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 +1,77 @@
|
||||
#
|
||||
# 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")
|
||||
Reference in new issue
Block a user