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Add VT2-examples: all 6 chapters of 'Visualize This' (110 files) — data scraping, ETL, trends, categorical, multivariate, spatial, distribution analysis

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VT2-examples/vt2-ch4-codedata-dir/data/month_hour_pct_matrix.csv
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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
1 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
2 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
3 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
4 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
5 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
6 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
7 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
8 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
9 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
10 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
11 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
12 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
13 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