134
|
||||
"040504" 4.5605 5.2475 "Vehicle/appliance maint/repair asst, non-household adults" 0.0201
|
||||
"040505" 4.4638 4.9507 "Financial mgmt asst for non-household adults" 0.0049
|
||||
"040506" 4.1688 5.3376 "household mgmt and paperwork asst, non-household adults" 0.0255
|
||||
"040507" 4.9319 5.3192 "Picking up/dropping off non-household adult" 0.1284
|
||||
"040508" 4.2182 5.2695 "Waiting associated with helping non-household adults" 0.023
|
||||
"040599" 4.3443 5.2868 "Helping non-household adults, misc." 0.015
|
||||
"050101" 4.2106 5.0372 "Work, main job" 3.8671
|
||||
"050102" 4.2169 5.0135 "Work, other job(s)" 0.1346
|
||||
"050104" 4.1585 4.952 "Waiting associated with working" 0.0258
|
||||
"050199" 3.502 3.8063 "Working, misc." 0.0012
|
||||
"050201" 4.8683 4.8224 "Socializing, relaxing, and leisure as part of job" 0.0028
|
||||
"050202" 4.6143 4.9853 "Eating and drinking as part of job" 0.0178
|
||||
"050301" 5.1982 5.486 "Income-generating hobbies, crafts, and food" 0.0079
|
||||
"050303" 4.7095 4.9767 "Income-generating services" 0.0307
|
||||
"050304" 3.7731 5.3123 "Income-generating rental property activities" 0.0053
|
||||
"050399" 4.5872 5.2503 "Other income-generating activities, misc." 0.0391
|
||||
"050401" 3.4136 5.4454 "Job search activities" 0.1018
|
||||
"050403" 4.4473 5.6315 "Job interviewing" 0.0046
|
||||
"060101" 4.0938 4.9396 "Taking class for degree, certification, or lic" 0.1708
|
||||
"060102" 4.8102 5.4599 "Taking class for personal interest" 0.0199
|
||||
"060103" 3.7852 5.4278 "Waiting associated with taking classes" 0.005
|
||||
"060201" 5.3468 5.7823 "Extracurricular club activities" 0.0028
|
||||
"060202" 4.7063 5.0467 "Extracurricular music and performance activities" 0.0049
|
||||
"060299" 4.8569 3.7138 "Education-related extracurricular activities, misc." 0.0017
|
||||
"060301" 3.3418 4.9021 "Homework for class, for degree" 0.2883
|
||||
"060302" 4.9457 5.6787 "Homework for class, for personal interest" 0.0067
|
||||
"060399" 3.0733 4.7988 "Research/homework misc." 0.0048
|
||||
"060401" 5.1 5.8001 "Admin activities: class for degree, cert, or lic" 0.0048
|
||||
"069999" 3.8977 5.3269 "Education, misc." 0.0103
|
||||
"070101" 4.3286 4.8367 "Grocery shopping" 0.5658
|
||||
"070102" 4.2173 4.872 "Purchasing gas" 0.0943
|
||||
"070103" 4.6715 4.8424 "Purchasing food (not groceries)" 0.3922
|
||||
"070104" 4.6217 4.9111 "Shopping" 1.0884
|
||||
"070105" 3.8775 5.1629 "Waiting associated with shopping" 0.0118
|
||||
"070201" 4.6118 4.9319 "Comparison shopping" 0.0037
|
||||
"080101" 5.0985 5.5574 "Using paid childcare services" 0.0073
|
||||
"080201" 4.2378 4.9952 "Banking" 0.0579
|
||||
"080202" 4.6522 5.3043 "Using other financial services" 0.0055
|
||||
"080203" 4.5258 5.3144 "Waiting associated w/banking/financial services" 0.0023
|
||||
"080401" 3.5839 5.4735 "Using health and care services outside the home" 0.1335
|
||||
"080402" 3.5935 4.8952 "Using in-home health and care services" 0.0068
|
||||
"080403" 3.3676 5.2215 "Waiting associated with medical services" 0.031
|
||||
"080501" 4.8617 5.0354 "Using personal care services" 0.0583
|
||||
"080502" 4.809 3.6661 "Waiting associated w/personal care services" 0.0025
|
||||
"080601" 3.9619 5.0571 "Activities rel. to purchasing/selling real estate" 0.0125
|
||||
"080701" 3.0977 5.7036 "Using veterinary services" 0.0085
|
||||
"080702" 4.4371 5.4764 "Waiting associated with veterinary services" 0.003
|
||||
"089999" 4.8267 5.1165 "Professional and personal services, misc." 0.0083
|
||||
"090103" 4.9078 5.18 "Using clothing repair and cleaning services" 0.0066
|
||||
"090201" 4.0885 5.0779 "Using home maint/repair/décor/construction svcs" 0.0121
|
||||
"090202" 4.866 5.2007 "Wtg assoc w/ home main/repair/décor/constr" 0.0058
|
||||
"090301" 4.139 4.4996 "Using pet services" 0.0043
|
||||
"090401" 5.0353 5.5002 "Using lawn and garden services" 0.0034
|
||||
"090501" 3.5476 4.8717 "Using vehicle maintenance or repair services" 0.021
|
||||
"090502" 4.4548 4.9964 "Waiting assoc with vehicle main. or repair svcs" 0.0087
|
||||
"100102" 4.036 5.3569 "Using social services" 0.0034
|
||||
"100103" 3.6129 5.5428 "Obtaining licenses and paying fines, fees, taxes" 0.0071
|
||||
"100201" 3.8247 5.8242 "Civic obligations and participation" 0.0055
|
||||
"100304" 4.2609 4.9115 "Waiting associated with using government services" 0.0028
|
||||
"110101" 4.8524 5.1731 "Eating and drinking" 10
|
||||
"110201" 4.6021 4.9123 "Waiting associated w/eating and drinking" 0.0332
|
||||
"120101" 5.0809 5.424 "Socializing and communicating" 2.5822
|
||||
"120201" 5.4271 5.486 "Attending or hosting parties/receptions/ceremonies" 0.164
|
||||
"120202" 4.4307 5.3018 "Attending meetings for personal interest (not volunteering)" 0.0262
|
||||
"120301" 4.6856 5.1863 "Relaxing, thinking" 1.0886
|
||||
"120302" 4.5497 5.0903 "Tobacco and drug use" 0.0602
|
||||
"120303" 4.634 4.7545 "Television and movies" 5.058
|
||||
"120304" 4.6446 5.4465 "Television (religious)" 0.0193
|
||||
"120305" 4.5594 5.1203 "Listening to the radio" 0.0842
|
||||
"120306" 4.9839 5.1187 "Listening to/playing music" 0.112
|
||||
"120307" 4.9215 4.6528 "Playing games" 0.4886
|
||||
"120308" 4.274 4.4493 "Computer use for leisure (exc. Games)" 0.5267
|
||||
"120309" 4.9311 5.2819 "Arts and crafts as a hobby" 0.0832
|
||||
"120311" 4.9605 5.5621 "Hobbies, except arts and crafts and collecting" 0.0094
|
||||
"120312" 4.5865 4.8958 "Reading for personal interest" 1.1138
|
||||
"120313" 4.8226 5.2921 "Writing for personal interest" 0.0148
|
||||
"120399" 5.3157 5.4208 "Relaxing and leisure, misc." 0.0091
|
||||
"120401" 5.2838 5.2415 "Attending performing arts" 0.0313
|
||||
"120402" 5.2915 5.4177 "Attending museums" 0.019
|
||||
"120403" 5.1679 5.0339 "Attending movies/film" 0.0597
|
||||
"120404" 4.9542 4.7208 "Attending gambling establishments" 0.0142
|
||||
"120499" 5.3123 5.3884 "Arts and entertainment, misc." 0.0612
|
||||
"120504" 5.3712 5.571 "Waiting associated with arts and entertainment" 0.0042
|
||||
"130101" 5.1623 5.4596 "Doing aerobics" 0.0089
|
||||
"130102" 5.2133 4.9253 "Playing baseball" 0.0034
|
||||
"130103" 5.3224 5.1499 "Playing basketball" 0.0297
|
||||
"130104" 5.3086 5.3288 "Biking" 0.0459
|
||||
"130105" 5.1553 4.7978 "Playing billiards" 0.0084
|
||||
"130106" 5.5945 5.2725 "Boating" 0.0158
|
||||
"130107" 4.257 4.9967 "Bowling" 0.0098
|
||||
"130109" 5.2666 5.6163 "Dancing" 0.0144
|
||||
"130110" 4.1328 5.5767 "Participating in equestrian sports" 0.0054
|
||||
"130112" 5.1375 5.3017 "Fishing" 0.0328
|
||||
"130113" 5.1277 4.4822 "Playing football" 0.0075
|
||||
"130114" 5.1526 5.1615 "Golfing" 0.0337
|
||||
"130116" 5.3033 5.4277 "Hiking" 0.0162
|
||||
"130117" 4.9474 5.6306 "Playing hockey" 0.0046
|
||||
"130118" 4.6138 5.5714 "Hunting" 0.0177
|
||||
"130119" 5 5.878 "Participating in martial arts" 0.0049
|
||||
"130120" 5.2921 5.1088 "Playing racquet sports" 0.0087
|
||||
"130122" 5.2786 4.8898 "Rollerblading" 0.0065
|
||||
"130124" 4.8552 5.4258 "Running" 0.0721
|
||||
"130125" 5.7289 5.2832 "Skiing, ice skating, snowboarding" 0.0084
|
||||
"130126" 5.3031 5.3535 "Playing soccer" 0.0116
|
||||
"130127" 4.7308 5.2851 "Playing softball" 0.0067
|
||||
"130128" 4.4901 5.4879 "Using cardiovascular equipment" 0.0678
|
||||
"130129" 5.8696 5.5908 "Vehicle touring/racing" 0.0065
|
||||
"130130" 5.8128 5.4136 "Playing volleyball" 0.0058
|
||||
"130131" 4.9928 5.4046 "Walking" 0.3685
|
||||
"130132" 5.4465 5.4959 "Participating in water sports" 0.0895
|
||||
"130133" 4.8286 5.4693 "Weightlifting/strength training" 0.0689
|
||||
"130134" 4.6372 5.3806 "Working out, unspecified" 0.2212
|
||||
"130136" 4.567 5.4904 "Doing yoga" 0.0186
|
||||
"130199" 5.1362 5.4151 "Playing sports misc." 0.0416
|
||||
"130202" 4.9877 5.1101 "Watching baseball" 0.0108
|
||||
"130203" 5.5753 5.0357 "Watching basketball" 0.0063
|
||||
"130213" 5.238 5.4997 "Watching football" 0.0096
|
||||
"130216" 4.6272 5.2029 "Watching hockey" 0.0071
|
||||
"130218" 4.8914 4.4692 "Watching racquet sports" 0.0023
|
||||
"130224" 5.5379 5.3283 "Watching soccer" 0.0081
|
||||
"130227" 5.499 4.9985 "Watching volleyball" 0.0022
|
||||
"130299" 4.818 5.182 "Attending sporting events, misc." 0.0053
|
||||
"140101" 5.1801 5.7656 "Attending religious services" 0.5128
|
||||
"140102" 5.1242 5.8226 "Participation in religious practices" 0.3447
|
||||
"140103" 5.3894 5.4142 "Waiting assoc w/religious and spiritual activities" 0.0098
|
||||
"140105" 5.294 5.8076 "Religious education activities" 0.0787
|
||||
"149999" 5.4999 6 "Religious and spiritual activities, misc." 0.0029
|
||||
"150101" 4.3872 5.1186 "Computer use" 0.0465
|
||||
"150102" 4.892 5.3698 "Organizing and preparing" 0.0538
|
||||
"150103" 5.1465 5.8767 "Reading" 0.0049
|
||||
"150104" 3.9379 5.2894 "Telephone calls (except hotline counseling)" 0.0174
|
||||
"150105" 5.0888 4.8161 "Writing" 0.0026
|
||||
"150106" 5.5408 5.6845 "Fundraising" 0.0133
|
||||
"150199" 5.2515 5.4781 "Administrative and support activities, misc." 0.0196
|
||||
"150201" 5.0504 5.6601 "Food preparation, presentation, clean-up" 0.036
|
||||
"150202" 4.4875 5.4283 "Collecting and delivering clothing and other goods" 0.0101
|
||||
"150203" 5.1426 5.5682 "Providing care" 0.0195
|
||||
"150204" 5.2749 5.6544 "Teaching, leading, counseling, mentoring" 0.0525
|
||||
"150299" 4.7265 5.6233 "Social service and care activities, misc." 0.0093
|
||||
"150302" 4.833 5.3045 "Indoor and outdoor maintenance, repair, and clean-up" 0.0173
|
||||
"150401" 5.2987 5.6969 "Performing" 0.0265
|
||||
"150402" 5.037 5.5589 "Serving at volunteer events and cultural activities" 0.0194
|
||||
"150501" 4.5845 5.3972 "Attending meetings, conferences, and training" 0.0507
|
||||
"150701" 4.5999 5.2999 "Waiting associated with volunteer activities" 0.0024
|
||||
"159999" 5.2785 5.6518 "Volunteer activities, misc." 0.1119
|
||||
"160101" 4.7783 5.5471 "Telephone calls to/from family members" 0.3752
|
||||
"160102" 4.795 5.1776 "Phone calls to/from friends, neighbors" 0.2003
|
||||
"160103" 2.2221 5.5185 "Telephone calls to/from education svcs providers" 0.0032
|
||||
"160104" 3.4873 5.4081 "Telephone calls to/from salespeople" 0.0059
|
||||
"160105" 2.6467 4.8562 "Phone calls to/from prof, personal svcs providers" 0.0167
|
||||
"160106" 2.1017 5.3628 "Phone calls to/from household services providers" 0.0106
|
||||
"160108" 3.7003 5.8925 "Telephone calls to/from government officials" 0.0056
|
||||
"160199" 4.5566 5.211 "Telephone calls (to or from), misc." 0.1438
|
||||
"180101" 4.674 5.1188 "Travel for personal care" 0.0959
|
||||
"180201" 4.4686 5.0219 "Travel for housework" 0.0524
|
||||
"180202" 4.8177 5.1817 "Travel for food and drink prep" 0.0526
|
||||
"180203" 4.4063 5.4387 "Travel for int. maint, repair, and decoration" 0.0109
|
||||
"180204" 4.6292 4.7371 "Travel for ext. maint, repair, and decoration" 0.0055
|
||||
"180205" 4.7036 5.5364 "Travel for lawn, garden, and houseplants" 0.013
|
||||
"180206" 4.7082 5.0638 "Travel for care for animals (not vet care)" 0.0486
|
||||
"180207" 5.0427 5.0209 "Travel for vehicle care and maint (by self)" 0.0223
|
||||
"180208" 5.8333 6 "Travel for tool, repair, and maintenance" 0.0043
|
||||
"180209" 4.6447 5.0846 "Travel for household management" 0.2689
|
||||
"180302" 4.797 5.2995 "Travel for caring for and helping household children" 0.859
|
||||
"180303" 4.2 5.0188 "Travel for household children's education" 0.0126
|
||||
"180304" 4.1476 5.2791 "Travel for household children's health" 0.0163
|
||||
"180305" 3.8614 5.8019 "Travel for caring for household adults" 0.0206
|
||||
"180306" 4.5551 5.1211 "Travel for helping household adults" 0.1177
|
||||
"180402" 4.8915 5.2767 "Travel for helping non-household kids" 0.1991
|
||||
"180404" 3.6108 5.3335 "Travel for non-household children's health" 0.0043
|
||||
"180405" 4.352 5.2076 "Travel for caring for non-household adults" 0.015
|
||||
"180406" 4.8412 5.1668 "Travel for helping non-household adults" 0.4152
|
||||
"180501" 4.433 4.9649 "Travel for working" 2.2379
|
||||
"180502" 3.9999 4.9312 "Travel for work-related activities" 0.007
|
||||
"180503" 4.5506 5.4222 "Travel for income-generating activities" 0.0318
|
||||
"180504" 3.8844 5.2982 "Travel for job search and interviewing" 0.0322
|
||||
"180601" 4.2031 4.8203 "Travel for taking class" 0.125
|
||||
"180602" 4.9581 4.6657 "Travel for extracurricular activities (ex. Sports)" 0.0058
|
||||
"180603" 4.4433 4.6157 "Travel for research/homework" 0.0171
|
||||
"180604" 4.1596 4.7597 "Travel for registration/admin activities" 0.003
|
||||
"180701" 4.596 4.8843 "Traveling to/from the grocery store" 0.8789
|
||||
"180703" 4.7388 4.952 "Travel for purchasing food (not groceries)" 0.5882
|
||||
"180704" 4.6983 5.0044 "Travel for shopping, not groceries" 1.433
|
||||
"180705" 4.5856 5.0456 "Traveling to/from gas station" 0.1591
|
||||
"180801" 4.8568 6 "Travel for using childcare services" 0.005
|
||||
"180802" 4.3214 5.0572 "Travel for using financial svcs and banking" 0.0787
|
||||
"180804" 3.6482 5.3131 "Travel for using medical services" 0.1596
|
||||
"180805" 4.8084 4.9991 "Travel for using personal care services" 0.057
|
||||
"180806" 4.1981 4.8519 "Travel for using real estate services" 0.0163
|
||||
"180807" 3.4253 5.2574 "Travel for using veterinary services" 0.013
|
||||
"180899" 5.0215 4.9994 "Travel rel. to using prof, personal care svcs misc." 0.0055
|
||||
"180901" 4.4148 5.1697 "Travel for using household services" 0.0113
|
||||
"180902" 3.6941 5.7827 "Travel for home maintenance" 0.0028
|
||||
"180903" 4.5553 4.2484 "Travel for using pet services (not vet)" 0.0086
|
||||
"180905" 4.3643 5.0414 "Travel for vehicle maintenance" 0.0455
|
||||
"181001" 4.543 5.2496 "Travel for using government services" 0.0124
|
||||
"181002" 4.9754 5.6815 "Travel for civic obligations and participation" 0.0049
|
||||
"181101" 4.9796 5.0953 "Travel for eating and drinking" 1.4294
|
||||
"181201" 4.8021 5.1563 "Travel for socializing" 1.1308
|
||||
"181202" 5.1019 5.1226 "Trvl related to attending or hosting social events" 0.1871
|
||||
"181204" 5.0067 5.073 "Travel for arts and entertainment" 0.1724
|
||||
"181205" 5.1206 5.0307 "Travel as a form of entertainment" 0.0582
|
||||
"181206" 4.7928 5.0097 "Travel for relaxing and leisure" 0.3648
|
||||
"181301" 4.8777 5.071 "Travel for sports, exercise, or recreation" 0.5078
|
||||
"181302" 4.8429 5.0556 "Travel for attending sporting events" 0.0643
|
||||
"181401" 5.0299 5.5472 "Travel for religious practices" 0.5638
|
||||
"181501" 4.8462 5.2251 "Travel for volunteering" 0.2669
|
||||
"181599" 5.0713 5.285 "Travel for volunteer activities, misc." 0.0084
|
||||
"181601" 4.356 4.9264 "Travel for phone calls" 0.0229
|
||||
"181801" 4.7595 4.3052 "Security procedures related to traveling" 0.009
|
||||
"189999" 4.6894 5.1014 "Traveling, misc." 0.2231
|
||||
"500101" 4.5424 5.223 "Insufficient detail in verbatim" 0.5265
|
||||
"500103" 4.907 5.2302 "Missing travel or destination" 0.0964
|
||||
"500104" 4.4997 5.2727 "Recorded simultaneous activities incorrectly" 0.0315
|
||||
"500107" 4.6635 5.3266 "Unable to code activity at 1st tier" 0.0125
|
||||
|
@@ -0,0 +1,14 @@
|
||||
<!DOCTYPE html>
|
||||
<head>
|
||||
<meta charset="utf-8">
|
||||
<title>Activities, Happiness, and Meaning</title>
|
||||
<link rel="stylesheet" href="style/style.css" type="text/css" media="screen" />
|
||||
</head>
|
||||
|
||||
<div id="main-wrapper">
|
||||
<h1>Meaningfulness with Happiness</h1>
|
||||
<div id="chart"></div>
|
||||
</div>
|
||||
|
||||
<script src="js/d3.v7.min.js"></script>
|
||||
<script src="js/scatterplot.js"></script>
|
||||
@@ -0,0 +1,2 @@
|
||||
// https://d3js.org v7.4.0 Copyright 2010-2022 Mike Bostock
|
||||
!function(t,n){"object"==typeof exports&&"undefined"!=typeof module?n(exports):"function"==typeof define&&define.amd?define(["exports"],n):n((t="undefined"!=typeof globalThis?globalThis:t||self).d3=t.d3||{})}(this,(function(t){"use strict";function n(t,n){return null==t||null==n?NaN:t<n?-1:t>n?1:t>=n?0:NaN}function e(t){let e=t,r=t,i=t;function o(t,n,e=0,o=t.length){if(e<o){if(0!==r(n,n))return o;do{const r=e+o>>>1;i(t[r],n)<0?e=r+1:o=r}while(e<o)}return e}return 2!==t.length&&(e=(n,e)=>t(n)-e,r=n,i=(e,r)=>n(t(e),r)),{left:o,center:function(t,n,r=0,i=t.length){const a=o(t,n,r,i-1);return a>r&&e(t[a-1],n)>-e(t[a],n)?a-1:a},right:function(t,n,e=0,o=t.length){if(e<o){if(0!==r(n,n))return o;do{const r=e+o>>>1;i(t[r],n)<=0?e=r+1:o=r}while(e<o)}return e}}}function r(t){return null===t?NaN:+t}const i=e(n),o=i.right,a=i.left,u=e(r).center;var c=o;function f(t,n){let e=0;if(void 0===n)for(let n of t)null!=n&&(n=+n)>=n&&++e;else{let r=-1;for(let i of t)null!=(i=n(i,++r,t))&&(i=+i)>=i&&++e}return e}function s(t){return 0|t.length}function l(t){return!(t>0)}function h(t){return"object"!=typeof t||"length"in t?t:Array.from(t)}function d(t,n){let e,r=0,i=0,o=0;if(void 0===n)for(let n of t)null!=n&&(n=+n)>=n&&(e=n-i,i+=e/++r,o+=e*(n-i));else{let a=-1;for(let u of t)null!=(u=n(u,++a,t))&&(u=+u)>=u&&(e=u-i,i+=e/++r,o+=e*(u-i))}if(r>1)return o/(r-1)}function p(t,n){const e=d(t,n);return e?Math.sqrt(e):e}function g(t,n){let e,r;if(void 0===n)for(const n of t)null!=n&&(void 0===e?n>=n&&(e=r=n):(e>n&&(e=n),r<n&&(r=n)));else{let i=-1;for(let o of t)null!=(o=n(o,++i,t))&&(void 0===e?o>=o&&(e=r=o):(e>o&&(e=o),r<o&&(r=o)))}return[e,r]}class y{constructor(){this._partials=new Float64Array(32),this._n=0}add(t){const n=this._partials;let e=0;for(let r=0;r<this._n&&r<32;r++){const i=n[r],o=t+i,a=Math.abs(t)<Math.abs(i)?t-(o-i):i-(o-t);a&&(n[e++]=a),t=o}return n[e]=t,this._n=e+1,this}valueOf(){const t=this._partials;let n,e,r,i=this._n,o=0;if(i>0){for(o=t[--i];i>0&&(n=o,e=t[--i],o=n+e,r=e-(o-n),!r););i>0&&(r<0&&t[i-1]<0||r>0&&t[i-1]>0)&&(e=2*r,n=o+e,e==n-o&&(o=n))}return o}}class InternMap extends Map{constructor(t,n=m){if(super(),Object.defineProperties(this,{_intern:{value:new Map},_key:{value:n}}),null!=t)for(const[n,e]of t)this.set(n,e)}get(t){return super.get(v(this,t))}has(t){return super.has(v(this,t))}set(t,n){return super.set(_(this,t),n)}delete(t){return super.delete(b(this,t))}}class InternSet extends Set{constructor(t,n=m){if(super(),Object.defineProperties(this,{_intern:{value:new Map},_key:{value:n}}),null!=t)for(const n of t)this.add(n)}has(t){return super.has(v(this,t))}add(t){return super.add(_(this,t))}delete(t){return super.delete(b(this,t))}}function v({_intern:t,_key:n},e){const r=n(e);return t.has(r)?t.get(r):e}function _({_intern:t,_key:n},e){const r=n(e);return t.has(r)?t.get(r):(t.set(r,e),e)}function b({_intern:t,_key:n},e){const r=n(e);return t.has(r)&&(e=t.get(r),t.delete(r)),e}function m(t){return null!==t&&"object"==typeof t?t.valueOf():t}function x(t){return t}function w(t,...n){return k(t,x,x,n)}function M(t,...n){return k(t,Array.from,x,n)}function A(t,n){for(let e=1,r=n.length;e<r;++e)t=t.flatMap((t=>t.pop().map((([n,e])=>[...t,n,e]))));return t}function T(t,n,...e){return k(t,x,n,e)}function S(t,n,...e){return k(t,Array.from,n,e)}function E(t){if(1!==t.length)throw new Error("duplicate key");return t[0]}function k(t,n,e,r){return function t(i,o){if(o>=r.length)return e(i);const a=new InternMap,u=r[o++];let c=-1;for(const t of i){const n=u(t,++c,i),e=a.get(n);e?e.push(t):a.set(n,[t])}for(const[n,e]of a)a.set(n,t(e,o));return n(a)}(t,0)}function N(t,n){return Array.from(n,(n=>t[n]))}function C(t,...n){if("function"!=typeof t[Symbol.iterator])throw new TypeError("values is not iterable");t=Array.from(t);let[e]=n;if(e&&2!==e.length||n.length>1){const r=Uint32Array.from(t,((t,n)=>n));return n.length>1?(n=n.map((n=>t.map(n))),r.sort(((t,e)=>{for(const r of n){const n=z(r[t],r[e]);if(n)return n}}))):(e=t.map(e),r.sort(((t,n)=>z(e[t],e[n])))),N(t,r)}return t.sort(P(e))}function P(t=n){if(t===n)return z;if("function"!=typeof t)throw new TypeError("compare is not a function");return(n,e)=>{const r=t(n,e);return r||0===r?r:(0===t(e,e))-(0===t(n,n))}}function z(t,n){return(null==t||!(t>=t))-(null==n||!(n>=n))||(t<n?-1:t>n?1:0)}var D=Array.prototype.slice;function R(t){return()=>t}var F=Math.sqrt(50),q=Math.sqrt(10),O=Math.sqrt(2);function U(t,n,e){var r,i,o,a,u=-1;if(e=+e,(t=+t)===(n=+n)&&e>0)return[t];if((r=n<t)&&(i=t,t=n,n=i),0===(a=I(t,n,e))||!isFinite(a))return[];if(a>0){let e=Math.round(t/a),r=Math.round(n/a);for(e*a<t&&++e,r*a>n&&--r,o=new Array(i=r-e+1);++u<i;)o[u]=(e+u)*a}else{a=-a;let e=Math.round(t*a),r=Math.round(n*a);for(e/a<t&&++e,r/a>n&&--r,o=new Array(i=r-e+1);++u<i;)o[u]=(e+u)/a}return r&&o.reverse(),o}function I(t,n,e){var r=(n-t)/Math.max(0,e),i=Math.floor(Math.log(r)/Math.LN10),o=r/Math.pow(10,i);return i>=0?(o>=F?10:o>=q?5:o>=O?2:1)*Math.pow(10,i):-Math.pow(10,-i)/(o>=F?10:o>=q?5:o>=O?2:1)}funLine truncated
|
||||
@@ -0,0 +1,103 @@
|
||||
// Dimensions of chart.
|
||||
let margin = { top: 20, right: 10, bottom: 50, left: 45 },
|
||||
// width = parseInt(d3.select('#chart').style('width'), 10) - margin.left - margin.right,
|
||||
width = 600 - margin.left - margin.right,
|
||||
height = 750 - margin.top - margin.bottom;
|
||||
|
||||
// Start SVG
|
||||
let svg = d3.select("#chart").append("svg")
|
||||
.attr("width", width + margin.left + margin.right)
|
||||
.attr("height", height + margin.top + margin.bottom)
|
||||
.append("g")
|
||||
.attr("transform", "translate(" + margin.left + "," + margin.top + ")");
|
||||
|
||||
// Scales: x and y
|
||||
let x = d3.scaleLinear()
|
||||
// .domain([0, 6])
|
||||
.domain([3, 6])
|
||||
.range([0, width]);
|
||||
let y = d3.scaleLinear()
|
||||
// .domain([0, 6])
|
||||
.domain([2, 6])
|
||||
.range([height, 0]);
|
||||
|
||||
// Point color
|
||||
let ptcolor = "#5a8171";
|
||||
|
||||
|
||||
|
||||
// x-axis
|
||||
let xAxis = d3.axisBottom(x)
|
||||
// .ticks(7)
|
||||
.ticks(4)
|
||||
.tickSize(-height-8)
|
||||
.tickPadding(5);
|
||||
let xAxisEl = svg.append("g")
|
||||
.attr("class", "x axis bottom")
|
||||
.attr("transform", "translate(0,"+(height+8)+")");
|
||||
xAxisEl.append("text")
|
||||
.attr("class", "axistitle")
|
||||
.attr("text-anchor", "start")
|
||||
.attr("x", 0).attr("y", 0)
|
||||
.attr("dx", "-.25em")
|
||||
.attr("dy", "2.5em")
|
||||
.text("Meaningfulness Score Average");
|
||||
xAxisEl.call(xAxis);
|
||||
|
||||
|
||||
// y-axis
|
||||
let yAxis = d3.axisLeft(y)
|
||||
// .ticks(7)
|
||||
.ticks(5)
|
||||
.tickSize(-width-8)
|
||||
.tickPadding(5);
|
||||
var yAxisEl = svg.append("g")
|
||||
.attr("class", "y axis left")
|
||||
.attr("transform", "translate("+(-8)+",0)");
|
||||
yAxisEl.append("text")
|
||||
.attr("class", "axistitle")
|
||||
.attr("x", 0).attr("y", 0)
|
||||
.attr("dx", "4px")
|
||||
.attr("dy", "-2em")
|
||||
.style("text-anchor", "end")
|
||||
.attr("transform", "rotate(-90)")
|
||||
.text("Happiness Score Average");
|
||||
yAxisEl.call(yAxis);
|
||||
|
||||
let activities;
|
||||
let circle;
|
||||
|
||||
// Load data
|
||||
const activitiesData = Promise.all([
|
||||
d3.tsv("data/act_means.tsv", d3.autoType)
|
||||
]);
|
||||
activitiesData.then(function(data) {
|
||||
|
||||
activities = data[0];
|
||||
console.log(activities);
|
||||
|
||||
// Initialize chart now that data is loaded.
|
||||
initChart();
|
||||
});
|
||||
|
||||
|
||||
function initChart() {
|
||||
// Circle for each node.
|
||||
circle = svg.append("g")
|
||||
.selectAll("circle")
|
||||
.data(activities)
|
||||
.join("circle")
|
||||
.attr("id", d => "circle"+d.activity)
|
||||
.attr("cx", d => x(d.meaning_mean))
|
||||
.attr("cy", d => y(d.schappy_mean))
|
||||
.attr("fill", ptcolor)
|
||||
// .attr("fill-opacity", .8)
|
||||
.attr("r", 3);
|
||||
// .attr("stroke", "#fff");
|
||||
}
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
@@ -0,0 +1,65 @@
|
||||
/* #Reset & Basics (Inspired by E. Meyers)
|
||||
================================================== */
|
||||
html, body, div, span, applet, object, iframe, h1, h2, h3, h4, h5, h6, p, blockquote, pre, a, abbr, acronym, address, big, cite, code, del, dfn, em, img, ins, kbd, q, s, samp, small, strike, strong, sub, sup, tt, var, b, u, i, center, dl, dt, dd, ol, ul, li, fieldset, form, label, legend, table, caption, tbody, tfoot, thead, tr, th, td, article, aside, canvas, details, embed, figure, figcaption, footer, header, hgroup, menu, nav, output, ruby, section, summary, time, mark, audio, video {
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
border: 0;
|
||||
font-size: 100%;
|
||||
font: inherit;
|
||||
vertical-align: baseline; }
|
||||
article, aside, details, figcaption, figure, footer, header, hgroup, menu, nav, section {
|
||||
display: block; }
|
||||
body {
|
||||
line-height: 1; }
|
||||
ol, ul {
|
||||
list-style: none; }
|
||||
blockquote, q {
|
||||
quotes: none; }
|
||||
blockquote:before, blockquote:after,
|
||||
q:before, q:after {
|
||||
content: '';
|
||||
content: none; }
|
||||
table {
|
||||
border-collapse: collapse;
|
||||
border-spacing: 0; }
|
||||
|
||||
|
||||
/* Main layout
|
||||
============================ */
|
||||
|
||||
#main-wrapper {
|
||||
width: 600px;
|
||||
margin: 40px auto;
|
||||
}
|
||||
h1 {
|
||||
font-family: Georgia, serif;
|
||||
font-size: 1.45em;
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
|
||||
/* Chart
|
||||
============================ */
|
||||
|
||||
#chart {
|
||||
margin: 0 auto;
|
||||
}
|
||||
.axis text {
|
||||
font-family: "Courier New", Courier, monospace;
|
||||
font-size: .8rem;
|
||||
}
|
||||
.axis .axistitle {
|
||||
text-transform: uppercase;
|
||||
fill: #333;
|
||||
font-size: .8rem;
|
||||
}
|
||||
.axis path,
|
||||
.axis line {
|
||||
fill: none;
|
||||
stroke: #ccc;
|
||||
stroke-width: 1px;
|
||||
shape-rendering: crispEdges;
|
||||
}
|
||||
.x.axis path, .y.axis path {
|
||||
display: none;
|
||||
}
|
||||
+74
@@ -0,0 +1,74 @@
|
||||
"Column Name","Label"
|
||||
"GEO_ID","Geography"
|
||||
"NAME","Geographic Area Name"
|
||||
"P8_001N"," !!Total:"
|
||||
"P8_002N"," !!Total:!!Population of one race:"
|
||||
"P8_003N"," !!Total:!!Population of one race:!!White alone"
|
||||
"P8_004N"," !!Total:!!Population of one race:!!Black or African American alone"
|
||||
"P8_005N"," !!Total:!!Population of one race:!!American Indian and Alaska Native alone"
|
||||
"P8_006N"," !!Total:!!Population of one race:!!Asian alone"
|
||||
"P8_007N"," !!Total:!!Population of one race:!!Native Hawaiian and Other Pacific Islander alone"
|
||||
"P8_008N"," !!Total:!!Population of one race:!!Some Other Race alone"
|
||||
"P8_009N"," !!Total:!!Population of two or more races:"
|
||||
"P8_010N"," !!Total:!!Population of two or more races:!!Population of two races:"
|
||||
"P8_011N"," !!Total:!!Population of two or more races:!!Population of two races:!!White; Black or African American"
|
||||
"P8_012N"," !!Total:!!Population of two or more races:!!Population of two races:!!White; American Indian and Alaska Native"
|
||||
"P8_013N"," !!Total:!!Population of two or more races:!!Population of two races:!!White; Asian"
|
||||
"P8_014N"," !!Total:!!Population of two or more races:!!Population of two races:!!White; Native Hawaiian and Other Pacific Islander"
|
||||
"P8_015N"," !!Total:!!Population of two or more races:!!Population of two races:!!White; Some Other Race"
|
||||
"P8_016N"," !!Total:!!Population of two or more races:!!Population of two races:!!Black or African American; American Indian and Alaska Native"
|
||||
"P8_017N"," !!Total:!!Population of two or more races:!!Population of two races:!!Black or African American; Asian"
|
||||
"P8_018N"," !!Total:!!Population of two or more races:!!Population of two races:!!Black or African American; Native Hawaiian and Other Pacific Islander"
|
||||
"P8_019N"," !!Total:!!Population of two or more races:!!Population of two races:!!Black or African American; Some Other Race"
|
||||
"P8_020N"," !!Total:!!Population of two or more races:!!Population of two races:!!American Indian and Alaska Native; Asian"
|
||||
"P8_021N"," !!Total:!!Population of two or more races:!!Population of two races:!!American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander"
|
||||
"P8_022N"," !!Total:!!Population of two or more races:!!Population of two races:!!American Indian and Alaska Native; Some Other Race"
|
||||
"P8_023N"," !!Total:!!Population of two or more races:!!Population of two races:!!Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P8_024N"," !!Total:!!Population of two or more races:!!Population of two races:!!Asian; Some Other Race"
|
||||
"P8_025N"," !!Total:!!Population of two or more races:!!Population of two races:!!Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P8_026N"," !!Total:!!Population of two or more races:!!Population of three races:"
|
||||
"P8_027N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; Black or African American; American Indian and Alaska Native"
|
||||
"P8_028N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; Black or African American; Asian"
|
||||
"P8_029N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; Black or African American; Native Hawaiian and Other Pacific Islander"
|
||||
"P8_030N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; Black or African American; Some Other Race"
|
||||
"P8_031N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; American Indian and Alaska Native; Asian"
|
||||
"P8_032N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander"
|
||||
"P8_033N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; American Indian and Alaska Native; Some Other Race"
|
||||
"P8_034N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P8_035N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; Asian; Some Other Race"
|
||||
"P8_036N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P8_037N"," !!Total:!!Population of two or more races:!!Population of three races:!!Black or African American; American Indian and Alaska Native; Asian"
|
||||
"P8_038N"," !!Total:!!Population of two or more races:!!Population of three races:!!Black or African American; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander"
|
||||
"P8_039N"," !!Total:!!Population of two or more races:!!Population of three races:!!Black or African American; American Indian and Alaska Native; Some Other Race"
|
||||
"P8_040N"," !!Total:!!Population of two or more races:!!Population of three races:!!Black or African American; Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P8_041N"," !!Total:!!Population of two or more races:!!Population of three races:!!Black or African American; Asian; Some Other Race"
|
||||
"P8_042N"," !!Total:!!Population of two or more races:!!Population of three races:!!Black or African American; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P8_043N"," !!Total:!!Population of two or more races:!!Population of three races:!!American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P8_044N"," !!Total:!!Population of two or more races:!!Population of three races:!!American Indian and Alaska Native; Asian; Some Other Race"
|
||||
"P8_045N"," !!Total:!!Population of two or more races:!!Population of three races:!!American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P8_046N"," !!Total:!!Population of two or more races:!!Population of three races:!!Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P8_047N"," !!Total:!!Population of two or more races:!!Population of four races:"
|
||||
"P8_048N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; Black or African American; American Indian and Alaska Native; Asian"
|
||||
"P8_049N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; Black or African American; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander"
|
||||
"P8_050N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; Black or African American; American Indian and Alaska Native; Some Other Race"
|
||||
"P8_051N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; Black or African American; Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P8_052N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; Black or African American; Asian; Some Other Race"
|
||||
"P8_053N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; Black or African American; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P8_054N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P8_055N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; American Indian and Alaska Native; Asian; Some Other Race"
|
||||
"P8_056N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P8_057N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P8_058N"," !!Total:!!Population of two or more races:!!Population of four races:!!Black or African American; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P8_059N"," !!Total:!!Population of two or more races:!!Population of four races:!!Black or African American; American Indian and Alaska Native; Asian; Some Other Race"
|
||||
"P8_060N"," !!Total:!!Population of two or more races:!!Population of four races:!!Black or African American; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P8_061N"," !!Total:!!Population of two or more races:!!Population of four races:!!Black or African American; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P8_062N"," !!Total:!!Population of two or more races:!!Population of four races:!!American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P8_063N"," !!Total:!!Population of two or more races:!!Population of five races:"
|
||||
"P8_064N"," !!Total:!!Population of two or more races:!!Population of five races:!!White; Black or African American; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P8_065N"," !!Total:!!Population of two or more races:!!Population of five races:!!White; Black or African American; American Indian and Alaska Native; Asian; Some Other Race"
|
||||
"P8_066N"," !!Total:!!Population of two or more races:!!Population of five races:!!White; Black or African American; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P8_067N"," !!Total:!!Population of two or more races:!!Population of five races:!!White; Black or African American; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P8_068N"," !!Total:!!Population of two or more races:!!Population of five races:!!White; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P8_069N"," !!Total:!!Population of two or more races:!!Population of five races:!!Black or African American; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P8_070N"," !!Total:!!Population of two or more races:!!Population of six races:"
|
||||
"P8_071N"," !!Total:!!Population of two or more races:!!Population of six races:!!White; Black or African American; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
|
File diff suppressed because it is too large.
Load diff
+17
@@ -0,0 +1,17 @@
|
||||
=============================================================================================================
|
||||
TABLE INFO
|
||||
=============================================================================================================
|
||||
|
||||
ID: DECENNIALDHC2020.P8
|
||||
Title: RACE
|
||||
|
||||
=============================================================================================================
|
||||
NOTES
|
||||
=============================================================================================================
|
||||
|
||||
To protect respondent confidentiality, data have undergone disclosure avoidance methods which add "statistical noise" - small, random additions or subtractions - to the data so that no one can reliably link the published data to a specific person or household. The Census Bureau encourages data users to aggregate small populations and geographies to improve accuracy and diminish implausible results.<br/><br/>
|
||||
|
||||
Source: U.S. Census Bureau, 2020 Census Demographic and Housing Characteristics File (DHC)<br/><br/>
|
||||
|
||||
Note: For information on data collection, confidentiality protection, nonsampling error, subject definitions, and guidance on using the data, visit the <a href="https://www.census.gov/programs-surveys/decennial-census/technical-documentation/complete-technical-documents.2020.html#dhc-and-dp">2020 Census Demographic and Housing Characteristics File (DHC) Technical Documentation</a> webpage.<br/><br/>
|
||||
|
||||
@@ -0,0 +1,53 @@
|
||||
"GEO_ID","NAME","P1_001N","P1_002N","P1_003N","P1_004N","P1_005N","P1_006N","P1_007N","P1_008N","P1_009N","P1_010N","P1_011N","P1_012N","P1_013N","P1_014N","P1_015N","P1_016N","P1_017N","P1_018N","P1_019N","P1_020N","P1_021N","P1_022N","P1_023N","P1_024N","P1_025N","P1_026N","P1_027N","P1_028N","P1_029N","P1_030N","P1_031N","P1_032N","P1_033N","P1_034N","P1_035N","P1_036N","P1_037N","P1_038N","P1_039N","P1_040N","P1_041N","P1_042N","P1_043N","P1_044N","P1_045N","P1_046N","P1_047N","P1_048N","P1_049N","P1_050N","P1_051N","P1_052N","P1_053N","P1_054N","P1_055N","P1_056N","P1_057N","P1_058N","P1_059N","P1_060N","P1_061N","P1_062N","P1_063N","P1_064N","P1_065N","P1_066N","P1_067N","P1_068N","P1_069N","P1_070N","P1_071N"
|
||||
"0400000US01","Alabama","5024279","4767326","3220452","1296162","33625","76660","2984","137443","256953","243473","45429","79559","18510","1449","80617","6301","2049","492","5421","266","77","1941","567","562","233","12093","4493","972","172","1441","912","138","2194","681","429","78","124","13","146","145","86","27","12","6","7","17","1191","304","64","516","80","47","4","35","48","7","25","31","7","4","15","4","187","89","78","13","0","5","2","9","9"
|
||||
"0400000US02","Alaska","733391","643867","435392","21898","111575","44032","12698","18272","89524","81221","5987","38129","9815","1599","17735","2039","547","319","948","1215","607","622","1349","255","55","7371","1988","402","121","361","1795","344","878","837","204","31","80","31","41","58","21","15","90","28","15","31","822","206","47","160","47","17","13","217","49","7","36","4","3","0","5","11","97","44","29","4","4","14","2","13","13"
|
||||
"0400000US04","Arizona","7151502","6154696","4322337","339150","319512","257430","16397","899870","996806","948897","60610","84795","62979","7025","687131","7977","4322","864","11926","1492","570","10400","4226","3696","884","43514","7360","3178","518","5839","2296","428","13994","3924","3882","457","254","87","479","218","190","49","117","111","36","97","3885","732","115","1450","225","246","35","299","410","50","217","35","27","13","13","18","440","174","215","12","7","28","4","70","70"
|
||||
"0400000US05","Arkansas","3011524","2797949","2114512","453783","27177","51839","14533","136105","213575","203299","28910","76042","11859","1281","75317","3149","865","214","2817","199","101","1347","502","522","174","9447","3600","466","101","1050","831","104","2079","441","358","73","63","9","134","81","22","2","8","11","0","14","699","183","33","299","14","19","0","51","47","14","13","7","7","4","8","0","118","60","38","2","15","2","1","12","12"
|
||||
"0400000US06","California","39538223","33777988","16296122","2237044","631016","6085947","157263","8370596","5760235","5380042","257897","384596","624936","45390","3626370","37342","51784","8765","88929","13189","2563","113787","51357","61163","11974","341027","41343","24099","3338","32938","22082","3308","119441","31003","42261","4250","2582","555","3381","2638","2603","606","960","1465","316","1858","34609","6504","981","11879","1951","2736","336","2531","4290","421","2082","260","282","77","170","109","4107","1345","2002","236","208","284","32","450","450"
|
||||
"0400000US08","Colorado","5773714","5066044","4082927","234828","74129","199827","10287","464046","707670","665645","48200","91231","63039","4943","426665","5076","3636","611","7619","851","218","8397","2431","2183","545","38117","6940","2747","337","4070","2331","325","14157","3105","2553","331","265","63","348","170","129","25","68","72","14","67","3437","688","136","1346","188","241","34","282","300","39","131","20","7","13","2","10","423","195","152","30","10","31","5","48","48"
|
||||
"0400000US09","Connecticut","3605944","3273040","2395128","388675","16051","172455","1598","299133","332904","313228","36315","25191","24100","853","191978","4947","2021","469","20121","356","87","3197","639","1839","1115","16883","4629","1111","75","5315","449","36","2516","462","975","119","152","20","641","35","177","49","8","36","21","57","2583","310","62","1879","45","130","18","39","54","5","19","10","5","0","6","1","185","76","87","8","2","11","1","25","25"
|
||||
"0400000US10","Delaware","989948","913430","597763","218899","5148","42699","412","48509","76518","71461","14610","9586","5480","310","32669","2662","911","147","3811","107","12","613","132","310","101","4488","1842","434","25","841","177","31","546","160","157","27","74","29","88","26","10","2","4","4","0","11","522","123","8","272","18","24","16","10","9","0","13","4","4","0","17","4","42","11","19","0","12","0","0","5","5"
|
||||
"0400000US11","District of Columbia","689545","633468","273194","285810","3193","33545","432","37294","56077","51147","7543","2212","8646","247","23425","2334","1340","112","3856","70","20","767","190","300","85","4262","1379","394","23","792","88","3","781","153","273","15","63","39","127","32","49","27","2","0","4","18","613","129","8","354","14","51","1","1","21","3","16","9","3","0","3","0","51","20","18","0","4","4","5","4","4"
|
||||
"0400000US12","Florida","21538187","17986115","12422961","3246381","94795","643682","14014","1564282","3552072","3428042","200545","192576","122838","7435","2694902","19086","20991","4320","127918","1859","393","14987","4389","11730","4073","106458","19129","9588","862","32695","4204","537","18348","3696","9942","854","541","132","2680","826","1589","322","93","177","35","208","16177","1800","244","10372","344","1751","137","296","547","63","271","81","118","14","116","23","1263","353","719","90","40","25","36","132","132"
|
||||
"0400000US13","Georgia","10711908","9968000","5555483","3320513","50618","479028","7299","555059","743908","698142","115782","106685","55138","3094","333782","19655","11481","1812","36334","1007","147","7360","1680","3398","787","40179","13019","4196","462","7178","1892","242","6817","1473","1931","185","490","101","1017","397","504","110","40","42","6","77","4971","1173","159","2453","154","352","40","176","191","30","71","61","40","13","56","2","551","193","270","22","11","22","33","65","65"
|
||||
"0400000US15","Hawaii","1455271","1087142","333261","23417","4370","541902","157445","26747","368129","231504","5615","11279","71907","34670","20218","800","2779","1736","929","1010","930","439","75347","2842","1003","118847","1511","1433","911","576","4244","2019","1147","99170","2728","1076","218","99","67","1245","83","32","1177","53","16","1042","15969","666","302","340","2156","116","62","8521","310","83","3112","216","24","3","44","14","1733","998","138","25","139","406","27","76","76"
|
||||
"0400000US16","Idaho","1839106","1685901","1510360","15726","25621","26836","3726","103632","153205","145443","7906","32995","15980","2696","81703","433","236","85","625","203","104","1365","591","384","137","6992","1022","330","85","575","693","162","2248","1156","494","109","14","6","29","8","16","3","18","3","5","16","649","100","27","180","48","27","6","109","46","10","45","22","13","0","7","9","82","38","18","12","6","5","3","39","39"
|
||||
"0400000US17","Illinois","12812508","11667524","7868227","1808271","96498","754878","4501","1135149","1144984","1087260","111307","107871","90923","3101","697568","12187","6283","716","23028","1470","168","23158","2673","5233","1574","51574","11661","2761","286","8170","2026","187","18641","1694","3603","255","391","103","904","227","286","76","27","113","43","120","5396","963","122","3171","117","294","16","136","296","12","130","33","34","14","42","16","670","301","301","35","14","4","15","84","84"
|
||||
"0400000US18","Indiana","6785528","6348802","5241795","648513","26086","167959","3137","261312","436726","414856","81420","90589","31442","2300","184637","4870","2177","381","8306","342","58","2919","3589","1443","383","19796","7003","1615","225","3161","968","177","4218","871","851","117","66","19","227","76","75","41","9","18","5","54","1784","430","91","835","59","67","17","80","77","20","40","27","12","1","15","13","262","149","80","16","7","2","8","28","28"
|
||||
"0400000US19","Iowa","3190369","3011086","2694521","131972","14486","75629","5758","88720","179283","170730","31415","33145","15391","1121","81757","1430","757","94","1860","180","40","1039","1816","577","108","7817","2828","596","135","1007","416","42","1561","529","350","62","52","13","76","68","45","12","11","5","4","5","609","140","42","237","24","34","16","36","41","4","19","3","0","0","7","6","111","60","29","3","6","2","11","16","16"
|
||||
"0400000US20","Kansas","2937880","2657373","2222462","168809","30995","86273","3412","145422","280507","265719","36935","63803","18823","1600","132329","3934","1261","269","2927","246","71","1918","795","633","175","13554","4878","979","163","1690","934","129","2994","714","570","66","90","36","163","49","34","14","12","16","0","23","1100","316","47","415","53","49","10","87","53","7","31","10","5","6","1","10","103","52","34","6","4","2","5","31","31"
|
||||
"0400000US21","Kentucky","4505836","4260996","3711254","362417","12801","74426","3681","96417","244840","232500","55381","66051","17238","1449","78941","2750","1258","335","5572","185","51","1140","1366","600","183","11103","4202","1014","165","1561","723","117","1892","544","450","70","74","23","115","71","27","6","9","12","6","22","1068","274","49","421","66","68","8","66","55","0","21","12","18","5","5","0","143","57","50","10","14","7","5","26","26"
|
||||
"0400000US22","Louisiana","4657757","4384380","2657652","1464023","31657","86438","1911","142699","273377","255214","43631","50194","17001","1278","116354","7332","2323","419","13305","280","69","1601","504","660","263","15833","4955","985","121","2995","840","117","3407","500","819","133","137","40","374","170","128","46","21","13","7","25","2083","339","46","1250","64","67","30","58","82","8","27","38","21","1","47","5","214","82","95","3","11","15","8","33","33"
|
||||
"0400000US23","Maine","1362359","1297649","1237041","25752","7885","16798","443","9730","64710","61608","7612","23177","7074","430","21646","272","163","41","651","86","16","141","153","123","23","2808","846","194","21","444","221","59","483","250","173","20","17","11","24","5","17","2","7","4","2","8","231","26","13","94","17","13","2","21","22","3","5","7","4","0","3","1","63","34","7","2","3","10","7","0","0"
|
||||
"0400000US24","Maryland","6177224","5695323","3007874","1820472","31845","420944","3247","410941","481901","444556","78371","48367","55237","1985","194761","15874","9381","1117","25559","810","112","8218","1403","2746","615","32617","11071","3651","330","5388","1356","111","5477","1158","1944","138","418","96","592","210","444","82","26","67","20","38","4231","1067","109","2187","111","316","35","92","173","29","32","19","33","5","19","4","439","181","200","23","25","1","9","58","58"
|
||||
"0400000US25","Massachusetts","7029917","6421050","4896037","494029","24018","507934","2301","496731","608867","571923","56449","41151","58164","1794","310903","6011","3375","648","80988","633","109","5177","994","3405","2122","32278","6372","1794","160","13544","908","99","4085","1030","1849","204","185","22","1155","106","473","147","20","36","22","67","4310","443","49","3004","67","348","63","37","103","16","93","10","25","0","48","4","326","136","152","23","10","5","0","30","30"
|
||||
"0400000US26","Michigan","10077331","9442016","7444974","1376579","61261","334300","3051","221851","635315","599811","115790","145036","60656","2906","240916","12023","3871","566","11229","735","102","2792","1108","1732","349","32500","13348","2305","308","4441","1797","244","5728","1403","1680","148","279","45","383","128","131","32","32","26","2","40","2609","699","131","1102","84","133","33","111","120","8","87","35","31","7","24","4","338","156","128","18","18","10","8","57","57"
|
||||
"0400000US27","Minnesota","5706494","5360773","4423146","398434","68641","299190","2918","168444","345721","324275","57953","65819","45265","1882","133575","5029","2674","313","4770","790","104","2660","1477","1609","355","19416","7897","1842","232","2123","1247","144","3123","1153","877","95","126","57","187","65","91","20","38","34","7","58","1755","441","71","763","70","158","9","103","65","1","24","21","18","5","6","0","244","91","116","13","15","4","5","31","31"
|
||||
"0400000US28","Mississippi","2961279","2850547","1658893","1084481","16450","32709","1154","56860","110732","103917","25992","27934","8293","603","31331","3877","1149","273","3095","128","28","571","251","284","108","5995","2320","496","63","735","411","58","991","221","246","30","75","21","134","92","60","4","7","8","2","21","676","172","54","253","21","28","4","44","14","5","9","11","16","7","36","2","119","47","38","17","8","0","9","25","25"
|
||||
"0400000US29","Missouri","6154913","5741742","4740335","699840","30518","133377","9730","127942","413171","390923","68493","128301","34538","3424","135671","7134","2313","542","6030","352","98","1682","1180","937","228","20344","7562","1634","313","2472","1618","280","3723","1129","764","165","154","46","236","101","54","16","23","15","1","38","1598","434","95","663","75","64","19","99","65","7","33","16","9","5","6","8","281","135","113","6","15","9","3","25","25"
|
||||
"0400000US30","Montana","1084225","1012950","916524","5484","67612","8300","941","14089","71275","67557","4608","29080","6430","916","24502","623","140","30","211","202","96","322","274","101","22","3410","959","161","41","214","472","112","773","434","121","37","1","6","5","7","4","13","27","11","1","11","256","39","14","83","14","4","4","34","27","5","3","6","5","6","7","5","40","13","17","3","0","4","3","12","12"
|
||||
"0400000US31","Nebraska","1961504","1817341","1538052","96535","23102","52951","1534","105167","144163","136456","19503","23079","12180","826","73788","1882","577","126","1607","167","42","1695","479","407","98","6979","2328","523","81","795","393","52","1745","462","304","43","49","5","98","41","6","15","5","8","9","17","624","124","25","241","56","33","7","24","70","11","13","2","3","1","10","4","84","34","23","6","8","4","9","20","20"
|
||||
"0400000US32","Nevada","3104614","2670605","1588463","304739","43932","272703","25011","435757","434009","400557","34520","36364","45769","6098","239236","4265","5716","1613","9242","738","262","4814","8079","3049","792","29850","4309","2794","575","3260","1735","366","5503","6574","2393","361","260","86","328","535","256","80","106","73","16","240","3159","540","136","792","393","197","45","472","179","38","262","41","29","11","24","0","400","184","127","7","48","31","3","43","43"
|
||||
"0400000US33","New Hampshire","1377529","1299787","1216203","20127","3031","35871","453","24102","77742","73876","8076","19548","9151","540","33530","322","180","64","1685","67","7","223","194","203","86","3465","992","334","29","735","260","28","559","191","178","36","1","24","39","17","16","4","2","11","3","6","338","43","3","200","11","20","1","15","18","2","9","3","1","2","9","1","59","26","11","14","0","3","5","4","4"
|
||||
"0400000US34","New Jersey","9288994","8385500","5112280","1219770","51186","950090","3533","1048641","903494","852673","70790","40811","65045","1740","559309","12399","7604","1168","65449","1842","143","14030","2097","7251","2995","43150","10254","2929","217","13263","1016","100","7374","967","3645","265","374","51","1323","139","734","113","30","158","56","142","7058","850","149","4730","79","633","62","46","244","26","112","18","39","13","38","19","546","157","310","22","17","29","11","67","67"
|
||||
"0400000US35","New Mexico","2117522","1695276","1078937","45904","212241","37469","2093","318632","422246","405338","10509","30305","11482","1097","337315","2488","645","130","3049","643","214","5425","668","1063","305","15498","1949","443","55","1807","737","131","7896","555","1226","171","58","21","171","35","54","13","31","60","35","50","1230","171","27","546","43","71","20","102","124","16","61","19","6","7","1","16","152","32","84","16","4","13","3","28","28"
|
||||
"0400000US36","New York","20201249","18433786","11143349","2986172","149690","1933127","10815","2210633","1767463","1649229","175686","113950","148927","3890","840481","31562","21450","3274","226733","5958","564","33617","6314","28694","8129","99616","24378","6334","504","31594","2154","258","15296","2222","6526","459","1059","171","3838","426","2558","476","145","548","156","514","16806","2049","232","11366","252","1429","92","135","430","37","240","92","210","29","120","93","1623","555","873","99","26","25","45","189","189"
|
||||
"0400000US37","North Carolina","10439388","9727667","6488459","2140217","130032","343051","8518","617390","711721","664545","114798","124955","57170","3574","294386","23110","6862","1462","24413","983","249","7175","1842","2749","817","41836","16307","3410","458","6524","2035","261","6802","1742","1731","204","454","138","936","298","244","92","64","34","15","87","4728","1102","153","2406","160","285","32","178","193","23","81","31","20","8","31","25","540","280","198","25","22","10","5","72","72"
|
||||
"0400000US38","North Dakota","779094","737154","645938","26783","38914","13213","924","11382","41940","39726","5120","14414","4048","415","13753","600","251","39","394","98","50","225","183","70","66","1968","645","155","34","212","173","36","347","166","76","11","9","7","29","21","7","1","11","11","0","17","192","35","8","62","11","2","3","22","22","0","0","3","10","1","6","7","49","14","10","6","16","3","0","5","5"
|
||||
"0400000US39","Ohio","11799448","11118076","9080688","1478781","30720","298509","5034","224344","681372","638388","157685","157622","59329","3367","217778","12938","4679","811","17084","637","99","2590","1312","1861","596","38520","17738","3162","488","5720","1974","243","4779","1669","1190","162","310","88","548","178","126","31","36","33","15","30","3942","1049","231","1893","150","180","12","122","138","13","52","30","29","18","14","11","461","219","153","29","37","3","20","61","61"
|
||||
"0400000US40","Oklahoma","3959353","3451195","2514885","289961","332791","90949","8608","214001","508158","476591","46341","251170","21338","2100","124450","19104","1726","420","3753","974","357","3132","824","665","237","29533","15616","1200","227","1956","2926","426","4845","921","541","75","202","58","295","61","41","13","77","21","7","25","1846","460","105","778","74","72","5","181","82","13","32","13","10","5","15","1","167","107","42","5","6","1","6","21","21"
|
||||
"0400000US41","Oregon","4237256","3793917","3169096","82655","62993","194538","19204","265431","443339","412968","32537","96929","59341","7738","198328","2285","1647","519","2794","805","332","3987","3737","1543","446","27366","5185","1771","382","2242","2840","643","6714","4854","1724","271","141","63","159","101","66","20","75","37","3","75","2568","446","98","842","161","115","19","453","229","22","141","17","11","10","4","0","385","191","116","13","30","35","0","52","52"
|
||||
"0400000US42","Pennsylvania","13002700","12228216","9750687","1423169","31052","510501","4276","508531","774484","726012","136716","107274","69760","3360","337578","14495","6188","1025","36170","858","164","5426","1692","3256","2050","42490","15669","3153","450","9963","1483","225","5306","1541","1891","235","328","92","1289","195","348","124","22","55","45","76","5454","1054","203","3296","118","316","55","96","119","27","71","26","42","0","26","5","435","195","195","22","15","4","4","93","93"
|
||||
"0400000US44","Rhode Island","1097379","995585","782920","62168","7385","38961","536","103615","101794","93292","9960","8317","7009","333","44471","2169","397","86","18100","98","32","1103","181","448","588","7427","1773","286","47","3143","142","39","712","149","243","64","37","12","514","44","109","45","5","25","26","12","994","113","19","711","19","63","14","4","13","9","4","3","7","10","5","0","69","13","36","8","2","10","0","12","12"
|
||||
"0400000US45","South Carolina","5118425","4820049","3243442","1280531","24303","90466","3431","177876","298376","280801","57455","62074","23180","1651","112478","7924","2859","554","8725","300","61","1688","774","790","288","15452","6080","1385","134","2280","928","125","2291","715","622","72","153","27","282","153","84","29","23","22","14","33","1775","364","70","821","110","101","17","112","57","18","42","21","14","3","18","7","292","125","113","15","19","14","6","56","56"
|
||||
"0400000US46","South Dakota","886667","840002","715336","17842","77748","13476","543","15057","46665","44190","5575","17783","3699","385","14479","940","163","26","323","165","58","332","133","86","43","2228","839","126","28","186","219","62","415","163","56","30","27","5","32","8","1","8","13","3","4","3","202","21","11","65","17","8","10","29","11","9","4","0","5","0","7","5","44","15","7","4","4","11","3","1","1"
|
||||
"0400000US47","Tennessee","6910840","6497942","4990938","1092948","28044","135615","4115","246282","412898","391747","71033","109625","31467","2453","153279","6326","2814","534","8615","347","104","2801","926","1082","341","19049","6873","1565","261","2599","1380","210","3407","1046","777","132","140","49","250","166","67","32","30","12","6","47","1832","466","82","770","79","113","12","112","83","16","36","25","6","8","16","8","250","107","108","12","14","5","4","20","20"
|
||||
"0400000US48","Texas","29145505","24011767","14609365","3552997","278948","1585480","33611","3951366","5133738","4966139","213221","321387","171466","11344","4040218","27070","18267","3622","71643","3305","609","55559","10559","14549","3320","151394","24321","8301","1030","25806","6421","883","58045","5929","13645","1276","753","158","2157","775","821","201","105","316","106","345","14376","2221","292","7383","511","1033","110","604","1316","115","490","101","88","5","73","34","1661","517","841","111","69","89","34","168","168"
|
||||
"0400000US49","Utah","3271616","2992603","2573413","40058","41644","80438","36930","220120","279013","261893","17096","31850","32648","12766","155296","888","744","651","2350","373","333","3090","2303","1054","451","15570","1520","702","369","1373","774","378","4847","3823","990","321","46","36","80","86","45","9","57","29","8","77","1368","125","52","533","123","58","6","207","115","35","77","11","7","8","1","10","174","54","63","17","4","31","5","8","8"
|
||||
"0400000US50","Vermont","643077","606051","577751","9034","2289","11549","181","5247","37026","35154","3637","13105","3882","203","13541","153","46","13","326","36","12","81","39","72","8","1656","575","92","27","283","132","21","276","81","79","24","5","7","9","10","9","4","4","3","4","11","169","41","6","72","14","6","1","6","6","4","2","4","2","1","4","0","41","19","13","0","1","6","2","6","6"
|
||||
"0400000US51","Virginia","8631393","7925686","5208856","1607581","40007","615436","7156","446650","705707","654932","111004","86898","105008","4119","284308","14934","10210","1255","21371","978","104","6852","3176","4062","653","44372","13505","5027","507","6748","2483","238","7356","2708","3246","186","494","98","633","463","367","71","31","54","41","116","5685","1326","157","2743","291","347","31","230","299","15","144","26","12","9","46","9","680","248","372","25","11","14","10","38","38"
|
||||
"0400000US53","Washington","7705281","6868622","5130920","307565","121468","730596","64933","513140","836659","770116","82193","138919","147299","15706","333489","6570","8676","2243","7734","2803","893","6295","11689","4451","1156","59396","11320","6658","1223","4725","6577","1179","10499","10336","3781","530","517","154","394","598","237","43","256","120","20","229","6331","1422","257","1715","684","355","63","906","421","45","323","79","24","5","18","14","710","346","209","39","55","48","13","106","106"
|
||||
"0400000US54","West Virginia","1793716","1708772","1610749","65813","3706","15109","476","12919","84944","80877","19578","30144","5443","462","22475","774","262","72","1128","53","36","127","140","144","39","3702","1701","297","67","463","260","44","480","193","89","28","20","4","17","13","7","0","7","2","6","4","303","65","9","109","31","10","4","32","12","3","7","4","9","2","5","1","47","21","25","0","0","0","1","15","15"
|
||||
"0400000US55","Wisconsin","5893718","5534184","4737545","376256","60428","175702","2199","182054","359534","341196","53543","64697","32014","2004","172629","4343","1586","199","5261","467","102","2178","892","1011","270","16568","5601","1077","164","2606","818","133","3769","963","760","98","106","5","278","55","52","24","3","26","13","17","1606","348","46","880","55","57","17","43","85","22","29","5","16","1","2","0","151","72","55","8","5","4","7","13","13"
|
||||
"0400000US56","Wyoming","576851","533378","488374","5232","13898","5212","579","20083","43473","41250","3059","11482","3108","481","21954","165","75","26","220","53","33","356","131","91","16","2024","375","120","35","145","161","43","692","232","117","23","10","2","33","2","12","6","4","11","0","1","163","35","9","32","12","3","13","21","12","9","9","4","3","1","0","0","33","11","14","2","0","4","2","3","3"
|
||||
"0400000US72","Puerto Rico","3285874","1650083","560592","228711","17870","4001","593","838316","1635791","1539017","24479","2586","755","191","1264479","2573","291","78","226074","149","56","13914","46","1075","2271","63117","9846","196","11","38672","42","12","3568","32","475","265","20","3","8953","26","772","98","13","45","51","17","33261","91","18","32529","9","311","44","11","35","40","64","1","51","13","33","11","362","42","234","64","3","12","7","34","34"
|
||||
|
+73
@@ -0,0 +1,73 @@
|
||||
"GEO_ID","id"
|
||||
"NAME","Geographic Area Name"
|
||||
"P1_001N"," !!Total:"
|
||||
"P1_002N"," !!Total:!!Population of one race:"
|
||||
"P1_003N"," !!Total:!!Population of one race:!!White alone"
|
||||
"P1_004N"," !!Total:!!Population of one race:!!Black or African American alone"
|
||||
"P1_005N"," !!Total:!!Population of one race:!!American Indian and Alaska Native alone"
|
||||
"P1_006N"," !!Total:!!Population of one race:!!Asian alone"
|
||||
"P1_007N"," !!Total:!!Population of one race:!!Native Hawaiian and Other Pacific Islander alone"
|
||||
"P1_008N"," !!Total:!!Population of one race:!!Some Other Race alone"
|
||||
"P1_009N"," !!Total:!!Population of two or more races:"
|
||||
"P1_010N"," !!Total:!!Population of two or more races:!!Population of two races:"
|
||||
"P1_011N"," !!Total:!!Population of two or more races:!!Population of two races:!!White; Black or African American"
|
||||
"P1_012N"," !!Total:!!Population of two or more races:!!Population of two races:!!White; American Indian and Alaska Native"
|
||||
"P1_013N"," !!Total:!!Population of two or more races:!!Population of two races:!!White; Asian"
|
||||
"P1_014N"," !!Total:!!Population of two or more races:!!Population of two races:!!White; Native Hawaiian and Other Pacific Islander"
|
||||
"P1_015N"," !!Total:!!Population of two or more races:!!Population of two races:!!White; Some Other Race"
|
||||
"P1_016N"," !!Total:!!Population of two or more races:!!Population of two races:!!Black or African American; American Indian and Alaska Native"
|
||||
"P1_017N"," !!Total:!!Population of two or more races:!!Population of two races:!!Black or African American; Asian"
|
||||
"P1_018N"," !!Total:!!Population of two or more races:!!Population of two races:!!Black or African American; Native Hawaiian and Other Pacific Islander"
|
||||
"P1_019N"," !!Total:!!Population of two or more races:!!Population of two races:!!Black or African American; Some Other Race"
|
||||
"P1_020N"," !!Total:!!Population of two or more races:!!Population of two races:!!American Indian and Alaska Native; Asian"
|
||||
"P1_021N"," !!Total:!!Population of two or more races:!!Population of two races:!!American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander"
|
||||
"P1_022N"," !!Total:!!Population of two or more races:!!Population of two races:!!American Indian and Alaska Native; Some Other Race"
|
||||
"P1_023N"," !!Total:!!Population of two or more races:!!Population of two races:!!Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P1_024N"," !!Total:!!Population of two or more races:!!Population of two races:!!Asian; Some Other Race"
|
||||
"P1_025N"," !!Total:!!Population of two or more races:!!Population of two races:!!Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P1_026N"," !!Total:!!Population of two or more races:!!Population of three races:"
|
||||
"P1_027N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; Black or African American; American Indian and Alaska Native"
|
||||
"P1_028N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; Black or African American; Asian"
|
||||
"P1_029N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; Black or African American; Native Hawaiian and Other Pacific Islander"
|
||||
"P1_030N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; Black or African American; Some Other Race"
|
||||
"P1_031N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; American Indian and Alaska Native; Asian"
|
||||
"P1_032N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander"
|
||||
"P1_033N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; American Indian and Alaska Native; Some Other Race"
|
||||
"P1_034N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P1_035N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; Asian; Some Other Race"
|
||||
"P1_036N"," !!Total:!!Population of two or more races:!!Population of three races:!!White; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P1_037N"," !!Total:!!Population of two or more races:!!Population of three races:!!Black or African American; American Indian and Alaska Native; Asian"
|
||||
"P1_038N"," !!Total:!!Population of two or more races:!!Population of three races:!!Black or African American; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander"
|
||||
"P1_039N"," !!Total:!!Population of two or more races:!!Population of three races:!!Black or African American; American Indian and Alaska Native; Some Other Race"
|
||||
"P1_040N"," !!Total:!!Population of two or more races:!!Population of three races:!!Black or African American; Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P1_041N"," !!Total:!!Population of two or more races:!!Population of three races:!!Black or African American; Asian; Some Other Race"
|
||||
"P1_042N"," !!Total:!!Population of two or more races:!!Population of three races:!!Black or African American; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P1_043N"," !!Total:!!Population of two or more races:!!Population of three races:!!American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P1_044N"," !!Total:!!Population of two or more races:!!Population of three races:!!American Indian and Alaska Native; Asian; Some Other Race"
|
||||
"P1_045N"," !!Total:!!Population of two or more races:!!Population of three races:!!American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P1_046N"," !!Total:!!Population of two or more races:!!Population of three races:!!Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P1_047N"," !!Total:!!Population of two or more races:!!Population of four races:"
|
||||
"P1_048N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; Black or African American; American Indian and Alaska Native; Asian"
|
||||
"P1_049N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; Black or African American; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander"
|
||||
"P1_050N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; Black or African American; American Indian and Alaska Native; Some Other Race"
|
||||
"P1_051N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; Black or African American; Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P1_052N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; Black or African American; Asian; Some Other Race"
|
||||
"P1_053N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; Black or African American; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P1_054N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P1_055N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; American Indian and Alaska Native; Asian; Some Other Race"
|
||||
"P1_056N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P1_057N"," !!Total:!!Population of two or more races:!!Population of four races:!!White; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P1_058N"," !!Total:!!Population of two or more races:!!Population of four races:!!Black or African American; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P1_059N"," !!Total:!!Population of two or more races:!!Population of four races:!!Black or African American; American Indian and Alaska Native; Asian; Some Other Race"
|
||||
"P1_060N"," !!Total:!!Population of two or more races:!!Population of four races:!!Black or African American; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P1_061N"," !!Total:!!Population of two or more races:!!Population of four races:!!Black or African American; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P1_062N"," !!Total:!!Population of two or more races:!!Population of four races:!!American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P1_063N"," !!Total:!!Population of two or more races:!!Population of five races:"
|
||||
"P1_064N"," !!Total:!!Population of two or more races:!!Population of five races:!!White; Black or African American; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander"
|
||||
"P1_065N"," !!Total:!!Population of two or more races:!!Population of five races:!!White; Black or African American; American Indian and Alaska Native; Asian; Some Other Race"
|
||||
"P1_066N"," !!Total:!!Population of two or more races:!!Population of five races:!!White; Black or African American; American Indian and Alaska Native; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P1_067N"," !!Total:!!Population of two or more races:!!Population of five races:!!White; Black or African American; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P1_068N"," !!Total:!!Population of two or more races:!!Population of five races:!!White; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P1_069N"," !!Total:!!Population of two or more races:!!Population of five races:!!Black or African American; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
"P1_070N"," !!Total:!!Population of two or more races:!!Population of six races:"
|
||||
"P1_071N"," !!Total:!!Population of two or more races:!!Population of six races:!!White; Black or African American; American Indian and Alaska Native; Asian; Native Hawaiian and Other Pacific Islander; Some Other Race"
|
||||
|
+8
@@ -0,0 +1,8 @@
|
||||
P1
|
||||
RACE
|
||||
For information on the statistical methods used to protect confidentiality in these tables, see <a href="https://www.census.gov/programs-surveys/decennial-census/2020-census/planning-management/2020-census-data-products.html">Disclosure Avoidance and the 2020 Census</a>.<br/><br/>
|
||||
|
||||
Note: For information on data collection, confidentiality protection, nonsampling error, and definitions, see <a href="https://www2.census.gov/programs-surveys/decennial/2020/technical-documentation/complete-tech-docs/summary-file/">2020 Census Redistricting Data (Public Law 94-171) Summary File Technical Documentation</a>.<br/><br/>
|
||||
|
||||
Source: U.S. Census Bureau, 2020 Census Redistricting Data (Public Law 94-171)<br/><br/>
|
||||
|
||||
File diff suppressed because it is too large.
Load diff
@@ -0,0 +1 @@
|
||||
UTF-8
|
||||
Binary file not shown.
@@ -0,0 +1 @@
|
||||
GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137,298.257222101]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]]
|
||||
Binary file not shown.
Executable
+360
@@ -0,0 +1,360 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<gfc:FC_FeatureCatalogue xmlns:xlink="http://www.w3.org/1999/xlink"
|
||||
xmlns:gmd="http://www.isotc211.org/2005/gmd"
|
||||
xmlns:gco="http://www.isotc211.org/2005/gco"
|
||||
xmlns:gml="http://www.opengis.net/gml/3.2"
|
||||
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
|
||||
xmlns:gmi="http://www.isotc211.org/2005/gmi"
|
||||
xmlns:srv="http://www.isotc211.org/2005/srv"
|
||||
xmlns:gmx="http://www.isotc211.org/2005/gmx"
|
||||
xmlns:gfc="http://www.isotc211.org/2005/gfc">
|
||||
<gmx:name>
|
||||
<gco:CharacterString>Feature Catalog for the 2022 Block Groups Cartographic Boundary File</gco:CharacterString>
|
||||
</gmx:name>
|
||||
<gmx:scope>
|
||||
<gco:CharacterString>Block Groups</gco:CharacterString>
|
||||
</gmx:scope>
|
||||
<gmx:versionNumber>
|
||||
<gco:CharacterString>2023-04</gco:CharacterString>
|
||||
</gmx:versionNumber>
|
||||
<gmx:versionDate>
|
||||
<gco:Date>2023-04</gco:Date>
|
||||
</gmx:versionDate>
|
||||
<gmx:language>
|
||||
<gco:CharacterString>eng; USA</gco:CharacterString>
|
||||
</gmx:language>
|
||||
<gmx:characterSet>
|
||||
<gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode"
|
||||
codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>
|
||||
</gmx:characterSet>
|
||||
<gfc:producer>
|
||||
<gmd:CI_ResponsibleParty>
|
||||
<gmd:organisationName>
|
||||
<gco:CharacterString>U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch</gco:CharacterString>
|
||||
</gmd:organisationName>
|
||||
<gmd:contactInfo>
|
||||
<gmd:CI_Contact>
|
||||
<gmd:phone>
|
||||
<gmd:CI_Telephone>
|
||||
<gmd:voice>
|
||||
<gco:CharacterString>301-763-1128</gco:CharacterString>
|
||||
</gmd:voice>
|
||||
<gmd:facsimile>
|
||||
<gco:CharacterString>301-763-4710</gco:CharacterString>
|
||||
</gmd:facsimile>
|
||||
</gmd:CI_Telephone>
|
||||
</gmd:phone>
|
||||
<gmd:address>
|
||||
<gmd:CI_Address>
|
||||
<gmd:deliveryPoint>
|
||||
<gco:CharacterString>4600 Silver Hill Road, Stop 7400</gco:CharacterString>
|
||||
</gmd:deliveryPoint>
|
||||
<gmd:city>
|
||||
<gco:CharacterString>Washington</gco:CharacterString>
|
||||
</gmd:city>
|
||||
<gmd:administrativeArea>
|
||||
<gco:CharacterString>DC</gco:CharacterString>
|
||||
</gmd:administrativeArea>
|
||||
<gmd:postalCode>
|
||||
<gco:CharacterString>20233-7400</gco:CharacterString>
|
||||
</gmd:postalCode>
|
||||
<gmd:country>
|
||||
<gco:CharacterString>United States</gco:CharacterString>
|
||||
</gmd:country>
|
||||
<gmd:electronicMailAddress>
|
||||
<gco:CharacterString>geo.geography@census.gov</gco:CharacterString>
|
||||
</gmd:electronicMailAddress>
|
||||
</gmd:CI_Address>
|
||||
</gmd:address>
|
||||
</gmd:CI_Contact>
|
||||
</gmd:contactInfo>
|
||||
<gmd:role>
|
||||
<gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode"
|
||||
codeListValue="pointOfContact">pointOfContact</gmd:CI_RoleCode>
|
||||
</gmd:role>
|
||||
</gmd:CI_ResponsibleParty>
|
||||
</gfc:producer>
|
||||
<gfc:featureType>
|
||||
<gfc:FC_FeatureType>
|
||||
<gfc:typeName>
|
||||
<gco:LocalName>cb_2022_32_bg_500k.shp</gco:LocalName>
|
||||
</gfc:typeName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current Block Group (state-based)</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:isAbstract>
|
||||
<gco:Boolean>false</gco:Boolean>
|
||||
</gfc:isAbstract>
|
||||
<gfc:featureCatalogue uuidref="cb_2022_32_bg_500k.shp.ea.iso.xml"/>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>STATEFP</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current state Federal Information Processing Series (FIPS) code</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality gco:nilReason="unknown"/>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label>
|
||||
<gco:CharacterString>National Standard Codes (ANSI INCITS 38-2009), Federal Information Processing Series (FIPS) - States/State Equivalents</gco:CharacterString>
|
||||
</gfc:label>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>COUNTYFP</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current county Federal Information Processing Series (FIPS) code</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality gco:nilReason="unknown"/>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label>
|
||||
<gco:CharacterString>National Standard Codes (ANSI INCITS 31-2009), Federal Information Processing Series (FIPS) - Counties/County Equivalents</gco:CharacterString>
|
||||
</gfc:label>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>TRACTCE</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current census tract code</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality gco:nilReason="unknown"/>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label>
|
||||
<gco:CharacterString>000000</gco:CharacterString>
|
||||
</gfc:label>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Water tract in some coastal and Great Lakes water and territorial sea</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label>
|
||||
<gco:CharacterString>000100 to 998999</gco:CharacterString>
|
||||
</gfc:label>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Census tract number</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>BLKGRPCE</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current block group number. A block group number of 0 represents a water block group.</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality>
|
||||
<gco:Multiplicity>
|
||||
<gco:range>
|
||||
<gco:MultiplicityRange>
|
||||
<gco:lower>
|
||||
<gco:Integer>0</gco:Integer>
|
||||
</gco:lower>
|
||||
<gco:upper>
|
||||
<gco:UnlimitedInteger>9</gco:UnlimitedInteger>
|
||||
</gco:upper>
|
||||
</gco:MultiplicityRange>
|
||||
</gco:range>
|
||||
</gco:Multiplicity>
|
||||
</gfc:cardinality>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>AFFGEOID</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>American FactFinder summary level code + geovariant code + '00US' + GEOID</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality gco:nilReason="unknown"/>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label>
|
||||
<gco:CharacterString>American FactFinder geographic identifier</gco:CharacterString>
|
||||
</gfc:label>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>GEOID</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Census block group identifier; a concatenation of the current state Federal Information Processing Series (FIPS) code, county FIPS code, census tract code, and block group number</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality gco:nilReason="unknown"/>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label gco:nilReason="inapplicable"/>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>The GEOID attribute is a concatenation of the state FIPS code, followed by the county FIPS code, followed by the census tract code, followed by the block group number. No spaces are allowed between the two codes. The state FIPS code is taken from "National Standard Codes (ANSI INCITS 38-2009), Federal Information Processing Series (FIPS) - States". The county FIPS code is taken from "National Standard Codes (ANSI INCITS 31-2009), Federal Information Processing Series (FIPS) - Counties/County Equivalents". The census tract code is taken from the "TRACTCE" attribute. The block group number is taken from the "BLKGRPCE" attribute.</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>NAME</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current block group number. A block group number of 0 represents a water block group.</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality gco:nilReason="unknown"/>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label gco:nilReason="inapplicable"/>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Refer to the block group number that appears in BLKGRPCE.</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>NAMELSAD</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current translated legal/statistical area description and the block group number</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality gco:nilReason="unknown"/>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label gco:nilReason="inapplicable"/>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Refer to the block group number that appears in BLKGRPCE and translated legal/statistical area description code BG, Block Group</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>LSAD</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current legal/statistical area description code for Census block group</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality gco:nilReason="unknown"/>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label>
|
||||
<gco:CharacterString>BG</gco:CharacterString>
|
||||
</gfc:label>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Block Group (prefix)</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>ALAND</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current land area (square meters)</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality>
|
||||
<gco:Multiplicity>
|
||||
<gco:range>
|
||||
<gco:MultiplicityRange>
|
||||
<gco:lower>
|
||||
<gco:Integer>0</gco:Integer>
|
||||
</gco:lower>
|
||||
<gco:upper>
|
||||
<gco:UnlimitedInteger>9,999,999,999,999</gco:UnlimitedInteger>
|
||||
</gco:upper>
|
||||
</gco:MultiplicityRange>
|
||||
</gco:range>
|
||||
</gco:Multiplicity>
|
||||
</gfc:cardinality>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>AWATER</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current water area (square meters)</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality>
|
||||
<gco:Multiplicity>
|
||||
<gco:range>
|
||||
<gco:MultiplicityRange>
|
||||
<gco:lower>
|
||||
<gco:Integer>0</gco:Integer>
|
||||
</gco:lower>
|
||||
<gco:upper>
|
||||
<gco:UnlimitedInteger>9,999,999,999,999</gco:UnlimitedInteger>
|
||||
</gco:upper>
|
||||
</gco:MultiplicityRange>
|
||||
</gco:range>
|
||||
</gco:Multiplicity>
|
||||
</gfc:cardinality>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
</gfc:FC_FeatureType>
|
||||
</gfc:featureType>
|
||||
</gfc:FC_FeatureCatalogue>
|
||||
+750
@@ -0,0 +1,750 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<gmi:MI_Metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
|
||||
xmlns:gmd="http://www.isotc211.org/2005/gmd"
|
||||
xmlns:gco="http://www.isotc211.org/2005/gco"
|
||||
xmlns:gml="http://www.opengis.net/gml/3.2"
|
||||
xmlns:gmi="http://www.isotc211.org/2005/gmi"
|
||||
xmlns:xlink="http://www.w3.org/1999/xlink"
|
||||
xmlns:srv="http://www.isotc211.org/2005/srv"
|
||||
xsi:schemaLocation="http://www.isotc211.org/2005/gmi https://data.noaa.gov/resources/iso19139/schema.xsd">
|
||||
<gmd:fileIdentifier>
|
||||
<gco:CharacterString>cb_2022_32_bg_500k.shp.iso.xml</gco:CharacterString>
|
||||
</gmd:fileIdentifier>
|
||||
<gmd:language>
|
||||
<gco:CharacterString>eng; USA</gco:CharacterString>
|
||||
</gmd:language>
|
||||
<gmd:characterSet>
|
||||
<gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode"
|
||||
codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>
|
||||
</gmd:characterSet>
|
||||
<gmd:hierarchyLevel>
|
||||
<gmd:MD_ScopeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ScopeCode"
|
||||
codeListValue="dataset">dataset</gmd:MD_ScopeCode>
|
||||
</gmd:hierarchyLevel>
|
||||
<gmd:contact>
|
||||
<gmd:CI_ResponsibleParty>
|
||||
<gmd:organisationName>
|
||||
<gco:CharacterString>U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch</gco:CharacterString>
|
||||
</gmd:organisationName>
|
||||
<gmd:contactInfo>
|
||||
<gmd:CI_Contact>
|
||||
<gmd:phone>
|
||||
<gmd:CI_Telephone>
|
||||
<gmd:voice>
|
||||
<gco:CharacterString>301-763-1128</gco:CharacterString>
|
||||
</gmd:voice>
|
||||
<gmd:facsimile>
|
||||
<gco:CharacterString>301-763-4710</gco:CharacterString>
|
||||
</gmd:facsimile>
|
||||
</gmd:CI_Telephone>
|
||||
</gmd:phone>
|
||||
<gmd:address>
|
||||
<gmd:CI_Address>
|
||||
<gmd:deliveryPoint>
|
||||
<gco:CharacterString>4600 Silver Hill Road, Stop 7400</gco:CharacterString>
|
||||
</gmd:deliveryPoint>
|
||||
<gmd:city>
|
||||
<gco:CharacterString>Washington</gco:CharacterString>
|
||||
</gmd:city>
|
||||
<gmd:administrativeArea>
|
||||
<gco:CharacterString>DC</gco:CharacterString>
|
||||
</gmd:administrativeArea>
|
||||
<gmd:postalCode>
|
||||
<gco:CharacterString>20233-7400</gco:CharacterString>
|
||||
</gmd:postalCode>
|
||||
<gmd:country>
|
||||
<gco:CharacterString>United States</gco:CharacterString>
|
||||
</gmd:country>
|
||||
<gmd:electronicMailAddress>
|
||||
<gco:CharacterString>geo.geography@census.gov</gco:CharacterString>
|
||||
</gmd:electronicMailAddress>
|
||||
</gmd:CI_Address>
|
||||
</gmd:address>
|
||||
</gmd:CI_Contact>
|
||||
</gmd:contactInfo>
|
||||
<gmd:role>
|
||||
<gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode"
|
||||
codeListValue="pointOfContact">pointOfContact</gmd:CI_RoleCode>
|
||||
</gmd:role>
|
||||
</gmd:CI_ResponsibleParty>
|
||||
</gmd:contact>
|
||||
<gmd:dateStamp>
|
||||
<gco:Date>2023-04</gco:Date>
|
||||
</gmd:dateStamp>
|
||||
<gmd:metadataStandardName>
|
||||
<gco:CharacterString>ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data</gco:CharacterString>
|
||||
</gmd:metadataStandardName>
|
||||
<gmd:metadataStandardVersion>
|
||||
<gco:CharacterString>ISO 19115-2:2009(E)</gco:CharacterString>
|
||||
</gmd:metadataStandardVersion>
|
||||
<gmd:dataSetURI>
|
||||
<gco:CharacterString>https://meta.geo.census.gov/data/existing/decennial/GEO/CPMB/boundary/2022/shp/19115/cb_2022_32_bg_500k.shp.iso.xml</gco:CharacterString>
|
||||
</gmd:dataSetURI>
|
||||
<gmd:spatialRepresentationInfo>
|
||||
<gmd:MD_VectorSpatialRepresentation>
|
||||
<gmd:geometricObjects>
|
||||
<gmd:MD_GeometricObjects>
|
||||
<gmd:geometricObjectType>
|
||||
<gmd:MD_GeometricObjectTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_GeometricObjectTypeCode"
|
||||
codeListValue="complex">complex</gmd:MD_GeometricObjectTypeCode>
|
||||
</gmd:geometricObjectType>
|
||||
<gmd:geometricObjectCount>
|
||||
<gco:Integer>1963</gco:Integer>
|
||||
</gmd:geometricObjectCount>
|
||||
</gmd:MD_GeometricObjects>
|
||||
</gmd:geometricObjects>
|
||||
</gmd:MD_VectorSpatialRepresentation>
|
||||
</gmd:spatialRepresentationInfo>
|
||||
<gmd:referenceSystemInfo>
|
||||
<gmd:MD_ReferenceSystem uuid="65f8b220-95ed-11e0-aa80-0800200c9a66">
|
||||
<gmd:referenceSystemIdentifier>
|
||||
<gmd:RS_Identifier>
|
||||
<gmd:authority>
|
||||
<gmd:CI_Citation>
|
||||
<gmd:title>
|
||||
<gco:CharacterString>North American Datum of 1983</gco:CharacterString>
|
||||
</gmd:title>
|
||||
<gmd:alternateTitle>
|
||||
<gco:CharacterString>NAD83</gco:CharacterString>
|
||||
</gmd:alternateTitle>
|
||||
<gmd:date>
|
||||
<gmd:CI_Date>
|
||||
<gmd:date>
|
||||
<gco:Date>2007-01-19</gco:Date>
|
||||
</gmd:date>
|
||||
<gmd:dateType>
|
||||
<gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode"
|
||||
codeListValue="revision">revision</gmd:CI_DateTypeCode>
|
||||
</gmd:dateType>
|
||||
</gmd:CI_Date>
|
||||
</gmd:date>
|
||||
<gmd:citedResponsibleParty>
|
||||
<gmd:CI_ResponsibleParty>
|
||||
<gmd:organisationName gco:nilReason="withheld"/>
|
||||
<gmd:contactInfo>
|
||||
<gmd:CI_Contact>
|
||||
<gmd:onlineResource>
|
||||
<gmd:CI_OnlineResource>
|
||||
<gmd:linkage>
|
||||
<gmd:URL>https://spatialreference.org/ref/epsg/4269/gml/</gmd:URL>
|
||||
</gmd:linkage>
|
||||
<gmd:name>
|
||||
<gco:CharacterString>NAD83</gco:CharacterString>
|
||||
</gmd:name>
|
||||
<gmd:description>
|
||||
<gco:CharacterString>Link to Geographic Markup Language (GML) description of reference system.</gco:CharacterString>
|
||||
</gmd:description>
|
||||
<gmd:function>
|
||||
<gmd:CI_OnLineFunctionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_OnLineFunctionCode"
|
||||
codeListValue="information">information</gmd:CI_OnLineFunctionCode>
|
||||
</gmd:function>
|
||||
</gmd:CI_OnlineResource>
|
||||
</gmd:onlineResource>
|
||||
</gmd:CI_Contact>
|
||||
</gmd:contactInfo>
|
||||
<gmd:role>
|
||||
<gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode"
|
||||
codeListValue="resourceProvider">resourceProvider</gmd:CI_RoleCode>
|
||||
</gmd:role>
|
||||
</gmd:CI_ResponsibleParty>
|
||||
</gmd:citedResponsibleParty>
|
||||
</gmd:CI_Citation>
|
||||
</gmd:authority>
|
||||
<gmd:code>
|
||||
<gco:CharacterString>urn:ogc:def:crs:EPSG::4269</gco:CharacterString>
|
||||
</gmd:code>
|
||||
</gmd:RS_Identifier>
|
||||
</gmd:referenceSystemIdentifier>
|
||||
</gmd:MD_ReferenceSystem>
|
||||
</gmd:referenceSystemInfo>
|
||||
<gmd:identificationInfo>
|
||||
<gmd:MD_DataIdentification>
|
||||
<gmd:citation>
|
||||
<gmd:CI_Citation>
|
||||
<gmd:title>
|
||||
<gco:CharacterString>2022 Cartographic Boundary File (SHP), Current Block Group for Nevada, 1:500,000</gco:CharacterString>
|
||||
</gmd:title>
|
||||
<gmd:date>
|
||||
<gmd:CI_Date>
|
||||
<gmd:date>
|
||||
<gco:Date>2023-04</gco:Date>
|
||||
</gmd:date>
|
||||
<gmd:dateType>
|
||||
<gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode"
|
||||
codeListValue="publication">publication</gmd:CI_DateTypeCode>
|
||||
</gmd:dateType>
|
||||
</gmd:CI_Date>
|
||||
</gmd:date>
|
||||
<gmd:date>
|
||||
<gmd:CI_Date>
|
||||
<gmd:date>
|
||||
<gco:Date>2023-04</gco:Date>
|
||||
</gmd:date>
|
||||
<gmd:dateType>
|
||||
<gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode"
|
||||
codeListValue="creation">creation</gmd:CI_DateTypeCode>
|
||||
</gmd:dateType>
|
||||
</gmd:CI_Date>
|
||||
</gmd:date>
|
||||
<gmd:date>
|
||||
<gmd:CI_Date>
|
||||
<gmd:date>
|
||||
<gco:Date>2023-04</gco:Date>
|
||||
</gmd:date>
|
||||
<gmd:dateType>
|
||||
<gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode"
|
||||
codeListValue="lastUpdate">lastUpdate</gmd:CI_DateTypeCode>
|
||||
</gmd:dateType>
|
||||
</gmd:CI_Date>
|
||||
</gmd:date>
|
||||
<gmd:identifier>
|
||||
<gmd:MD_Identifier>
|
||||
<gmd:code>
|
||||
<gco:CharacterString>cb_2022_32_bg_500k</gco:CharacterString>
|
||||
</gmd:code>
|
||||
</gmd:MD_Identifier>
|
||||
</gmd:identifier>
|
||||
<gmd:citedResponsibleParty>
|
||||
<gmd:CI_ResponsibleParty>
|
||||
<gmd:organisationName>
|
||||
<gco:CharacterString>U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch</gco:CharacterString>
|
||||
</gmd:organisationName>
|
||||
<gmd:contactInfo>
|
||||
<gmd:CI_Contact>
|
||||
<gmd:phone>
|
||||
<gmd:CI_Telephone>
|
||||
<gmd:voice>
|
||||
<gco:CharacterString>301-763-1128</gco:CharacterString>
|
||||
</gmd:voice>
|
||||
<gmd:facsimile>
|
||||
<gco:CharacterString>301-763-4710</gco:CharacterString>
|
||||
</gmd:facsimile>
|
||||
</gmd:CI_Telephone>
|
||||
</gmd:phone>
|
||||
<gmd:address>
|
||||
<gmd:CI_Address>
|
||||
<gmd:deliveryPoint>
|
||||
<gco:CharacterString>4600 Silver Hill Road, Stop 7400</gco:CharacterString>
|
||||
</gmd:deliveryPoint>
|
||||
<gmd:city>
|
||||
<gco:CharacterString>Washington</gco:CharacterString>
|
||||
</gmd:city>
|
||||
<gmd:administrativeArea>
|
||||
<gco:CharacterString>DC</gco:CharacterString>
|
||||
</gmd:administrativeArea>
|
||||
<gmd:postalCode>
|
||||
<gco:CharacterString>20233-7400</gco:CharacterString>
|
||||
</gmd:postalCode>
|
||||
<gmd:country>
|
||||
<gco:CharacterString>United States</gco:CharacterString>
|
||||
</gmd:country>
|
||||
<gmd:electronicMailAddress>
|
||||
<gco:CharacterString>geo.geography@census.gov</gco:CharacterString>
|
||||
</gmd:electronicMailAddress>
|
||||
</gmd:CI_Address>
|
||||
</gmd:address>
|
||||
</gmd:CI_Contact>
|
||||
</gmd:contactInfo>
|
||||
<gmd:role>
|
||||
<gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode"
|
||||
codeListValue="pointOfContact">pointOfContact</gmd:CI_RoleCode>
|
||||
</gmd:role>
|
||||
</gmd:CI_ResponsibleParty>
|
||||
</gmd:citedResponsibleParty>
|
||||
<gmd:presentationForm>
|
||||
<gmd:CI_PresentationFormCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_PresentationFormCode"
|
||||
codeListValue="mapDigital">mapDigital</gmd:CI_PresentationFormCode>
|
||||
</gmd:presentationForm>
|
||||
</gmd:CI_Citation>
|
||||
</gmd:citation>
|
||||
<gmd:abstract>
|
||||
<gco:CharacterString>The 2022 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files.
|
||||
|
||||
Block Groups (BGs) are clusters of blocks within the same census tract. Each census tract contains at least one BG, and BGs are uniquely numbered within census tracts. BGs have a valid code range of 0 through 9. BGs have the same first digit of their 4-digit census block number from the same decennial census. For example, tabulation blocks numbered 3001, 3002, 3003,.., 3999 within census tract 1210.02 are also within BG 3 within that census tract. BGs coded 0 are intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and Great Lakes water areas. Block groups generally contain between 600 and 3,000 people. A BG usually covers a contiguous area but never crosses county or census tract boundaries. They may, however, cross the boundaries of other geographic entities like county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian / Alaska Native / Native Hawaiian areas.
|
||||
|
||||
The generalized BG boundaries in this release are based on those that were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.</gco:CharacterString>
|
||||
</gmd:abstract>
|
||||
<gmd:purpose>
|
||||
<gco:CharacterString>These files were specifically created to support small-scale thematic mapping. To improve the appearance of shapes at small scales, areas are represented with fewer vertices than detailed TIGER/Line Shapefiles. Cartographic boundary files take up less disk space than their ungeneralized counterparts. Cartographic boundary files take less time to render on screen than TIGER/Line Shapefiles. You can join this file with table data downloaded from American FactFinder by using the AFFGEOID field in the cartographic boundary file. If detailed boundaries are required, please use the TIGER/Line Shapefiles instead of the generalized cartographic boundary files.</gco:CharacterString>
|
||||
</gmd:purpose>
|
||||
<gmd:status>
|
||||
<gmd:MD_ProgressCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ProgressCode"
|
||||
codeListValue="completed">completed</gmd:MD_ProgressCode>
|
||||
</gmd:status>
|
||||
<gmd:pointOfContact>
|
||||
<gmd:CI_ResponsibleParty>
|
||||
<gmd:organisationName>
|
||||
<gco:CharacterString>U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch</gco:CharacterString>
|
||||
</gmd:organisationName>
|
||||
<gmd:contactInfo>
|
||||
<gmd:CI_Contact>
|
||||
<gmd:phone>
|
||||
<gmd:CI_Telephone>
|
||||
<gmd:voice>
|
||||
<gco:CharacterString>301-763-1128</gco:CharacterString>
|
||||
</gmd:voice>
|
||||
<gmd:facsimile>
|
||||
<gco:CharacterString>301-763-4710</gco:CharacterString>
|
||||
</gmd:facsimile>
|
||||
</gmd:CI_Telephone>
|
||||
</gmd:phone>
|
||||
<gmd:address>
|
||||
<gmd:CI_Address>
|
||||
<gmd:deliveryPoint>
|
||||
<gco:CharacterString>4600 Silver Hill Road, Stop 7400</gco:CharacterString>
|
||||
</gmd:deliveryPoint>
|
||||
<gmd:city>
|
||||
<gco:CharacterString>Washington</gco:CharacterString>
|
||||
</gmd:city>
|
||||
<gmd:administrativeArea>
|
||||
<gco:CharacterString>DC</gco:CharacterString>
|
||||
</gmd:administrativeArea>
|
||||
<gmd:postalCode>
|
||||
<gco:CharacterString>20233-7400</gco:CharacterString>
|
||||
</gmd:postalCode>
|
||||
<gmd:country>
|
||||
<gco:CharacterString>United States</gco:CharacterString>
|
||||
</gmd:country>
|
||||
<gmd:electronicMailAddress>
|
||||
<gco:CharacterString>geo.geography@census.gov</gco:CharacterString>
|
||||
</gmd:electronicMailAddress>
|
||||
</gmd:CI_Address>
|
||||
</gmd:address>
|
||||
</gmd:CI_Contact>
|
||||
</gmd:contactInfo>
|
||||
<gmd:role>
|
||||
<gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode"
|
||||
codeListValue="pointOfContact">pointOfContact</gmd:CI_RoleCode>
|
||||
</gmd:role>
|
||||
</gmd:CI_ResponsibleParty>
|
||||
</gmd:pointOfContact>
|
||||
<gmd:resourceMaintenance>
|
||||
<gmd:MD_MaintenanceInformation>
|
||||
<gmd:maintenanceAndUpdateFrequency>
|
||||
<gmd:MD_MaintenanceFrequencyCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_MaintenanceFrequencyCode"
|
||||
codeListValue="notPlanned">notPlanned</gmd:MD_MaintenanceFrequencyCode>
|
||||
</gmd:maintenanceAndUpdateFrequency>
|
||||
</gmd:MD_MaintenanceInformation>
|
||||
</gmd:resourceMaintenance>
|
||||
<gmd:descriptiveKeywords>
|
||||
<gmd:MD_Keywords>
|
||||
<gmd:keyword>
|
||||
<gco:CharacterString>2022</gco:CharacterString>
|
||||
</gmd:keyword>
|
||||
<gmd:keyword>
|
||||
<gco:CharacterString>SHP</gco:CharacterString>
|
||||
</gmd:keyword>
|
||||
<gmd:keyword>
|
||||
<gco:CharacterString>Block Group</gco:CharacterString>
|
||||
</gmd:keyword>
|
||||
<gmd:keyword>
|
||||
<gco:CharacterString>Cartographic Boundary</gco:CharacterString>
|
||||
</gmd:keyword>
|
||||
<gmd:keyword>
|
||||
<gco:CharacterString>Census Tract</gco:CharacterString>
|
||||
</gmd:keyword>
|
||||
<gmd:keyword>
|
||||
<gco:CharacterString>County</gco:CharacterString>
|
||||
</gmd:keyword>
|
||||
<gmd:keyword>
|
||||
<gco:CharacterString>Generalized</gco:CharacterString>
|
||||
</gmd:keyword>
|
||||
<gmd:type>
|
||||
<gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode"
|
||||
codeListValue="theme"/>
|
||||
</gmd:type>
|
||||
<gmd:thesaurusName>
|
||||
<gmd:CI_Citation>
|
||||
<gmd:title>
|
||||
<gco:CharacterString>None</gco:CharacterString>
|
||||
</gmd:title>
|
||||
<gmd:date gco:nilReason="unknown"/>
|
||||
</gmd:CI_Citation>
|
||||
</gmd:thesaurusName>
|
||||
</gmd:MD_Keywords>
|
||||
</gmd:descriptiveKeywords>
|
||||
<gmd:descriptiveKeywords>
|
||||
<gmd:MD_Keywords>
|
||||
<gmd:keyword>
|
||||
<gco:CharacterString>Nevada</gco:CharacterString>
|
||||
</gmd:keyword>
|
||||
<gmd:keyword>
|
||||
<gco:CharacterString>NV</gco:CharacterString>
|
||||
</gmd:keyword>
|
||||
<gmd:type>
|
||||
<gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode"
|
||||
codeListValue="place"/>
|
||||
</gmd:type>
|
||||
<gmd:thesaurusName>
|
||||
<gmd:CI_Citation>
|
||||
<gmd:title>
|
||||
<gco:CharacterString>INCITS 38-2009[R2019]: Information Technology - Codes for the Identification of the States and Equivalent Areas within the United States, Puerto Rico, and the Insular Areas</gco:CharacterString>
|
||||
</gmd:title>
|
||||
<gmd:date gco:nilReason="unknown"/>
|
||||
</gmd:CI_Citation>
|
||||
</gmd:thesaurusName>
|
||||
</gmd:MD_Keywords>
|
||||
</gmd:descriptiveKeywords>
|
||||
<gmd:resourceConstraints>
|
||||
<gmd:MD_LegalConstraints>
|
||||
<gmd:accessConstraints>
|
||||
<gmd:MD_RestrictionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_RestrictionCode"
|
||||
codeListValue="otherRestrictions">otherRestrictions</gmd:MD_RestrictionCode>
|
||||
</gmd:accessConstraints>
|
||||
<gmd:useConstraints>
|
||||
<gmd:MD_RestrictionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_RestrictionCode"
|
||||
codeListValue="otherRestrictions">otherRestrictions</gmd:MD_RestrictionCode>
|
||||
</gmd:useConstraints>
|
||||
<gmd:otherConstraints>
|
||||
<gco:CharacterString>Access_Constraints: None</gco:CharacterString>
|
||||
</gmd:otherConstraints>
|
||||
<gmd:otherConstraints>
|
||||
<gco:CharacterString>Use Constraints: The intended display scale for this file is 1:500,000. This file should not be displayed at scales larger than 1:500,000.
|
||||
|
||||
These products are free to use in a product or publication, however acknowledgement must be given to the U.S. Census Bureau as the source. The boundary information is for visual display at appropriate small scales only. Cartographic boundary files should not be used for geographic analysis including area or perimeter calculation. Files should not be used for geocoding addresses. Files should not be used for determining precise geographic area relationships.</gco:CharacterString>
|
||||
</gmd:otherConstraints>
|
||||
</gmd:MD_LegalConstraints>
|
||||
</gmd:resourceConstraints>
|
||||
<gmd:spatialRepresentationType>
|
||||
<gmd:MD_SpatialRepresentationTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_SpatialRepresentationTypeCode"
|
||||
codeListValue="vector">vector</gmd:MD_SpatialRepresentationTypeCode>
|
||||
</gmd:spatialRepresentationType>
|
||||
<gmd:language>
|
||||
<gco:CharacterString>eng; USA</gco:CharacterString>
|
||||
</gmd:language>
|
||||
<gmd:characterSet>
|
||||
<gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode"
|
||||
codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>
|
||||
</gmd:characterSet>
|
||||
<gmd:topicCategory>
|
||||
<gmd:MD_TopicCategoryCode>boundaries</gmd:MD_TopicCategoryCode>
|
||||
</gmd:topicCategory>
|
||||
<gmd:environmentDescription>
|
||||
<gco:CharacterString>The cartographic boundary files contain geographic data only and do not include display mapping software or statistical data. For information on how to use cartographic boundary file data with specific software package users shall contact the company that produced the software.</gco:CharacterString>
|
||||
</gmd:environmentDescription>
|
||||
<gmd:extent>
|
||||
<gmd:EX_Extent id="boundingExtent">
|
||||
<gmd:geographicElement>
|
||||
<gmd:EX_GeographicBoundingBox id="boundingGeographicBoundingBox">
|
||||
<gmd:westBoundLongitude>
|
||||
<gco:Decimal>-120.005746</gco:Decimal>
|
||||
</gmd:westBoundLongitude>
|
||||
<gmd:eastBoundLongitude>
|
||||
<gco:Decimal>-114.039648</gco:Decimal>
|
||||
</gmd:eastBoundLongitude>
|
||||
<gmd:southBoundLatitude>
|
||||
<gco:Decimal>35.001857</gco:Decimal>
|
||||
</gmd:southBoundLatitude>
|
||||
<gmd:northBoundLatitude>
|
||||
<gco:Decimal>42.002207</gco:Decimal>
|
||||
</gmd:northBoundLatitude>
|
||||
</gmd:EX_GeographicBoundingBox>
|
||||
</gmd:geographicElement>
|
||||
<gmd:temporalElement>
|
||||
<gmd:EX_TemporalExtent id="boundingTemporalExtent">
|
||||
<gmd:extent>
|
||||
<gml:TimeInstant gml:id="boundingTemporalExtentASingleDate">
|
||||
<gml:description>publication date</gml:description>
|
||||
<gml:timePosition>2023-04</gml:timePosition>
|
||||
</gml:TimeInstant>
|
||||
</gmd:extent>
|
||||
</gmd:EX_TemporalExtent>
|
||||
</gmd:temporalElement>
|
||||
</gmd:EX_Extent>
|
||||
</gmd:extent>
|
||||
</gmd:MD_DataIdentification>
|
||||
</gmd:identificationInfo>
|
||||
<gmd:contentInfo>
|
||||
<gmd:MD_FeatureCatalogueDescription>
|
||||
<gmd:includedWithDataset>
|
||||
<gco:Boolean>1</gco:Boolean>
|
||||
</gmd:includedWithDataset>
|
||||
<gmd:featureTypes>
|
||||
<gco:LocalName codeSpace="unknown">Block Groups</gco:LocalName>
|
||||
</gmd:featureTypes>
|
||||
<gmd:featureCatalogueCitation>
|
||||
<gmd:CI_Citation>
|
||||
<gmd:title>
|
||||
<gco:CharacterString>Feature Catalog for the 2022 Block Groups Cartographic Boundary File</gco:CharacterString>
|
||||
</gmd:title>
|
||||
<gmd:date>
|
||||
<gmd:CI_Date>
|
||||
<gmd:date>
|
||||
<gco:Date>2022</gco:Date>
|
||||
</gmd:date>
|
||||
<gmd:dateType>
|
||||
<gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode"
|
||||
codeListValue="publication">publication</gmd:CI_DateTypeCode>
|
||||
</gmd:dateType>
|
||||
</gmd:CI_Date>
|
||||
</gmd:date>
|
||||
<gmd:citedResponsibleParty>
|
||||
<gmd:CI_ResponsibleParty>
|
||||
<gmd:organisationName>
|
||||
<gco:CharacterString>U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch</gco:CharacterString>
|
||||
</gmd:organisationName>
|
||||
<gmd:contactInfo>
|
||||
<gmd:CI_Contact>
|
||||
<gmd:phone>
|
||||
<gmd:CI_Telephone>
|
||||
<gmd:voice>
|
||||
<gco:CharacterString>301-763-1128</gco:CharacterString>
|
||||
</gmd:voice>
|
||||
<gmd:facsimile>
|
||||
<gco:CharacterString>301-763-4710</gco:CharacterString>
|
||||
</gmd:facsimile>
|
||||
</gmd:CI_Telephone>
|
||||
</gmd:phone>
|
||||
<gmd:address>
|
||||
<gmd:CI_Address>
|
||||
<gmd:deliveryPoint>
|
||||
<gco:CharacterString>4600 Silver Hill Road, Stop 7400</gco:CharacterString>
|
||||
</gmd:deliveryPoint>
|
||||
<gmd:city>
|
||||
<gco:CharacterString>Washington</gco:CharacterString>
|
||||
</gmd:city>
|
||||
<gmd:administrativeArea>
|
||||
<gco:CharacterString>DC</gco:CharacterString>
|
||||
</gmd:administrativeArea>
|
||||
<gmd:postalCode>
|
||||
<gco:CharacterString>20233-7400</gco:CharacterString>
|
||||
</gmd:postalCode>
|
||||
<gmd:country>
|
||||
<gco:CharacterString>United States</gco:CharacterString>
|
||||
</gmd:country>
|
||||
<gmd:electronicMailAddress>
|
||||
<gco:CharacterString>geo.geography@census.gov</gco:CharacterString>
|
||||
</gmd:electronicMailAddress>
|
||||
</gmd:CI_Address>
|
||||
</gmd:address>
|
||||
</gmd:CI_Contact>
|
||||
</gmd:contactInfo>
|
||||
<gmd:role>
|
||||
<gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode"
|
||||
codeListValue="pointOfContact">pointOfContact</gmd:CI_RoleCode>
|
||||
</gmd:role>
|
||||
</gmd:CI_ResponsibleParty>
|
||||
</gmd:citedResponsibleParty>
|
||||
<gmd:otherCitationDetails>
|
||||
<gco:CharacterString>https://meta.geo.census.gov/data/existing/decennial/GEO/CPMB/boundary/2022/shp/19110/cb_2022_32_bg_500k.shp.ea.iso.xml</gco:CharacterString>
|
||||
</gmd:otherCitationDetails>
|
||||
</gmd:CI_Citation>
|
||||
</gmd:featureCatalogueCitation>
|
||||
</gmd:MD_FeatureCatalogueDescription>
|
||||
</gmd:contentInfo>
|
||||
<gmd:distributionInfo>
|
||||
<gmd:MD_Distribution>
|
||||
<gmd:distributionFormat>
|
||||
<gmd:MD_Format>
|
||||
<gmd:name>
|
||||
<gco:CharacterString>ZIP</gco:CharacterString>
|
||||
</gmd:name>
|
||||
<gmd:version gco:nilReason="unknown"/>
|
||||
</gmd:MD_Format>
|
||||
</gmd:distributionFormat>
|
||||
<gmd:distributor>
|
||||
<gmd:MD_Distributor>
|
||||
<gmd:distributorContact>
|
||||
<gmd:CI_ResponsibleParty>
|
||||
<gmd:organisationName>
|
||||
<gco:CharacterString>U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch</gco:CharacterString>
|
||||
</gmd:organisationName>
|
||||
<gmd:contactInfo>
|
||||
<gmd:CI_Contact>
|
||||
<gmd:phone>
|
||||
<gmd:CI_Telephone>
|
||||
<gmd:voice>
|
||||
<gco:CharacterString>301-763-1128</gco:CharacterString>
|
||||
</gmd:voice>
|
||||
<gmd:facsimile>
|
||||
<gco:CharacterString>301-763-4710</gco:CharacterString>
|
||||
</gmd:facsimile>
|
||||
</gmd:CI_Telephone>
|
||||
</gmd:phone>
|
||||
<gmd:address>
|
||||
<gmd:CI_Address>
|
||||
<gmd:deliveryPoint>
|
||||
<gco:CharacterString>4600 Silver Hill Road, Stop 7400</gco:CharacterString>
|
||||
</gmd:deliveryPoint>
|
||||
<gmd:city>
|
||||
<gco:CharacterString>Washington</gco:CharacterString>
|
||||
</gmd:city>
|
||||
<gmd:administrativeArea>
|
||||
<gco:CharacterString>DC</gco:CharacterString>
|
||||
</gmd:administrativeArea>
|
||||
<gmd:postalCode>
|
||||
<gco:CharacterString>20233-7400</gco:CharacterString>
|
||||
</gmd:postalCode>
|
||||
<gmd:country>
|
||||
<gco:CharacterString>United States</gco:CharacterString>
|
||||
</gmd:country>
|
||||
<gmd:electronicMailAddress>
|
||||
<gco:CharacterString>geo.geography@census.gov</gco:CharacterString>
|
||||
</gmd:electronicMailAddress>
|
||||
</gmd:CI_Address>
|
||||
</gmd:address>
|
||||
</gmd:CI_Contact>
|
||||
</gmd:contactInfo>
|
||||
<gmd:role>
|
||||
<gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode"
|
||||
codeListValue="distributor">distributor</gmd:CI_RoleCode>
|
||||
</gmd:role>
|
||||
</gmd:CI_ResponsibleParty>
|
||||
</gmd:distributorContact>
|
||||
<gmd:distributionOrderProcess>
|
||||
<gmd:MD_StandardOrderProcess>
|
||||
<gmd:fees>
|
||||
<gco:CharacterString>The online cartographic boundary files may be downloaded without charge.</gco:CharacterString>
|
||||
</gmd:fees>
|
||||
</gmd:MD_StandardOrderProcess>
|
||||
</gmd:distributionOrderProcess>
|
||||
</gmd:MD_Distributor>
|
||||
</gmd:distributor>
|
||||
<gmd:transferOptions>
|
||||
<gmd:MD_DigitalTransferOptions>
|
||||
<gmd:onLine>
|
||||
<gmd:CI_OnlineResource>
|
||||
<gmd:linkage>
|
||||
<gmd:URL>https://www2.census.gov/geo/tiger/GENZ2022/shp/cb_2022_32_bg_500k.zip</gmd:URL>
|
||||
</gmd:linkage>
|
||||
<gmd:applicationProfile>
|
||||
<gco:CharacterString>Shapefile Zip File</gco:CharacterString>
|
||||
</gmd:applicationProfile>
|
||||
<gmd:name>
|
||||
<gco:CharacterString>cb_2022_32_bg_500k.zip</gco:CharacterString>
|
||||
</gmd:name>
|
||||
<gmd:description>
|
||||
<gco:CharacterString>The cartographic boundary files are simplified representations of selected geographic areas specifically designed for small scale thematic mapping. These files contain simplified extracts of selected geographic areas from the U.S. Census Bureau's Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) database.</gco:CharacterString>
|
||||
</gmd:description>
|
||||
<gmd:function>
|
||||
<gmd:CI_OnLineFunctionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_OnlineFunctionCode"
|
||||
codeListValue="download">download</gmd:CI_OnLineFunctionCode>
|
||||
</gmd:function>
|
||||
</gmd:CI_OnlineResource>
|
||||
</gmd:onLine>
|
||||
</gmd:MD_DigitalTransferOptions>
|
||||
</gmd:transferOptions>
|
||||
<gmd:transferOptions>
|
||||
<gmd:MD_DigitalTransferOptions>
|
||||
<gmd:onLine>
|
||||
<gmd:CI_OnlineResource>
|
||||
<gmd:linkage>
|
||||
<gmd:URL>https://meta.geo.census.gov/data/existing/decennial/GEO/CPMB/boundary/2022/shp/19110/cb_2022_32_bg_500k.shp.ea.iso.xml</gmd:URL>
|
||||
</gmd:linkage>
|
||||
<gmd:applicationProfile>
|
||||
<gco:CharacterString>XML</gco:CharacterString>
|
||||
</gmd:applicationProfile>
|
||||
<gmd:name>
|
||||
<gco:CharacterString>cb_2022_32_bg_500k.shp.ea.iso.xml</gco:CharacterString>
|
||||
</gmd:name>
|
||||
<gmd:description>
|
||||
<gco:CharacterString>Entity and attribute file</gco:CharacterString>
|
||||
</gmd:description>
|
||||
<gmd:function>
|
||||
<gmd:CI_OnLineFunctionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_OnlineFunctionCode"
|
||||
codeListValue="download">download</gmd:CI_OnLineFunctionCode>
|
||||
</gmd:function>
|
||||
</gmd:CI_OnlineResource>
|
||||
</gmd:onLine>
|
||||
</gmd:MD_DigitalTransferOptions>
|
||||
</gmd:transferOptions>
|
||||
<gmd:transferOptions>
|
||||
<gmd:MD_DigitalTransferOptions>
|
||||
<gmd:onLine>
|
||||
<gmd:CI_OnlineResource>
|
||||
<gmd:linkage>
|
||||
<gmd:URL>https://www2.census.gov/geo/tiger/GENZ2022/2022_file_name_def.pdf</gmd:URL>
|
||||
</gmd:linkage>
|
||||
<gmd:applicationProfile>
|
||||
<gco:CharacterString>PDF</gco:CharacterString>
|
||||
</gmd:applicationProfile>
|
||||
<gmd:name>
|
||||
<gco:CharacterString>2022_file_name_def.pdf</gco:CharacterString>
|
||||
</gmd:name>
|
||||
<gmd:description>
|
||||
<gco:CharacterString>The file naming convention for the cartographic boundary files.</gco:CharacterString>
|
||||
</gmd:description>
|
||||
<gmd:function>
|
||||
<gmd:CI_OnLineFunctionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_OnlineFunctionCode"
|
||||
codeListValue="search">search</gmd:CI_OnLineFunctionCode>
|
||||
</gmd:function>
|
||||
</gmd:CI_OnlineResource>
|
||||
</gmd:onLine>
|
||||
</gmd:MD_DigitalTransferOptions>
|
||||
</gmd:transferOptions>
|
||||
<gmd:transferOptions>
|
||||
<gmd:MD_DigitalTransferOptions>
|
||||
<gmd:onLine>
|
||||
<gmd:CI_OnlineResource>
|
||||
<gmd:linkage>
|
||||
<gmd:URL>https://www2.census.gov/geo/tiger/GENZ2022/description.pdf</gmd:URL>
|
||||
</gmd:linkage>
|
||||
<gmd:applicationProfile>
|
||||
<gco:CharacterString>PDF</gco:CharacterString>
|
||||
</gmd:applicationProfile>
|
||||
<gmd:name>
|
||||
<gco:CharacterString>description.pdf</gco:CharacterString>
|
||||
</gmd:name>
|
||||
<gmd:description>
|
||||
<gco:CharacterString>General description of the cartographic boundary files and their appropriate use.</gco:CharacterString>
|
||||
</gmd:description>
|
||||
<gmd:function>
|
||||
<gmd:CI_OnLineFunctionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_OnlineFunctionCode"
|
||||
codeListValue="search">search</gmd:CI_OnLineFunctionCode>
|
||||
</gmd:function>
|
||||
</gmd:CI_OnlineResource>
|
||||
</gmd:onLine>
|
||||
</gmd:MD_DigitalTransferOptions>
|
||||
</gmd:transferOptions>
|
||||
</gmd:MD_Distribution>
|
||||
</gmd:distributionInfo>
|
||||
<gmd:dataQualityInfo>
|
||||
<gmd:DQ_DataQuality>
|
||||
<gmd:scope>
|
||||
<gmd:DQ_Scope>
|
||||
<gmd:level>
|
||||
<gmd:MD_ScopeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ScopeCode"
|
||||
codeListValue="dataset">dataset</gmd:MD_ScopeCode>
|
||||
</gmd:level>
|
||||
</gmd:DQ_Scope>
|
||||
</gmd:scope>
|
||||
<gmd:report>
|
||||
<gmd:DQ_ConceptualConsistency>
|
||||
<gmd:measureDescription>
|
||||
<gco:CharacterString>The Census Bureau performed automated tests to ensure logical consistency and limits of shapefiles. Segments making up the outer and inner boundaries of a polygon tie end-to-end to completely enclose the area. All polygons are tested for closure.
|
||||
The Census Bureau uses its internally developed geographic update system to enhance and modify spatial and attribute data in the Census MAF/TIGER database. Standard geographic codes, such as FIPS codes for states, counties, municipalities, county subdivisions, places, American Indian/Alaska Native/Native Hawaiian areas, and congressional districts are used when encoding spatial entities. The Census Bureau performed spatial data tests for logical consistency of the codes during the compilation of the original Census MAF/TIGER database files. Most of the codes for geographic entities except states, counties, urban areas, Core Based Statistical Areas (CBSAs), American Indian Areas (AIAs), and congressional districts were provided to the Census Bureau by the USGS, the agency responsible for maintaining the Geographic Names Information System (GNIS). Feature attribute information has been examined but has not been fully tested for consistency.
|
||||
For the Cartographic Boundary Files, the Point and Vector Object Count for the G-polygon SDTS Point and Vector Object Type reflects the number of records in the shapefile attribute table. For multi-polygon features, only one attribute record exists for each multi-polygon rather than one attribute record per individual G-polygon component of the multi-polygon feature. Cartographic Boundary File multi-polygons are an exception to the G-polygon object type classification. Therefore, when multi-polygons exist in a shapefile, the object count will be less than the actual number of G-polygons.</gco:CharacterString>
|
||||
</gmd:measureDescription>
|
||||
<gmd:result gco:nilReason="unknown"/>
|
||||
</gmd:DQ_ConceptualConsistency>
|
||||
</gmd:report>
|
||||
<gmd:report>
|
||||
<gmd:DQ_CompletenessOmission>
|
||||
<gmd:evaluationMethodDescription>
|
||||
<gco:CharacterString>The cartographic boundary files are generalized representations of extracts taken from the MAF/TIGER database. Generalized boundary files are clipped to a simplified version of the U.S. outline. As a result, some off-shore areas may be excluded from the generalized files. Some small geographic areas, holes, or discontiguous parts of areas may not be included in generalized files if they are not visible at the target scale.</gco:CharacterString>
|
||||
</gmd:evaluationMethodDescription>
|
||||
<gmd:result gco:nilReason="unknown"/>
|
||||
</gmd:DQ_CompletenessOmission>
|
||||
</gmd:report>
|
||||
<gmd:report>
|
||||
<gmd:DQ_CompletenessCommission>
|
||||
<gmd:evaluationMethodDescription>
|
||||
<gco:CharacterString>The cartographic boundary files are generalized representations of extracts taken from the MAF/TIGER database. Generalized boundary files are clipped to a simplified version of the U.S. outline. As a result, some off-shore areas may be excluded from the generalized files. Some small geographic areas, holes, or discontiguous parts of areas may not be included in generalized files if they are not visible at the target scale.</gco:CharacterString>
|
||||
</gmd:evaluationMethodDescription>
|
||||
<gmd:result gco:nilReason="unknown"/>
|
||||
</gmd:DQ_CompletenessCommission>
|
||||
</gmd:report>
|
||||
</gmd:DQ_DataQuality>
|
||||
</gmd:dataQualityInfo>
|
||||
<gmd:metadataMaintenance>
|
||||
<gmd:MD_MaintenanceInformation>
|
||||
<gmd:maintenanceAndUpdateFrequency>
|
||||
<gmd:MD_MaintenanceFrequencyCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_MaintenanceFrequencyCode"
|
||||
codeListValue="notPlanned">notPlanned</gmd:MD_MaintenanceFrequencyCode>
|
||||
</gmd:maintenanceAndUpdateFrequency>
|
||||
<gmd:maintenanceNote>
|
||||
<gco:CharacterString>This was transformed from the Census Bureau Geospatial Product Metadata Content Standard.</gco:CharacterString>
|
||||
</gmd:maintenanceNote>
|
||||
</gmd:MD_MaintenanceInformation>
|
||||
</gmd:metadataMaintenance>
|
||||
</gmi:MI_Metadata>
|
||||
Binary file not shown.
@@ -0,0 +1 @@
|
||||
UTF-8
|
||||
Binary file not shown.
@@ -0,0 +1 @@
|
||||
GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137,298.257222101]],PRIMEM["Greenwich",0],UNIT["Degree",0.017453292519943295]]
|
||||
Binary file not shown.
+300
@@ -0,0 +1,300 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<gfc:FC_FeatureCatalogue xmlns:xlink="http://www.w3.org/1999/xlink"
|
||||
xmlns:gmd="http://www.isotc211.org/2005/gmd"
|
||||
xmlns:gco="http://www.isotc211.org/2005/gco"
|
||||
xmlns:gml="http://www.opengis.net/gml/3.2"
|
||||
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
|
||||
xmlns:gmi="http://www.isotc211.org/2005/gmi"
|
||||
xmlns:srv="http://www.isotc211.org/2005/srv"
|
||||
xmlns:gmx="http://www.isotc211.org/2005/gmx"
|
||||
xmlns:gfc="http://www.isotc211.org/2005/gfc">
|
||||
<gmx:name>
|
||||
<gco:CharacterString>Feature Catalog for the 2022 States and Equivalent Areas Cartographic Boundary File</gco:CharacterString>
|
||||
</gmx:name>
|
||||
<gmx:scope>
|
||||
<gco:CharacterString>States and Equivalent Areas</gco:CharacterString>
|
||||
</gmx:scope>
|
||||
<gmx:versionNumber>
|
||||
<gco:CharacterString>2023-04</gco:CharacterString>
|
||||
</gmx:versionNumber>
|
||||
<gmx:versionDate>
|
||||
<gco:Date>2023-04</gco:Date>
|
||||
</gmx:versionDate>
|
||||
<gmx:language>
|
||||
<gco:CharacterString>eng; USA</gco:CharacterString>
|
||||
</gmx:language>
|
||||
<gmx:characterSet>
|
||||
<gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode"
|
||||
codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>
|
||||
</gmx:characterSet>
|
||||
<gfc:producer>
|
||||
<gmd:CI_ResponsibleParty>
|
||||
<gmd:organisationName>
|
||||
<gco:CharacterString>U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch</gco:CharacterString>
|
||||
</gmd:organisationName>
|
||||
<gmd:contactInfo>
|
||||
<gmd:CI_Contact>
|
||||
<gmd:phone>
|
||||
<gmd:CI_Telephone>
|
||||
<gmd:voice>
|
||||
<gco:CharacterString>301-763-1128</gco:CharacterString>
|
||||
</gmd:voice>
|
||||
<gmd:facsimile>
|
||||
<gco:CharacterString>301-763-4710</gco:CharacterString>
|
||||
</gmd:facsimile>
|
||||
</gmd:CI_Telephone>
|
||||
</gmd:phone>
|
||||
<gmd:address>
|
||||
<gmd:CI_Address>
|
||||
<gmd:deliveryPoint>
|
||||
<gco:CharacterString>4600 Silver Hill Road, Stop 7400</gco:CharacterString>
|
||||
</gmd:deliveryPoint>
|
||||
<gmd:city>
|
||||
<gco:CharacterString>Washington</gco:CharacterString>
|
||||
</gmd:city>
|
||||
<gmd:administrativeArea>
|
||||
<gco:CharacterString>DC</gco:CharacterString>
|
||||
</gmd:administrativeArea>
|
||||
<gmd:postalCode>
|
||||
<gco:CharacterString>20233-7400</gco:CharacterString>
|
||||
</gmd:postalCode>
|
||||
<gmd:country>
|
||||
<gco:CharacterString>United States</gco:CharacterString>
|
||||
</gmd:country>
|
||||
<gmd:electronicMailAddress>
|
||||
<gco:CharacterString>geo.geography@census.gov</gco:CharacterString>
|
||||
</gmd:electronicMailAddress>
|
||||
</gmd:CI_Address>
|
||||
</gmd:address>
|
||||
</gmd:CI_Contact>
|
||||
</gmd:contactInfo>
|
||||
<gmd:role>
|
||||
<gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode"
|
||||
codeListValue="pointOfContact">pointOfContact</gmd:CI_RoleCode>
|
||||
</gmd:role>
|
||||
</gmd:CI_ResponsibleParty>
|
||||
</gfc:producer>
|
||||
<gfc:featureType>
|
||||
<gfc:FC_FeatureType>
|
||||
<gfc:typeName>
|
||||
<gco:LocalName>cb_2022_us_state_20m.shp</gco:LocalName>
|
||||
</gfc:typeName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current State and Equivalent (national)</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:isAbstract>
|
||||
<gco:Boolean>false</gco:Boolean>
|
||||
</gfc:isAbstract>
|
||||
<gfc:featureCatalogue uuidref="cb_2022_us_state_20m.shp.ea.iso.xml"/>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>STATEFP</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current state Federal Information Processing Series (FIPS) code</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality gco:nilReason="unknown"/>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label>
|
||||
<gco:CharacterString>National Standard Codes (ANSI INCITS 38-2009), Federal Information Processing Series (FIPS) - States/State Equivalents</gco:CharacterString>
|
||||
</gfc:label>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>STATENS</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current state Geographic Names Information System (GNIS) code</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality gco:nilReason="unknown"/>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label>
|
||||
<gco:CharacterString>INCITS 446:2008 (Geographic Names Information System (GNIS)), Identifying Attributes for Named Physical and Cultural Geographic Features (Except Roads and Highways) of the United States, Its Territories, Outlying Areas, and Freely Associated Areas, and the Waters of the Same to the Limit of the Twelve-Mile Statutory Zone</gco:CharacterString>
|
||||
</gfc:label>
|
||||
<gfc:definitionReference xlink:title="United States Geological Survey (USGS)"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/8d0b86d3-09b4-4fc4-8e8e-2922517fe12d "/>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>AFFGEOID</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>American FactFinder summary level code + geovariant code + '00US' + GEOID</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality gco:nilReason="unknown"/>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label>
|
||||
<gco:CharacterString>American FactFinder geographic identifier</gco:CharacterString>
|
||||
</gfc:label>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>GEOID</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>State identifier; state FIPS code</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality gco:nilReason="unknown"/>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label>
|
||||
<gco:CharacterString>National Standard Codes (ANSI INCITS 38-2009), Federal Information Processing Series (FIPS) - States/State Equivalents</gco:CharacterString>
|
||||
</gfc:label>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>STUSPS</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current United States Postal Service state abbreviation</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality gco:nilReason="unknown"/>
|
||||
<gfc:definitionReference xlink:title="U.S. Postal Service"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/2de06071-f4d0-49b7-bd93-ba7a38e5d911 "/>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label>
|
||||
<gco:CharacterString>Publication 28 - Postal Addressing Standards</gco:CharacterString>
|
||||
</gfc:label>
|
||||
<gfc:definitionReference xlink:title="U.S. Postal Service"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/2de06071-f4d0-49b7-bd93-ba7a38e5d911 "/>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>NAME</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current State name</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality gco:nilReason="unknown"/>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label>
|
||||
<gco:CharacterString>National Standard Codes (ANSI INCITS 38-2009), Federal Information Processing Series (FIPS) - States/State Equivalents</gco:CharacterString>
|
||||
</gfc:label>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>LSAD</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current legal/statistical area description code for state</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality gco:nilReason="unknown"/>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
<gfc:listedValue>
|
||||
<gfc:FC_ListedValue>
|
||||
<gfc:label>
|
||||
<gco:CharacterString>00</gco:CharacterString>
|
||||
</gfc:label>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Blank</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_ListedValue>
|
||||
</gfc:listedValue>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>ALAND</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current land area (square meters)</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality>
|
||||
<gco:Multiplicity>
|
||||
<gco:range>
|
||||
<gco:MultiplicityRange>
|
||||
<gco:lower>
|
||||
<gco:Integer>0</gco:Integer>
|
||||
</gco:lower>
|
||||
<gco:upper>
|
||||
<gco:UnlimitedInteger>9,999,999,999,999</gco:UnlimitedInteger>
|
||||
</gco:upper>
|
||||
</gco:MultiplicityRange>
|
||||
</gco:range>
|
||||
</gco:Multiplicity>
|
||||
</gfc:cardinality>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
<gfc:carrierOfCharacteristics>
|
||||
<gfc:FC_FeatureAttribute>
|
||||
<gfc:memberName>
|
||||
<gco:LocalName>AWATER</gco:LocalName>
|
||||
</gfc:memberName>
|
||||
<gfc:definition>
|
||||
<gco:CharacterString>Current water area (square meters)</gco:CharacterString>
|
||||
</gfc:definition>
|
||||
<gfc:cardinality>
|
||||
<gco:Multiplicity>
|
||||
<gco:range>
|
||||
<gco:MultiplicityRange>
|
||||
<gco:lower>
|
||||
<gco:Integer>0</gco:Integer>
|
||||
</gco:lower>
|
||||
<gco:upper>
|
||||
<gco:UnlimitedInteger>9,999,999,999,999</gco:UnlimitedInteger>
|
||||
</gco:upper>
|
||||
</gco:MultiplicityRange>
|
||||
</gco:range>
|
||||
</gco:Multiplicity>
|
||||
</gfc:cardinality>
|
||||
<gfc:definitionReference xlink:title="U.S Census Bureau"
|
||||
xlink:href="http://www.ngdc.noaa.gov/docucomp/eb139e38-ee29-4d59-b157-5e874d4420c4"/>
|
||||
</gfc:FC_FeatureAttribute>
|
||||
</gfc:carrierOfCharacteristics>
|
||||
</gfc:FC_FeatureType>
|
||||
</gfc:featureType>
|
||||
</gfc:FC_FeatureCatalogue>
|
||||
+739
@@ -0,0 +1,739 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<gmi:MI_Metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
|
||||
xmlns:gmd="http://www.isotc211.org/2005/gmd"
|
||||
xmlns:gco="http://www.isotc211.org/2005/gco"
|
||||
xmlns:gml="http://www.opengis.net/gml/3.2"
|
||||
xmlns:gmi="http://www.isotc211.org/2005/gmi"
|
||||
xmlns:xlink="http://www.w3.org/1999/xlink"
|
||||
xmlns:srv="http://www.isotc211.org/2005/srv"
|
||||
xsi:schemaLocation="http://www.isotc211.org/2005/gmi https://data.noaa.gov/resources/iso19139/schema.xsd">
|
||||
<gmd:fileIdentifier>
|
||||
<gco:CharacterString>cb_2022_us_state_20m.shp.iso.xml</gco:CharacterString>
|
||||
</gmd:fileIdentifier>
|
||||
<gmd:language>
|
||||
<gco:CharacterString>eng; USA</gco:CharacterString>
|
||||
</gmd:language>
|
||||
<gmd:characterSet>
|
||||
<gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode"
|
||||
codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>
|
||||
</gmd:characterSet>
|
||||
<gmd:hierarchyLevel>
|
||||
<gmd:MD_ScopeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ScopeCode"
|
||||
codeListValue="dataset">dataset</gmd:MD_ScopeCode>
|
||||
</gmd:hierarchyLevel>
|
||||
<gmd:contact>
|
||||
<gmd:CI_ResponsibleParty>
|
||||
<gmd:organisationName>
|
||||
<gco:CharacterString>U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch</gco:CharacterString>
|
||||
</gmd:organisationName>
|
||||
<gmd:contactInfo>
|
||||
<gmd:CI_Contact>
|
||||
<gmd:phone>
|
||||
<gmd:CI_Telephone>
|
||||
<gmd:voice>
|
||||
<gco:CharacterString>301-763-1128</gco:CharacterString>
|
||||
</gmd:voice>
|
||||
<gmd:facsimile>
|
||||
<gco:CharacterString>301-763-4710</gco:CharacterString>
|
||||
</gmd:facsimile>
|
||||
</gmd:CI_Telephone>
|
||||
</gmd:phone>
|
||||
<gmd:address>
|
||||
<gmd:CI_Address>
|
||||
<gmd:deliveryPoint>
|
||||
<gco:CharacterString>4600 Silver Hill Road, Stop 7400</gco:CharacterString>
|
||||
</gmd:deliveryPoint>
|
||||
<gmd:city>
|
||||
<gco:CharacterString>Washington</gco:CharacterString>
|
||||
</gmd:city>
|
||||
<gmd:administrativeArea>
|
||||
<gco:CharacterString>DC</gco:CharacterString>
|
||||
</gmd:administrativeArea>
|
||||
<gmd:postalCode>
|
||||
<gco:CharacterString>20233-7400</gco:CharacterString>
|
||||
</gmd:postalCode>
|
||||
<gmd:country>
|
||||
<gco:CharacterString>United States</gco:CharacterString>
|
||||
</gmd:country>
|
||||
<gmd:electronicMailAddress>
|
||||
<gco:CharacterString>geo.geography@census.gov</gco:CharacterString>
|
||||
</gmd:electronicMailAddress>
|
||||
</gmd:CI_Address>
|
||||
</gmd:address>
|
||||
</gmd:CI_Contact>
|
||||
</gmd:contactInfo>
|
||||
<gmd:role>
|
||||
<gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode"
|
||||
codeListValue="pointOfContact">pointOfContact</gmd:CI_RoleCode>
|
||||
</gmd:role>
|
||||
</gmd:CI_ResponsibleParty>
|
||||
</gmd:contact>
|
||||
<gmd:dateStamp>
|
||||
<gco:Date>2023-04</gco:Date>
|
||||
</gmd:dateStamp>
|
||||
<gmd:metadataStandardName>
|
||||
<gco:CharacterString>ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data</gco:CharacterString>
|
||||
</gmd:metadataStandardName>
|
||||
<gmd:metadataStandardVersion>
|
||||
<gco:CharacterString>ISO 19115-2:2009(E)</gco:CharacterString>
|
||||
</gmd:metadataStandardVersion>
|
||||
<gmd:dataSetURI>
|
||||
<gco:CharacterString>https://meta.geo.census.gov/data/existing/decennial/GEO/CPMB/boundary/2022/shp/19115/cb_2022_us_state_20m.shp.iso.xml</gco:CharacterString>
|
||||
</gmd:dataSetURI>
|
||||
<gmd:spatialRepresentationInfo>
|
||||
<gmd:MD_VectorSpatialRepresentation>
|
||||
<gmd:geometricObjects>
|
||||
<gmd:MD_GeometricObjects>
|
||||
<gmd:geometricObjectType>
|
||||
<gmd:MD_GeometricObjectTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_GeometricObjectTypeCode"
|
||||
codeListValue="complex">complex</gmd:MD_GeometricObjectTypeCode>
|
||||
</gmd:geometricObjectType>
|
||||
<gmd:geometricObjectCount>
|
||||
<gco:Integer>52</gco:Integer>
|
||||
</gmd:geometricObjectCount>
|
||||
</gmd:MD_GeometricObjects>
|
||||
</gmd:geometricObjects>
|
||||
</gmd:MD_VectorSpatialRepresentation>
|
||||
</gmd:spatialRepresentationInfo>
|
||||
<gmd:referenceSystemInfo>
|
||||
<gmd:MD_ReferenceSystem uuid="65f8b220-95ed-11e0-aa80-0800200c9a66">
|
||||
<gmd:referenceSystemIdentifier>
|
||||
<gmd:RS_Identifier>
|
||||
<gmd:authority>
|
||||
<gmd:CI_Citation>
|
||||
<gmd:title>
|
||||
<gco:CharacterString>North American Datum of 1983</gco:CharacterString>
|
||||
</gmd:title>
|
||||
<gmd:alternateTitle>
|
||||
<gco:CharacterString>NAD83</gco:CharacterString>
|
||||
</gmd:alternateTitle>
|
||||
<gmd:date>
|
||||
<gmd:CI_Date>
|
||||
<gmd:date>
|
||||
<gco:Date>2007-01-19</gco:Date>
|
||||
</gmd:date>
|
||||
<gmd:dateType>
|
||||
<gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode"
|
||||
codeListValue="revision">revision</gmd:CI_DateTypeCode>
|
||||
</gmd:dateType>
|
||||
</gmd:CI_Date>
|
||||
</gmd:date>
|
||||
<gmd:citedResponsibleParty>
|
||||
<gmd:CI_ResponsibleParty>
|
||||
<gmd:organisationName gco:nilReason="withheld"/>
|
||||
<gmd:contactInfo>
|
||||
<gmd:CI_Contact>
|
||||
<gmd:onlineResource>
|
||||
<gmd:CI_OnlineResource>
|
||||
<gmd:linkage>
|
||||
<gmd:URL>https://spatialreference.org/ref/epsg/4269/gml/</gmd:URL>
|
||||
</gmd:linkage>
|
||||
<gmd:name>
|
||||
<gco:CharacterString>NAD83</gco:CharacterString>
|
||||
</gmd:name>
|
||||
<gmd:description>
|
||||
<gco:CharacterString>Link to Geographic Markup Language (GML) description of reference system.</gco:CharacterString>
|
||||
</gmd:description>
|
||||
<gmd:function>
|
||||
<gmd:CI_OnLineFunctionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_OnLineFunctionCode"
|
||||
codeListValue="information">information</gmd:CI_OnLineFunctionCode>
|
||||
</gmd:function>
|
||||
</gmd:CI_OnlineResource>
|
||||
</gmd:onlineResource>
|
||||
</gmd:CI_Contact>
|
||||
</gmd:contactInfo>
|
||||
<gmd:role>
|
||||
<gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode"
|
||||
codeListValue="resourceProvider">resourceProvider</gmd:CI_RoleCode>
|
||||
</gmd:role>
|
||||
</gmd:CI_ResponsibleParty>
|
||||
</gmd:citedResponsibleParty>
|
||||
</gmd:CI_Citation>
|
||||
</gmd:authority>
|
||||
<gmd:code>
|
||||
<gco:CharacterString>urn:ogc:def:crs:EPSG::4269</gco:CharacterString>
|
||||
</gmd:code>
|
||||
</gmd:RS_Identifier>
|
||||
</gmd:referenceSystemIdentifier>
|
||||
</gmd:MD_ReferenceSystem>
|
||||
</gmd:referenceSystemInfo>
|
||||
<gmd:identificationInfo>
|
||||
<gmd:MD_DataIdentification>
|
||||
<gmd:citation>
|
||||
<gmd:CI_Citation>
|
||||
<gmd:title>
|
||||
<gco:CharacterString>2022 Cartographic Boundary File (SHP), Current State and Equivalent for United States, 1:20,000,000</gco:CharacterString>
|
||||
</gmd:title>
|
||||
<gmd:date>
|
||||
<gmd:CI_Date>
|
||||
<gmd:date>
|
||||
<gco:Date>2023-04</gco:Date>
|
||||
</gmd:date>
|
||||
<gmd:dateType>
|
||||
<gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode"
|
||||
codeListValue="publication">publication</gmd:CI_DateTypeCode>
|
||||
</gmd:dateType>
|
||||
</gmd:CI_Date>
|
||||
</gmd:date>
|
||||
<gmd:date>
|
||||
<gmd:CI_Date>
|
||||
<gmd:date>
|
||||
<gco:Date>2023-04</gco:Date>
|
||||
</gmd:date>
|
||||
<gmd:dateType>
|
||||
<gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode"
|
||||
codeListValue="creation">creation</gmd:CI_DateTypeCode>
|
||||
</gmd:dateType>
|
||||
</gmd:CI_Date>
|
||||
</gmd:date>
|
||||
<gmd:date>
|
||||
<gmd:CI_Date>
|
||||
<gmd:date>
|
||||
<gco:Date>2023-04</gco:Date>
|
||||
</gmd:date>
|
||||
<gmd:dateType>
|
||||
<gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode"
|
||||
codeListValue="lastUpdate">lastUpdate</gmd:CI_DateTypeCode>
|
||||
</gmd:dateType>
|
||||
</gmd:CI_Date>
|
||||
</gmd:date>
|
||||
<gmd:identifier>
|
||||
<gmd:MD_Identifier>
|
||||
<gmd:code>
|
||||
<gco:CharacterString>cb_2022_us_state_20m</gco:CharacterString>
|
||||
</gmd:code>
|
||||
</gmd:MD_Identifier>
|
||||
</gmd:identifier>
|
||||
<gmd:citedResponsibleParty>
|
||||
<gmd:CI_ResponsibleParty>
|
||||
<gmd:organisationName>
|
||||
<gco:CharacterString>U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch</gco:CharacterString>
|
||||
</gmd:organisationName>
|
||||
<gmd:contactInfo>
|
||||
<gmd:CI_Contact>
|
||||
<gmd:phone>
|
||||
<gmd:CI_Telephone>
|
||||
<gmd:voice>
|
||||
<gco:CharacterString>301-763-1128</gco:CharacterString>
|
||||
</gmd:voice>
|
||||
<gmd:facsimile>
|
||||
<gco:CharacterString>301-763-4710</gco:CharacterString>
|
||||
</gmd:facsimile>
|
||||
</gmd:CI_Telephone>
|
||||
</gmd:phone>
|
||||
<gmd:address>
|
||||
<gmd:CI_Address>
|
||||
<gmd:deliveryPoint>
|
||||
<gco:CharacterString>4600 Silver Hill Road, Stop 7400</gco:CharacterString>
|
||||
</gmd:deliveryPoint>
|
||||
<gmd:city>
|
||||
<gco:CharacterString>Washington</gco:CharacterString>
|
||||
</gmd:city>
|
||||
<gmd:administrativeArea>
|
||||
<gco:CharacterString>DC</gco:CharacterString>
|
||||
</gmd:administrativeArea>
|
||||
<gmd:postalCode>
|
||||
<gco:CharacterString>20233-7400</gco:CharacterString>
|
||||
</gmd:postalCode>
|
||||
<gmd:country>
|
||||
<gco:CharacterString>United States</gco:CharacterString>
|
||||
</gmd:country>
|
||||
<gmd:electronicMailAddress>
|
||||
<gco:CharacterString>geo.geography@census.gov</gco:CharacterString>
|
||||
</gmd:electronicMailAddress>
|
||||
</gmd:CI_Address>
|
||||
</gmd:address>
|
||||
</gmd:CI_Contact>
|
||||
</gmd:contactInfo>
|
||||
<gmd:role>
|
||||
<gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode"
|
||||
codeListValue="pointOfContact">pointOfContact</gmd:CI_RoleCode>
|
||||
</gmd:role>
|
||||
</gmd:CI_ResponsibleParty>
|
||||
</gmd:citedResponsibleParty>
|
||||
<gmd:presentationForm>
|
||||
<gmd:CI_PresentationFormCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_PresentationFormCode"
|
||||
codeListValue="mapDigital">mapDigital</gmd:CI_PresentationFormCode>
|
||||
</gmd:presentationForm>
|
||||
</gmd:CI_Citation>
|
||||
</gmd:citation>
|
||||
<gmd:abstract>
|
||||
<gco:CharacterString>The 2022 cartographic boundary shapefiles are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files.
|
||||
|
||||
States and equivalent entities are the primary governmental divisions of the United States. In addition to the fifty states, the Census Bureau treats the District of Columbia, Puerto Rico, and each of the Island Areas (American Samoa, the Commonwealth of the Northern Mariana Islands, Guam, and the U.S. Virgin Islands) as the statistical equivalents of states for the purpose of data presentation.</gco:CharacterString>
|
||||
</gmd:abstract>
|
||||
<gmd:purpose>
|
||||
<gco:CharacterString>These files were specifically created to support small-scale thematic mapping. To improve the appearance of shapes at small scales, areas are represented with fewer vertices than detailed TIGER/Line Shapefiles. Cartographic boundary files take up less disk space than their ungeneralized counterparts. Cartographic boundary files take less time to render on screen than TIGER/Line Shapefiles. You can join this file with table data downloaded from American FactFinder by using the AFFGEOID field in the cartographic boundary file. If detailed boundaries are required, please use the TIGER/Line Shapefiles instead of the generalized cartographic boundary files.</gco:CharacterString>
|
||||
</gmd:purpose>
|
||||
<gmd:status>
|
||||
<gmd:MD_ProgressCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ProgressCode"
|
||||
codeListValue="completed">completed</gmd:MD_ProgressCode>
|
||||
</gmd:status>
|
||||
<gmd:pointOfContact>
|
||||
<gmd:CI_ResponsibleParty>
|
||||
<gmd:organisationName>
|
||||
<gco:CharacterString>U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch</gco:CharacterString>
|
||||
</gmd:organisationName>
|
||||
<gmd:contactInfo>
|
||||
<gmd:CI_Contact>
|
||||
<gmd:phone>
|
||||
<gmd:CI_Telephone>
|
||||
<gmd:voice>
|
||||
<gco:CharacterString>301-763-1128</gco:CharacterString>
|
||||
</gmd:voice>
|
||||
<gmd:facsimile>
|
||||
<gco:CharacterString>301-763-4710</gco:CharacterString>
|
||||
</gmd:facsimile>
|
||||
</gmd:CI_Telephone>
|
||||
</gmd:phone>
|
||||
<gmd:address>
|
||||
<gmd:CI_Address>
|
||||
<gmd:deliveryPoint>
|
||||
<gco:CharacterString>4600 Silver Hill Road, Stop 7400</gco:CharacterString>
|
||||
</gmd:deliveryPoint>
|
||||
<gmd:city>
|
||||
<gco:CharacterString>Washington</gco:CharacterString>
|
||||
</gmd:city>
|
||||
<gmd:administrativeArea>
|
||||
<gco:CharacterString>DC</gco:CharacterString>
|
||||
</gmd:administrativeArea>
|
||||
<gmd:postalCode>
|
||||
<gco:CharacterString>20233-7400</gco:CharacterString>
|
||||
</gmd:postalCode>
|
||||
<gmd:country>
|
||||
<gco:CharacterString>United States</gco:CharacterString>
|
||||
</gmd:country>
|
||||
<gmd:electronicMailAddress>
|
||||
<gco:CharacterString>geo.geography@census.gov</gco:CharacterString>
|
||||
</gmd:electronicMailAddress>
|
||||
</gmd:CI_Address>
|
||||
</gmd:address>
|
||||
</gmd:CI_Contact>
|
||||
</gmd:contactInfo>
|
||||
<gmd:role>
|
||||
<gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode"
|
||||
codeListValue="pointOfContact">pointOfContact</gmd:CI_RoleCode>
|
||||
</gmd:role>
|
||||
</gmd:CI_ResponsibleParty>
|
||||
</gmd:pointOfContact>
|
||||
<gmd:resourceMaintenance>
|
||||
<gmd:MD_MaintenanceInformation>
|
||||
<gmd:maintenanceAndUpdateFrequency>
|
||||
<gmd:MD_MaintenanceFrequencyCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_MaintenanceFrequencyCode"
|
||||
codeListValue="notPlanned">notPlanned</gmd:MD_MaintenanceFrequencyCode>
|
||||
</gmd:maintenanceAndUpdateFrequency>
|
||||
</gmd:MD_MaintenanceInformation>
|
||||
</gmd:resourceMaintenance>
|
||||
<gmd:descriptiveKeywords>
|
||||
<gmd:MD_Keywords>
|
||||
<gmd:keyword>
|
||||
<gco:CharacterString>2022</gco:CharacterString>
|
||||
</gmd:keyword>
|
||||
<gmd:keyword>
|
||||
<gco:CharacterString>SHP</gco:CharacterString>
|
||||
</gmd:keyword>
|
||||
<gmd:keyword>
|
||||
<gco:CharacterString>Cartographic Boundary</gco:CharacterString>
|
||||
</gmd:keyword>
|
||||
<gmd:keyword>
|
||||
<gco:CharacterString>Generalized</gco:CharacterString>
|
||||
</gmd:keyword>
|
||||
<gmd:type>
|
||||
<gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode"
|
||||
codeListValue="theme"/>
|
||||
</gmd:type>
|
||||
<gmd:thesaurusName>
|
||||
<gmd:CI_Citation>
|
||||
<gmd:title>
|
||||
<gco:CharacterString>None</gco:CharacterString>
|
||||
</gmd:title>
|
||||
<gmd:date gco:nilReason="unknown"/>
|
||||
</gmd:CI_Citation>
|
||||
</gmd:thesaurusName>
|
||||
</gmd:MD_Keywords>
|
||||
</gmd:descriptiveKeywords>
|
||||
<gmd:descriptiveKeywords>
|
||||
<gmd:MD_Keywords>
|
||||
<gmd:keyword>
|
||||
<gco:CharacterString>United States of America (the)</gco:CharacterString>
|
||||
</gmd:keyword>
|
||||
<gmd:keyword>
|
||||
<gco:CharacterString>US</gco:CharacterString>
|
||||
</gmd:keyword>
|
||||
<gmd:type>
|
||||
<gmd:MD_KeywordTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_KeywordTypeCode"
|
||||
codeListValue="place"/>
|
||||
</gmd:type>
|
||||
<gmd:thesaurusName>
|
||||
<gmd:CI_Citation>
|
||||
<gmd:title>
|
||||
<gco:CharacterString>ISO 3166 Codes for the representation of names of countries and their subdivisions</gco:CharacterString>
|
||||
</gmd:title>
|
||||
<gmd:date gco:nilReason="unknown"/>
|
||||
</gmd:CI_Citation>
|
||||
</gmd:thesaurusName>
|
||||
</gmd:MD_Keywords>
|
||||
</gmd:descriptiveKeywords>
|
||||
<gmd:resourceConstraints>
|
||||
<gmd:MD_LegalConstraints>
|
||||
<gmd:accessConstraints>
|
||||
<gmd:MD_RestrictionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_RestrictionCode"
|
||||
codeListValue="otherRestrictions">otherRestrictions</gmd:MD_RestrictionCode>
|
||||
</gmd:accessConstraints>
|
||||
<gmd:useConstraints>
|
||||
<gmd:MD_RestrictionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_RestrictionCode"
|
||||
codeListValue="otherRestrictions">otherRestrictions</gmd:MD_RestrictionCode>
|
||||
</gmd:useConstraints>
|
||||
<gmd:otherConstraints>
|
||||
<gco:CharacterString>Access_Constraints: None</gco:CharacterString>
|
||||
</gmd:otherConstraints>
|
||||
<gmd:otherConstraints>
|
||||
<gco:CharacterString>Use Constraints: The intended display scale for this file is 1:20,000,000. This file should not be displayed at scales larger than 1:20,000,000.
|
||||
|
||||
These products are free to use in a product or publication, however acknowledgement must be given to the U.S. Census Bureau as the source. The boundary information is for visual display at appropriate small scales only. Cartographic boundary files should not be used for geographic analysis including area or perimeter calculation. Files should not be used for geocoding addresses. Files should not be used for determining precise geographic area relationships.</gco:CharacterString>
|
||||
</gmd:otherConstraints>
|
||||
</gmd:MD_LegalConstraints>
|
||||
</gmd:resourceConstraints>
|
||||
<gmd:spatialRepresentationType>
|
||||
<gmd:MD_SpatialRepresentationTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_SpatialRepresentationTypeCode"
|
||||
codeListValue="vector">vector</gmd:MD_SpatialRepresentationTypeCode>
|
||||
</gmd:spatialRepresentationType>
|
||||
<gmd:language>
|
||||
<gco:CharacterString>eng; USA</gco:CharacterString>
|
||||
</gmd:language>
|
||||
<gmd:characterSet>
|
||||
<gmd:MD_CharacterSetCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_CharacterSetCode"
|
||||
codeListValue="utf8">utf8</gmd:MD_CharacterSetCode>
|
||||
</gmd:characterSet>
|
||||
<gmd:topicCategory>
|
||||
<gmd:MD_TopicCategoryCode>boundaries</gmd:MD_TopicCategoryCode>
|
||||
</gmd:topicCategory>
|
||||
<gmd:environmentDescription>
|
||||
<gco:CharacterString>The cartographic boundary files contain geographic data only and do not include display mapping software or statistical data. For information on how to use cartographic boundary file data with specific software package users shall contact the company that produced the software.</gco:CharacterString>
|
||||
</gmd:environmentDescription>
|
||||
<gmd:extent>
|
||||
<gmd:EX_Extent id="boundingExtent">
|
||||
<gmd:geographicElement>
|
||||
<gmd:EX_GeographicBoundingBox id="boundingGeographicBoundingBox">
|
||||
<gmd:westBoundLongitude>
|
||||
<gco:Decimal>-179.174265</gco:Decimal>
|
||||
</gmd:westBoundLongitude>
|
||||
<gmd:eastBoundLongitude>
|
||||
<gco:Decimal>179.773922</gco:Decimal>
|
||||
</gmd:eastBoundLongitude>
|
||||
<gmd:southBoundLatitude>
|
||||
<gco:Decimal>17.913769</gco:Decimal>
|
||||
</gmd:southBoundLatitude>
|
||||
<gmd:northBoundLatitude>
|
||||
<gco:Decimal>71.352561</gco:Decimal>
|
||||
</gmd:northBoundLatitude>
|
||||
</gmd:EX_GeographicBoundingBox>
|
||||
</gmd:geographicElement>
|
||||
<gmd:temporalElement>
|
||||
<gmd:EX_TemporalExtent id="boundingTemporalExtent">
|
||||
<gmd:extent>
|
||||
<gml:TimeInstant gml:id="boundingTemporalExtentASingleDate">
|
||||
<gml:description>publication date</gml:description>
|
||||
<gml:timePosition>2023-04</gml:timePosition>
|
||||
</gml:TimeInstant>
|
||||
</gmd:extent>
|
||||
</gmd:EX_TemporalExtent>
|
||||
</gmd:temporalElement>
|
||||
</gmd:EX_Extent>
|
||||
</gmd:extent>
|
||||
</gmd:MD_DataIdentification>
|
||||
</gmd:identificationInfo>
|
||||
<gmd:contentInfo>
|
||||
<gmd:MD_FeatureCatalogueDescription>
|
||||
<gmd:includedWithDataset>
|
||||
<gco:Boolean>1</gco:Boolean>
|
||||
</gmd:includedWithDataset>
|
||||
<gmd:featureTypes>
|
||||
<gco:LocalName codeSpace="unknown">States and Equivalent Areas</gco:LocalName>
|
||||
</gmd:featureTypes>
|
||||
<gmd:featureCatalogueCitation>
|
||||
<gmd:CI_Citation>
|
||||
<gmd:title>
|
||||
<gco:CharacterString>Feature Catalog for the 2022 States and Equivalent Areas Cartographic Boundary File</gco:CharacterString>
|
||||
</gmd:title>
|
||||
<gmd:date>
|
||||
<gmd:CI_Date>
|
||||
<gmd:date>
|
||||
<gco:Date>2022</gco:Date>
|
||||
</gmd:date>
|
||||
<gmd:dateType>
|
||||
<gmd:CI_DateTypeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_DateTypeCode"
|
||||
codeListValue="publication">publication</gmd:CI_DateTypeCode>
|
||||
</gmd:dateType>
|
||||
</gmd:CI_Date>
|
||||
</gmd:date>
|
||||
<gmd:citedResponsibleParty>
|
||||
<gmd:CI_ResponsibleParty>
|
||||
<gmd:organisationName>
|
||||
<gco:CharacterString>U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch</gco:CharacterString>
|
||||
</gmd:organisationName>
|
||||
<gmd:contactInfo>
|
||||
<gmd:CI_Contact>
|
||||
<gmd:phone>
|
||||
<gmd:CI_Telephone>
|
||||
<gmd:voice>
|
||||
<gco:CharacterString>301-763-1128</gco:CharacterString>
|
||||
</gmd:voice>
|
||||
<gmd:facsimile>
|
||||
<gco:CharacterString>301-763-4710</gco:CharacterString>
|
||||
</gmd:facsimile>
|
||||
</gmd:CI_Telephone>
|
||||
</gmd:phone>
|
||||
<gmd:address>
|
||||
<gmd:CI_Address>
|
||||
<gmd:deliveryPoint>
|
||||
<gco:CharacterString>4600 Silver Hill Road, Stop 7400</gco:CharacterString>
|
||||
</gmd:deliveryPoint>
|
||||
<gmd:city>
|
||||
<gco:CharacterString>Washington</gco:CharacterString>
|
||||
</gmd:city>
|
||||
<gmd:administrativeArea>
|
||||
<gco:CharacterString>DC</gco:CharacterString>
|
||||
</gmd:administrativeArea>
|
||||
<gmd:postalCode>
|
||||
<gco:CharacterString>20233-7400</gco:CharacterString>
|
||||
</gmd:postalCode>
|
||||
<gmd:country>
|
||||
<gco:CharacterString>United States</gco:CharacterString>
|
||||
</gmd:country>
|
||||
<gmd:electronicMailAddress>
|
||||
<gco:CharacterString>geo.geography@census.gov</gco:CharacterString>
|
||||
</gmd:electronicMailAddress>
|
||||
</gmd:CI_Address>
|
||||
</gmd:address>
|
||||
</gmd:CI_Contact>
|
||||
</gmd:contactInfo>
|
||||
<gmd:role>
|
||||
<gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode"
|
||||
codeListValue="pointOfContact">pointOfContact</gmd:CI_RoleCode>
|
||||
</gmd:role>
|
||||
</gmd:CI_ResponsibleParty>
|
||||
</gmd:citedResponsibleParty>
|
||||
<gmd:otherCitationDetails>
|
||||
<gco:CharacterString>https://meta.geo.census.gov/data/existing/decennial/GEO/CPMB/boundary/2022/shp/19110/cb_2022_us_state_20m.shp.ea.iso.xml</gco:CharacterString>
|
||||
</gmd:otherCitationDetails>
|
||||
</gmd:CI_Citation>
|
||||
</gmd:featureCatalogueCitation>
|
||||
</gmd:MD_FeatureCatalogueDescription>
|
||||
</gmd:contentInfo>
|
||||
<gmd:distributionInfo>
|
||||
<gmd:MD_Distribution>
|
||||
<gmd:distributionFormat>
|
||||
<gmd:MD_Format>
|
||||
<gmd:name>
|
||||
<gco:CharacterString>ZIP</gco:CharacterString>
|
||||
</gmd:name>
|
||||
<gmd:version gco:nilReason="unknown"/>
|
||||
</gmd:MD_Format>
|
||||
</gmd:distributionFormat>
|
||||
<gmd:distributor>
|
||||
<gmd:MD_Distributor>
|
||||
<gmd:distributorContact>
|
||||
<gmd:CI_ResponsibleParty>
|
||||
<gmd:organisationName>
|
||||
<gco:CharacterString>U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Customer Engagement Branch</gco:CharacterString>
|
||||
</gmd:organisationName>
|
||||
<gmd:contactInfo>
|
||||
<gmd:CI_Contact>
|
||||
<gmd:phone>
|
||||
<gmd:CI_Telephone>
|
||||
<gmd:voice>
|
||||
<gco:CharacterString>301-763-1128</gco:CharacterString>
|
||||
</gmd:voice>
|
||||
<gmd:facsimile>
|
||||
<gco:CharacterString>301-763-4710</gco:CharacterString>
|
||||
</gmd:facsimile>
|
||||
</gmd:CI_Telephone>
|
||||
</gmd:phone>
|
||||
<gmd:address>
|
||||
<gmd:CI_Address>
|
||||
<gmd:deliveryPoint>
|
||||
<gco:CharacterString>4600 Silver Hill Road, Stop 7400</gco:CharacterString>
|
||||
</gmd:deliveryPoint>
|
||||
<gmd:city>
|
||||
<gco:CharacterString>Washington</gco:CharacterString>
|
||||
</gmd:city>
|
||||
<gmd:administrativeArea>
|
||||
<gco:CharacterString>DC</gco:CharacterString>
|
||||
</gmd:administrativeArea>
|
||||
<gmd:postalCode>
|
||||
<gco:CharacterString>20233-7400</gco:CharacterString>
|
||||
</gmd:postalCode>
|
||||
<gmd:country>
|
||||
<gco:CharacterString>United States</gco:CharacterString>
|
||||
</gmd:country>
|
||||
<gmd:electronicMailAddress>
|
||||
<gco:CharacterString>geo.geography@census.gov</gco:CharacterString>
|
||||
</gmd:electronicMailAddress>
|
||||
</gmd:CI_Address>
|
||||
</gmd:address>
|
||||
</gmd:CI_Contact>
|
||||
</gmd:contactInfo>
|
||||
<gmd:role>
|
||||
<gmd:CI_RoleCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_RoleCode"
|
||||
codeListValue="distributor">distributor</gmd:CI_RoleCode>
|
||||
</gmd:role>
|
||||
</gmd:CI_ResponsibleParty>
|
||||
</gmd:distributorContact>
|
||||
<gmd:distributionOrderProcess>
|
||||
<gmd:MD_StandardOrderProcess>
|
||||
<gmd:fees>
|
||||
<gco:CharacterString>The online cartographic boundary files may be downloaded without charge.</gco:CharacterString>
|
||||
</gmd:fees>
|
||||
</gmd:MD_StandardOrderProcess>
|
||||
</gmd:distributionOrderProcess>
|
||||
</gmd:MD_Distributor>
|
||||
</gmd:distributor>
|
||||
<gmd:transferOptions>
|
||||
<gmd:MD_DigitalTransferOptions>
|
||||
<gmd:onLine>
|
||||
<gmd:CI_OnlineResource>
|
||||
<gmd:linkage>
|
||||
<gmd:URL>https://www2.census.gov/geo/tiger/GENZ2022/shp/cb_2022_us_state_20m.zip</gmd:URL>
|
||||
</gmd:linkage>
|
||||
<gmd:applicationProfile>
|
||||
<gco:CharacterString>Shapefile Zip File</gco:CharacterString>
|
||||
</gmd:applicationProfile>
|
||||
<gmd:name>
|
||||
<gco:CharacterString>cb_2022_us_state_20m.zip</gco:CharacterString>
|
||||
</gmd:name>
|
||||
<gmd:description>
|
||||
<gco:CharacterString>The cartographic boundary files are simplified representations of selected geographic areas specifically designed for small scale thematic mapping. These files contain simplified extracts of selected geographic areas from the U.S. Census Bureau's Master Address File/Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) database.</gco:CharacterString>
|
||||
</gmd:description>
|
||||
<gmd:function>
|
||||
<gmd:CI_OnLineFunctionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_OnlineFunctionCode"
|
||||
codeListValue="download">download</gmd:CI_OnLineFunctionCode>
|
||||
</gmd:function>
|
||||
</gmd:CI_OnlineResource>
|
||||
</gmd:onLine>
|
||||
</gmd:MD_DigitalTransferOptions>
|
||||
</gmd:transferOptions>
|
||||
<gmd:transferOptions>
|
||||
<gmd:MD_DigitalTransferOptions>
|
||||
<gmd:onLine>
|
||||
<gmd:CI_OnlineResource>
|
||||
<gmd:linkage>
|
||||
<gmd:URL>https://meta.geo.census.gov/data/existing/decennial/GEO/CPMB/boundary/2022/shp/19110/cb_2022_us_state_20m.shp.ea.iso.xml</gmd:URL>
|
||||
</gmd:linkage>
|
||||
<gmd:applicationProfile>
|
||||
<gco:CharacterString>XML</gco:CharacterString>
|
||||
</gmd:applicationProfile>
|
||||
<gmd:name>
|
||||
<gco:CharacterString>cb_2022_us_state_20m.shp.ea.iso.xml</gco:CharacterString>
|
||||
</gmd:name>
|
||||
<gmd:description>
|
||||
<gco:CharacterString>Entity and attribute file</gco:CharacterString>
|
||||
</gmd:description>
|
||||
<gmd:function>
|
||||
<gmd:CI_OnLineFunctionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_OnlineFunctionCode"
|
||||
codeListValue="download">download</gmd:CI_OnLineFunctionCode>
|
||||
</gmd:function>
|
||||
</gmd:CI_OnlineResource>
|
||||
</gmd:onLine>
|
||||
</gmd:MD_DigitalTransferOptions>
|
||||
</gmd:transferOptions>
|
||||
<gmd:transferOptions>
|
||||
<gmd:MD_DigitalTransferOptions>
|
||||
<gmd:onLine>
|
||||
<gmd:CI_OnlineResource>
|
||||
<gmd:linkage>
|
||||
<gmd:URL>https://www2.census.gov/geo/tiger/GENZ2022/2022_file_name_def.pdf</gmd:URL>
|
||||
</gmd:linkage>
|
||||
<gmd:applicationProfile>
|
||||
<gco:CharacterString>PDF</gco:CharacterString>
|
||||
</gmd:applicationProfile>
|
||||
<gmd:name>
|
||||
<gco:CharacterString>2022_file_name_def.pdf</gco:CharacterString>
|
||||
</gmd:name>
|
||||
<gmd:description>
|
||||
<gco:CharacterString>The file naming convention for the cartographic boundary files.</gco:CharacterString>
|
||||
</gmd:description>
|
||||
<gmd:function>
|
||||
<gmd:CI_OnLineFunctionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_OnlineFunctionCode"
|
||||
codeListValue="search">search</gmd:CI_OnLineFunctionCode>
|
||||
</gmd:function>
|
||||
</gmd:CI_OnlineResource>
|
||||
</gmd:onLine>
|
||||
</gmd:MD_DigitalTransferOptions>
|
||||
</gmd:transferOptions>
|
||||
<gmd:transferOptions>
|
||||
<gmd:MD_DigitalTransferOptions>
|
||||
<gmd:onLine>
|
||||
<gmd:CI_OnlineResource>
|
||||
<gmd:linkage>
|
||||
<gmd:URL>https://www2.census.gov/geo/tiger/GENZ2022/description.pdf</gmd:URL>
|
||||
</gmd:linkage>
|
||||
<gmd:applicationProfile>
|
||||
<gco:CharacterString>PDF</gco:CharacterString>
|
||||
</gmd:applicationProfile>
|
||||
<gmd:name>
|
||||
<gco:CharacterString>description.pdf</gco:CharacterString>
|
||||
</gmd:name>
|
||||
<gmd:description>
|
||||
<gco:CharacterString>General description of the cartographic boundary files and their appropriate use.</gco:CharacterString>
|
||||
</gmd:description>
|
||||
<gmd:function>
|
||||
<gmd:CI_OnLineFunctionCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#CI_OnlineFunctionCode"
|
||||
codeListValue="search">search</gmd:CI_OnLineFunctionCode>
|
||||
</gmd:function>
|
||||
</gmd:CI_OnlineResource>
|
||||
</gmd:onLine>
|
||||
</gmd:MD_DigitalTransferOptions>
|
||||
</gmd:transferOptions>
|
||||
</gmd:MD_Distribution>
|
||||
</gmd:distributionInfo>
|
||||
<gmd:dataQualityInfo>
|
||||
<gmd:DQ_DataQuality>
|
||||
<gmd:scope>
|
||||
<gmd:DQ_Scope>
|
||||
<gmd:level>
|
||||
<gmd:MD_ScopeCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_ScopeCode"
|
||||
codeListValue="dataset">dataset</gmd:MD_ScopeCode>
|
||||
</gmd:level>
|
||||
</gmd:DQ_Scope>
|
||||
</gmd:scope>
|
||||
<gmd:report>
|
||||
<gmd:DQ_ConceptualConsistency>
|
||||
<gmd:measureDescription>
|
||||
<gco:CharacterString>The Census Bureau performed automated tests to ensure logical consistency and limits of shapefiles. Segments making up the outer and inner boundaries of a polygon tie end-to-end to completely enclose the area. All polygons are tested for closure.
|
||||
The Census Bureau uses its internally developed geographic update system to enhance and modify spatial and attribute data in the Census MAF/TIGER database. Standard geographic codes, such as FIPS codes for states, counties, municipalities, county subdivisions, places, American Indian/Alaska Native/Native Hawaiian areas, and congressional districts are used when encoding spatial entities. The Census Bureau performed spatial data tests for logical consistency of the codes during the compilation of the original Census MAF/TIGER database files. Most of the codes for geographic entities except states, counties, urban areas, Core Based Statistical Areas (CBSAs), American Indian Areas (AIAs), and congressional districts were provided to the Census Bureau by the USGS, the agency responsible for maintaining the Geographic Names Information System (GNIS). Feature attribute information has been examined but has not been fully tested for consistency.
|
||||
For the Cartographic Boundary Files, the Point and Vector Object Count for the G-polygon SDTS Point and Vector Object Type reflects the number of records in the shapefile attribute table. For multi-polygon features, only one attribute record exists for each multi-polygon rather than one attribute record per individual G-polygon component of the multi-polygon feature. Cartographic Boundary File multi-polygons are an exception to the G-polygon object type classification. Therefore, when multi-polygons exist in a shapefile, the object count will be less than the actual number of G-polygons.</gco:CharacterString>
|
||||
</gmd:measureDescription>
|
||||
<gmd:result gco:nilReason="unknown"/>
|
||||
</gmd:DQ_ConceptualConsistency>
|
||||
</gmd:report>
|
||||
<gmd:report>
|
||||
<gmd:DQ_CompletenessOmission>
|
||||
<gmd:evaluationMethodDescription>
|
||||
<gco:CharacterString>The cartographic boundary files are generalized representations of extracts taken from the MAF/TIGER database. Generalized boundary files are clipped to a simplified version of the U.S. outline. As a result, some off-shore areas may be excluded from the generalized files. Some small geographic areas, holes, or discontiguous parts of areas may not be included in generalized files if they are not visible at the target scale.</gco:CharacterString>
|
||||
</gmd:evaluationMethodDescription>
|
||||
<gmd:result gco:nilReason="unknown"/>
|
||||
</gmd:DQ_CompletenessOmission>
|
||||
</gmd:report>
|
||||
<gmd:report>
|
||||
<gmd:DQ_CompletenessCommission>
|
||||
<gmd:evaluationMethodDescription>
|
||||
<gco:CharacterString>The cartographic boundary files are generalized representations of extracts taken from the MAF/TIGER database. Generalized boundary files are clipped to a simplified version of the U.S. outline. As a result, some off-shore areas may be excluded from the generalized files. Some small geographic areas, holes, or discontiguous parts of areas may not be included in generalized files if they are not visible at the target scale.</gco:CharacterString>
|
||||
</gmd:evaluationMethodDescription>
|
||||
<gmd:result gco:nilReason="unknown"/>
|
||||
</gmd:DQ_CompletenessCommission>
|
||||
</gmd:report>
|
||||
</gmd:DQ_DataQuality>
|
||||
</gmd:dataQualityInfo>
|
||||
<gmd:metadataMaintenance>
|
||||
<gmd:MD_MaintenanceInformation>
|
||||
<gmd:maintenanceAndUpdateFrequency>
|
||||
<gmd:MD_MaintenanceFrequencyCode codeList="http://www.isotc211.org/2005/resources/Codelist/gmxCodelists.xml#MD_MaintenanceFrequencyCode"
|
||||
codeListValue="notPlanned">notPlanned</gmd:MD_MaintenanceFrequencyCode>
|
||||
</gmd:maintenanceAndUpdateFrequency>
|
||||
<gmd:maintenanceNote>
|
||||
<gco:CharacterString>This was transformed from the Census Bureau Geospatial Product Metadata Content Standard.</gco:CharacterString>
|
||||
</gmd:maintenanceNote>
|
||||
</gmd:MD_MaintenanceInformation>
|
||||
</gmd:metadataMaintenance>
|
||||
</gmi:MI_Metadata>
|
||||
Binary file not shown.
@@ -0,0 +1,99 @@
|
||||
rank,brewer,city,state,country,us_address,url,Latitude,Longitude,"Accuracy Score","Accuracy Type",Number,Street,City,State,County,Zip,Country,Source
|
||||
1,"Hill Farmstead Brewery",Greensboro,Vermont,USA,"403 Hill Road, Greensboro, VT 05842",http://hillfarmstead.com,44.606678,-72.263338,0.9,rooftop,403,"Hill Rd",Greensboro,VT,"Orleans County",05841,US,"VT Enhanced 911 Board, VCGI"
|
||||
2,"Russian River Brewing","Santa Rosa",California,USA,"725 4th St, Santa Rosa, California, USA 95404",https://russianriverbrewing.com,38.441677,-122.712065,1,rooftop,725,"4th St","Santa Rosa",CA,"Sonoma County",95404,US,"Sonoma County"
|
||||
3,"Trillium Brewing Company",Boston,Massachusetts,USA,"50 Thompson Place, Boston, Massachusetts, USA 02210",http://www.trilliumbrewing.com/,42.359739,-71.068201,0.9,range_interpolation,50,"Thompson Ct",Boston,MA,"Suffolk County",02114,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
4,"Cigar City Brewing",Tampa,Florida,USA,"3924 W Spruce Street, Tampa, Florida, USA 33607",http://www.cigarcitybrewing.com/,27.95903,-82.50919,1,rooftop,3924,"W Spruce St",Tampa,FL,"Hillsborough County",33607,US,"Hillsborough County"
|
||||
5,"Tree House Brewing Company",Charlton,Massachusetts,USA,"129 Sturbridge Road, Charlton, Massachusetts, USA 01507",http://www.treehousebrew.com/,42.139231,-72.017444,1,range_interpolation,129,"Sturbridge Rd",Charlton,MA,"Worcester County",01507,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
6,"AleSmith Brewing Company","San Diego",California,USA,"9990 AleSmith Ct, San Diego, California, USA 92126",http://www.alesmith.com/,32.888174,-117.149655,1,rooftop,9990,"Alesmith Ct","San Diego",CA,"San Diego County",92126,US,"San Diego Geographic Information Source - JPA"
|
||||
7,"Three Floyds Brewing Company",Munster,Indiana,USA,"9750 Indiana Parkway, Munster, Indiana, USA 46321",http://www.3floyds.com/,41.535554,-87.51681,1,rooftop,9750,"Indiana Pkwy",Munster,IN,"Lake County",46321,US,Lake
|
||||
8,"New Glarus Brewing Company","New Glarus",Wisconsin,USA,"2400 State Highway 69, New Glarus, Wisconsin, USA 53574",http://www.newglarusbrewing.com/,42.794194,-89.630126,1,rooftop,2400,"State Hwy 69","New Glarus",WI,"Green County",53574,US,Green
|
||||
9,"Side Project Brewing",Maplewood,Missouri,USA,"7458 Manchester Road, Maplewood, Missouri, USA 63143",http://www.sideprojectbrewing.com/,38.612105,-90.321857,1,rooftop,7458,"Manchester Rd","Saint Louis",MO,"St. Louis County",63143,US,"St Louis"
|
||||
10,"Sante Adairius Rustic Ales",Capitola,California,USA,"103 Kennedy Dr, Capitola, California, USA 95010",http://www.santeadairius.com/,36.983231,-121.949517,1,rooftop,103,"Kennedy Dr",Capitola,CA,"Santa Cruz County",95010,US,"Santa Cruz County"
|
||||
11,"Port Brewing Company / The Lost Abbey","San Marcos",California,USA,"155 Mata Way, Ste 104, San Marcos, California, USA 92069",http://www.lostabbey.com/,33.140565,-117.149872,1,range_interpolation,155,"Mata Way","San Marcos",CA,"San Diego County",92069,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
12,"Founders Brewing Company","Grand Rapids",Michigan,USA,"235 Grandville Ave SW, Grand Rapids, Michigan, USA 49503",http://www.foundersbrewing.com/,42.958216,-85.674062,1,rooftop,235,"Grandville Ave SW","Grand Rapids",MI,"Kent County",49503,US,Kent
|
||||
13,"Tired Hands Brewing Company",Ardmore,Pennsylvania,USA,"16 Ardmore Avenue, Ardmore, Pennsylvania, USA 19003 ",http://www.tiredhands.com/,40.008663,-75.293571,1,range_interpolation,16,"Ardmore Ave",Ardmore,PA,"Montgomery County",19003,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
14,"Cloudwater Brew Co",Manchester,"Greater Manchester",England,,,34.54426,-91.96903,1,place,,,England,AR,"Lonoke County",72046,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
15,"Toppling Goliath Brewing Company",Decorah,Iowa,USA,"1600 Prosperity Rd, Decorah, Iowa, USA 52101",http://www.tgbrews.com/,43.273486,-91.726288,0.6,nearest_rooftop_match,1665,"Prosperity Rd",Decorah,IA,"Winneshiek County",52101,US,Winneshiek
|
||||
16,"Firestone Walker Brewing (Duvel-Moortgat)","Paso Robles",California,USA,"1400 Ramada Dr, Paso Robles, California, USA 93446",http://www.firestonebeer.com/,35.595911,-120.694102,1,rooftop,1400,"Ramada Dr","Paso Robles",CA,"San Luis Obispo County",93446,US,"San Luis Obispo County"
|
||||
17,Mikkeller,Copenhagen,-,Denmark,"2021 India Str, San Diego, CA 92101",http://mikkeller.dk/location/mikkeller-tasting-room-little-italy/,32.725754,-117.168862,1,rooftop,2021,"India St","San Diego",CA,"San Diego County",92101,US,"San Diego Geographic Information Source - JPA"
|
||||
18,"The Kernel Brewery",Bermondsey,"Greater London",England,,,34.54426,-91.96903,1,place,,,England,AR,"Lonoke County",72046,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
19,"Surly Brewing Company",Minneapolis,Minnesota,USA,"520 Malcolm Avenue SE, Minneapolis, Minnesota, USA 55414",http://www.surlybrewing.com/,44.973297,-93.208629,1,rooftop,520,"Malcolm Ave SE",Minneapolis,MN,"Hennepin County",55414,US,Hennepin
|
||||
20,"De Garde Brewing",Tillamook,Oregon,USA,"6000 Blimp Blvd, Tillamook, Oregon, USA 97141",http://degardebrewing.com/,45.420699,-123.799945,1,rooftop,6000,"Blimp Blvd",Tillamook,OR,"Tillamook County",97141,US,Tillamook
|
||||
21,"Brasserie Dieu du Ciel!",Montréal,Quebec,Canada,,http://www.dieuduciel.com/,45.50884,-73.58781,1,place,,,Montréal,QC,,,CA,"CanVec+ by Natural Resources Canada"
|
||||
22,"Stone Brewing",Escondido,California,USA,"1999 Citracado Pkwy, Escondido, California, USA 92029",https://www.stonebrewing.com,33.115652,-117.120286,1,rooftop,1999,"Citracado Pkwy",Escondido,CA,"San Diego County",92029,US,"San Diego Geographic Information Source - JPA"
|
||||
23,"Modern Times Beer","San Diego",California,USA,"3725 Greenwood St, San Diego, California, USA 92110",http://moderntimesbeer.com/,32.754238,-117.206165,1,rooftop,3725,"Greenwood St","San Diego",CA,"San Diego County",92110,US,"San Diego Geographic Information Source - JPA"
|
||||
24,"Cycle Brewing","Saint Petersburg",Florida,USA,"534 Central Ave, Saint Petersburg, Florida, USA 33701",https://cyclebrewing.com/,27.770919,-82.640765,1,rooftop,534,"Central Ave","Saint Petersburg",FL,"Pinellas County",33701,US,Pinellas
|
||||
25,"Sierra Nevada Brewing Company",Chico,California,USA,"1075 E 20th St, Chico, California, USA 95928",http://www.sierranevada.com/,39.724437,-121.815269,1,rooftop,1075,"E 20th St",Chico,CA,"Butte County",95928,US,"Butte County"
|
||||
26,"Maine Beer Company",Freeport,Maine,USA,"525 US Route One, Freeport, Maine, USA 04032",http://www.mainebeercompany.com/,43.864477,-70.097543,0.33,place,,,Freeport,ME,"Cumberland County",04032,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
27,"Other Half Brewing",Brooklyn,"New York",USA,"195 Centre Street, Brooklyn, New York, USA 11231",http://otherhalfbrewing.com/,40.673763,-73.999129,1,rooftop,195,"Centre St",Brooklyn,NY,"Kings County",11231,US,"City of New York"
|
||||
28,"De Struise Brouwers",Oostvleteren,-,Belgium,,,43.499631,-87.918042,1,place,,,Belgium,WI,"Ozaukee County",53004,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
29,"The Bruery",Placentia,California,USA,"715 Dunn Way, Placentia, California, USA 92870",http://www.thebruery.com/,33.861325,-117.880165,1,range_interpolation,715,"Dunn Way",Placentia,CA,"Orange County",92870,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
30,"Brouwerij De Molen",Bodegraven,-,Netherlands,,,36.299233,-89.751194,0.8,place,,,Netherlands,MO,"Pemiscot County",63851,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
31,"Bell's Brewery",Comstock,Michigan,USA,"8690 Krum Ave., Comstock, Michigan, USA 49053",http://www.bellsbeer.com/,42.287238,-85.457792,0.6,street_center,,"Krum Ave",Galesburg,MI,"Kalamazoo County",49053,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
32,"Allagash Brewing Company",Portland,Maine,USA,"50 Industrial Way, Portland, Maine, USA 04103",http://www.allagash.com/,43.703096,-70.317846,1,rooftop,50,"Industrial Way",Portland,ME,"Cumberland County",04103,US,"Maine Office of GIS"
|
||||
33,"Schramm's Mead",Ferndale,Michigan,USA,"327 West 9 Mile Road, Ferndale, Michigan, USA 48220",http://www.schrammsmead.com/,42.460272,-83.138593,1,rooftop,327,"W 9 Mile Rd",Ferndale,MI,"Oakland County",48220,US,Oakland
|
||||
34,"Brasserie Dunham",Dunham,Quebec,Canada,,,45.13338,-72.79913,1,place,,,Dunham,QC,,,CA,"CanVec+ by Natural Resources Canada"
|
||||
35,"Superstition Meadery",Prescott,Arizona,USA,"120 W Gurley St, Prescott, Arizona, USA 86301",http://superstitionmeadery.com/,34.542056,-112.469468,1,rooftop,120,"W Gurley St",Prescott,AZ,"Yavapai County",86301,US,Yavapai
|
||||
36,"Funky Buddha Brewery (Constellation Brands)","Oakland Park",Florida,USA,"1201 NE 38th Street, Oakland Park, Florida, USA 33334",http://funkybuddhabrewery.com/,26.175277,-80.13088,0.9,rooftop,1201,"NE 38th St","Fort Lauderdale",FL,"Broward County",33334,US,Broward
|
||||
37,Buxton,Buxton,Derbyshire,England,,,34.54426,-91.96903,1,place,,,England,AR,"Lonoke County",72046,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
38,Fuller's,Chiswick,"Greater London",England,,,34.54426,-91.96903,1,place,,,England,AR,"Lonoke County",72046,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
39,Siren,Finchampstead,Berkshire,England,,,34.54426,-91.96903,1,place,,,England,AR,"Lonoke County",72046,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
40,"Brouwerij 3 Fonteinen","Lot, Beersel",-,Belgium,,,43.499631,-87.918042,1,place,,,Belgium,WI,"Ozaukee County",53004,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
41,"To Øl","Copenhagen N",-,Denmark,,,33.237543,-81.104895,1,place,,,Denmark,SC,"Bamberg County",29042,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
42,"Deschutes Brewery",Bend,Oregon,USA,"901 SW Simpson Ave, Bend, Oregon, USA 97702",http://www.deschutesbrewery.com/,44.046778,-121.322167,1,rooftop,901,"SW Simpson Ave",Bend,OR,"Deschutes County",97702,US,Deschutes
|
||||
43,"Jack's Abby Brewing",Framingham,Massachusetts,USA,"100 Clinton Street, Framingham, Massachusetts, USA 01702",http://jacksabby.com/,42.280776,-71.410715,1,rooftop,100,"Clinton St",Framingham,MA,"Middlesex County",01702,US,"Office of Geographic Information (MassGIS), Commonwealth of Massachusetts, MassIT"
|
||||
44,"Magic Rock Brewing",Huddersfield,"West Yorkshire",England,,,34.54426,-91.96903,1,place,,,England,AR,"Lonoke County",72046,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
45,"Alpine Beer Company (CA)",Alpine,California,USA,"2363 Alpine Blvd, Alpine, California, USA 91901",http://www.alpinebeerco.com/,32.834684,-116.762695,1,rooftop,2363,"Alpine Blvd",Alpine,CA,"San Diego County",91901,US,"San Diego Geographic Information Source - JPA"
|
||||
46,"Brewery Ommegang (Duvel-Moortgat)",Cooperstown,"New York",USA,"656 County Highway 33, Cooperstown, New York, USA 13326",http://www.ommegang.com/,42.626849,-74.945318,1,rooftop,656,"County Highway 33",Cooperstown,NY,"Otsego County",13326,US,"NYS GIS Program Office, State Geographic Information Officer (GIO)"
|
||||
47,"Bellwoods Brewery",Toronto,Ontario,Canada,,,43.70011,-79.4163,1,place,,,Toronto,ON,,,CA,"CanVec+ by Natural Resources Canada"
|
||||
49,"Cellarmaker Brewing Company","San Francisco",California,USA,"1150 Howard St, San Francisco, California, USA 94103",http://www.cellarmakerbrewing.com/,37.777218,-122.410768,1,rooftop,1150,"Howard St","San Francisco",CA,"San Francisco County",94103,US,"San Francisco"
|
||||
50,"Westvleteren Abdij St. Sixtus",Westvleteren,-,Belgium,,,43.499631,-87.918042,1,place,,,Belgium,WI,"Ozaukee County",53004,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
51,"Hair of the Dog Brewing Company",Portland,Oregon,USA,"61 SE Yamhill Street, Portland, Oregon, USA 97214",http://www.hairofthedog.com/,45.516036,-122.665512,1,rooftop,61,"SE Yamhill St",Portland,OR,"Multnomah County",97214,US,Portland
|
||||
52,Cantillon,Brussels,-,Belgium,,,43.499631,-87.918042,1,place,,,Belgium,WI,"Ozaukee County",53004,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
53,"Kuhnhenn Brewing",Warren,Michigan,USA,"5919 Chicago Road, Warren, Michigan, USA 48092",http://www.kbrewery.com/,42.527803,-83.046787,1,rooftop,5919,"Chicago Rd",Warren,MI,"Macomb County",48092,US,Macomb
|
||||
54,"Victory Brewing Company (ABV)",Downingtown,Pennsylvania,USA,"420 Acorn Lane, Downingtown, Pennsylvania, USA 19335",http://www.victorybeer.com/,40.004875,-75.693318,1,rooftop,420,"Acorn Ln",Downingtown,PA,"Chester County",19335,US,Chester
|
||||
55,"Hoppin' Frog Brewery",Akron,Ohio,USA,"1680 E. Waterloo Rd. (Rte 224) Suite F, Akron, Ohio, USA 44306",http://www.hoppinfrog.com/,41.024836,-81.467737,1,rooftop,1680,"E Waterloo Rd",Akron,OH,"Summit County",44306,US,Summit
|
||||
56,"Goose Island Beer Company (AB-InBev)",Chicago,Illinois,USA,"1800 West Fulton Street, Chicago, Illinois, USA 60612",http://www.gooseisland.com/,41.887114,-87.672126,1,rooftop,1800,"W Fulton St",Chicago,IL,"Cook County",60612,US,"City of Chicago"
|
||||
57,Põhjala,Tallinn,-,Estonia,,,0,0,0,,,,,,,,,
|
||||
58,"Westbrook Brewing","Mount Pleasant","South Carolina",USA,"510 Ridge Rd, Mount Pleasant, South Carolina, USA 29464",http://westbrookbrewing.com/,32.847273,-79.820563,0.33,place,,,"Mount Pleasant",SC,"Charleston County",29464,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
59,"Stillwater Artisanal",Baltimore,Maryland,USA,,,39.296536,-76.623489,1,place,,,Baltimore,MD,"Baltimore city",21201,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
60,"Casey Brewing and Blending","Glenwood Springs",Colorado,USA,"3421 Grand Avenue , Glenwood Springs, Colorado, USA 81601",http://caseybrewing.com/,39.515686,-107.319678,0.9,rooftop,3421,"S Grand Ave","Glenwood Springs",CO,"Garfield County",81601,US,Garfield
|
||||
61,"Ballast Point Brewing Company (Constellation Brands)","San Diego",California,USA,"5401 Linda Vista Rd Ste 406, San Diego, California, USA 92110",http://www.ballastpoint.com/,32.766791,-117.195204,1,rooftop,5401,"Linda Vista Rd","San Diego",CA,"San Diego County",92110,US,"San Diego Geographic Information Source - JPA"
|
||||
62,"Brasserie de la Senne",Brussels,-,Belgium,,,43.499631,-87.918042,1,place,,,Belgium,WI,"Ozaukee County",53004,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
63,"Evil Twin Brewing",Brooklyn,"New York",USA,,,40.63122,-73.941542,0.9,street_center,,"Brooklyn Rd",Brooklyn,NY,"Kings County",11210,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
64,"Pipeworks Brewing Company",Chicago,Illinois,USA,"1675 N Western Ave, Chicago, Illinois, USA 60647 ",http://www.pipeworksbrewing.com/,41.912453,-87.686899,1,rooftop,1675,"N Western Ave",Chicago,IL,"Cook County",60647,US,"City of Chicago"
|
||||
65,"Mikkeller San Diego","San Diego",California,USA,"9366 Cabot Dr, San Diego, California, USA 92126",http://www.mikkellersd.com/home,32.892134,-117.144844,1,rooftop,9366,"Cabot Dr","San Diego",CA,"San Diego County",92126,US,"San Diego Geographic Information Source - JPA"
|
||||
66,Omnipollo,Stockholm,-,Sweden,,,34.193154,-91.724296,0.8,place,,,Sweden,AR,"Jefferson County",72004,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
67,"Perennial Artisan Ales","St. Louis",Missouri,USA,"8125 Michigan Ave., St. Louis, Missouri, USA 63111",http://www.perennialbeer.com/,38.545745,-90.265711,1,rooftop,8125,"Michigan Ave","Saint Louis",MO,"St. Louis city",63111,US,"City of St Louis"
|
||||
68,"Bottle Logic Brewing",Anaheim,California,USA,"1072 N Armando St, Anaheim, California, USA 92806",http://www.bottlelogic.com/,33.849508,-117.859702,1,rooftop,1072,"N Armando St",Anaheim,CA,"Orange County",92806,US,"City of Anaheim"
|
||||
69,"Boulevard Brewing Company (Duvel-Moortgat)","Kansas City",Missouri,USA,"2501 Southwest Boulevard, Kansas City, Missouri, USA 64108",http://www.boulevard.com/,39.082248,-94.596602,1,rooftop,2501,"Southwest Blvd","Kansas City",MO,"Jackson County",64108,US,Jackson
|
||||
70,"Avery Brewing Company",Boulder,Colorado,USA,"4910 Nautilus Ct, Boulder, Colorado, USA 80301",http://www.averybrewing.com/,40.06261,-105.204906,1,rooftop,4910,Nautilus,Boulder,CO,"Boulder County",80301,US,Statewide
|
||||
71,"De Dolle Brouwers",Diksmuide,-,Belgium,,,43.499631,-87.918042,1,place,,,Belgium,WI,"Ozaukee County",53004,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
72,"Angry Chair Brewing",Tampa,Florida,USA,"6401 N. Florida Avenue, Tampa, Florida, USA 33604",http://angrychairbrewing.com/,28.00514,-82.459211,1,rooftop,6401,"N Florida Ave",Tampa,FL,"Hillsborough County",33604,US," Loveland"
|
||||
74,"Amager Bryghus",Kastrup,-,Denmark,,http://www.amagerbryghus.dk/,33.237543,-81.104895,1,place,,,Denmark,SC,"Bamberg County",29042,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
75,"Crooked Stave Artisan Beer Project",Denver,Colorado,USA,"3350 Brighton Blvd, Denver, Colorado, USA 80216",http://www.crookedstave.com/,39.768811,-104.981001,1,range_interpolation,3350,"Brighton Blvd",Denver,CO,"Denver County",80216,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
76,"Jolly Pumpkin Artisan Ales",Dexter,Michigan,USA,"2319 Bishop Circle East, Dexter, Michigan, USA 48130",http://www.jollypumpkin.com/,42.323711,-83.878362,1,rooftop,2319,"Bishop Cir E",Dexter,MI,"Washtenaw County",48130,US,Semcog
|
||||
77,"Almanac Beer Company","San Francisco",California,USA,"2339 3rd St, Ste 20, San Francisco, California, USA 94107",http://www.almanacbeer.com/,37.760023,-122.388308,1,range_interpolation,2339,"3rd St","San Francisco",CA,"San Francisco County",94107,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
78,"Half Acre Beer Company",Chicago,Illinois,USA,"4257 N. Lincoln Avenue, Chicago, Illinois, USA 60618",http://www.halfacrebeer.com/,41.959374,-87.682142,1,rooftop,4257,"N Lincoln Ave",Chicago,IL,"Cook County",60618,US,Cook
|
||||
79,"Heater Allen Brewing Co.",McMinnville,Oregon,USA,"907 NE 10th Ave., McMinnville, Oregon, USA 97128",http://heaterallen.com/,45.214058,-123.187804,0.9,range_interpolation,907,"NE 10th Ave",McMinnville,OR,"Yamhill County",97128,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
80,"Lawson's Finest Liquids",Warren,Vermont,USA,"155 Carroll Road, Waitsfield, Vermont, USA 05673",http://www.lawsonsfinest.com/,44.187877,-72.835269,1,rooftop,155,"Carroll Rd",Waitsfield,VT,"Washington County",05673,US,"VT Enhanced 911 Board, VCGI"
|
||||
81,"3 Sons Brewing Company","Dania Beach",Florida,USA,"236 N Federal Highway (US1), Dania Beach, Florida, USA 33004",https://www.3sonsbrewingco.com/,26.057123,-80.143202,1,rooftop,236,"N Federal Hwy",Dania,FL,"Broward County",33004,US,Broward
|
||||
82,"Prairie Artisan Ales",Tulsa,Oklahoma,USA,"1803B S 49th W Ave, Tulsa, Oklahoma, USA 74107",http://www.prairieales.com/,36.13695,-96.047103,0.9,range_interpolation,1803,"S 49th W Ave",Tulsa,OK,"Tulsa County",74107,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
83,"Browar Widawa","Chrząstawa Mała",-,Poland,,http://browarwidawa.pl/,44.047435,-70.389923,1,place,,,Poland,ME,"Androscoggin County",04274,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
84,"Suarez Family Brewery",Livingston,"New York",USA,"2278 Route 9, Livingston , New York, USA 12534",http://www.suarezfamilybrewery.com/,42.110935,-73.812398,0.8,nearest_rooftop_match,2274,"Route 9",Germantown,NY,"Columbia County",12526,US,"NYS GIS Program Office, State Geographic Information Officer (GIO)"
|
||||
85,"Smuttynose Brewing Company",Hampton,"New Hampshire",USA,"105 Towle Farm Road, Hampton, New Hampshire, USA 03842",http://smuttynose.com/,42.94557,-70.854646,1,rooftop,105,"Towle Farm Rd",Hampton,NH,"Rockingham County",03842,US,Statewide
|
||||
86,"Dogfish Head Brewery",Milton,Delaware,USA,"6 Cannery Village Center, Milton, Delaware, USA 19968",http://www.dogfish.com/,38.77761,-75.30991,0.33,place,,,Milton,DE,"Sussex County",19968,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
87,"Rogue Ales",Newport,Oregon,USA,"2320 OSU Drive, Newport, Oregon, USA 97365",http://www.rogue.com/,44.619668,-124.048292,0.5,street_center,,"SE Marine Science Dr",Newport,OR,"Lincoln County",97365,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
88,BrewDog,"Ellon, Aberdeenshire",-,Scotland,"96 Gender Rd, Canal Winchester, OH 43110, USA",http://www.brewdog.com,39.847898,-82.828303,1,rooftop,96,"Gender Rd","Canal Winchester",OH,"Franklin County",43110,US,Franklin
|
||||
89,"J. Wakefield Brewing",Miami,Florida,USA,"120 NW 24th Street, Miami, Florida, USA 33127 ",http://www.jwakefieldbrewing.com/,25.799643,-80.197554,1,rooftop,120,"NW 24th St",Miami,FL,"Miami-Dade County",33127,US,Miami
|
||||
90,Tempest,"Tweedbank, Scottish Borders",-,Scotland,,,39.970229,-77.590358,1,place,,,Scotland,PA,"Franklin County",17254,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
91,"Brauerei Aying",Aying,Bavaria,Germany,,,34.895926,-83.46655,0.8,place,,,Germany,GA,"Rabun County",30525,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
92,"Drakes Brewing Company","San Leandro",California,USA,"1933 Davis St, #177, San Leandro, California, USA 94577",http://www.drinkdrakes.com/,37.717165,-122.179501,1,rooftop,1933,"Davis St","San Leandro",CA,"Alameda County",94577,US,"Alameda County"
|
||||
93,"Nøgne Ø (Hansa Borg)",Grimstad,-,Norway,,,45.857201,-87.917602,1,place,,,Norway,MI,"Dickinson County",49870,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
94,"Bullfrog Brewery",Williamsport,Pennsylvania,USA,"229 West Fourth Street, Williamsport, Pennsylvania, USA 17701",http://www.bullfrogbrewery.com/,41.240345,-77.00567,1,rooftop,229,"W 4th St",Williamsport,PA,"Lycoming County",17701,US,Lycoming
|
||||
95,"Jester King Brewery",Austin,Texas,USA,"13187 Fitzhugh Rd, Bldg B, Austin, Texas, USA 78736",http://jesterkingbrewery.com/,30.232257,-98.000232,1,rooftop,13187,"Fitzhugh Rd",Austin,TX,"Hays County",78736,US,Capcog
|
||||
96,"Lervig Aktiebryggeri",Stavanger,-,Norway,,,45.857201,-87.917602,1,place,,,Norway,MI,"Dickinson County",49870,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
97,"Monkish Brewing Company",Torrance,California,USA,"20311 S Western Ave, Torrance, California, USA 90501",http://www.monkishbrewing.com/,33.84632,-118.31033,1,rooftop,20311,"S Highway 213",Torrance,CA,"Los Angeles County",90501,US,"Los Angeles County"
|
||||
98,"Wicked Weed Brewing (AB InBev)",Asheville,"North Carolina",USA,"91 Biltmore Street, Asheville, North Carolina, USA 28801",http://www.wickedweedbrewing.com/,35.56318,-82.55307,1,range_interpolation,91,"Biltmore Estate Dr",Asheville,NC,"Buncombe County",28803,US,"TIGER/Line® dataset from the US Census Bureau"
|
||||
99,"Jackie O's Pub & Brewery",Athens,Ohio,USA,"24 West Union Street, Athens, Ohio, USA 45701",http://www.jackieos.com/,39.32772,-82.102367,1,rooftop,24,"W Union St",Athens,OH,"Athens County",45701,US,Athens
|
||||
100,"Lagunitas Brewing Company (Heineken)",Petaluma,California,USA,"1280 N McDowell Blvd, Petaluma, California, USA 94954",http://www.lagunitas.com/,38.272428,-122.661783,1,rooftop,1280,"N McDowell Blvd",Petaluma,CA,"Sonoma County",94954,US,"Sonoma County"
|
||||
|
File diff suppressed because it is too large.
Load diff
File diff suppressed because it is too large.
Load diff
File diff suppressed because it is too large.
Load diff
File diff suppressed because it is too large.
Load diff
Loaded 100 of 110 files, more files were not shown because too many files have changed in this diff.
Show more
Reference in new issue
Block a user