├── 3 Advanced Excel Tasks in Python.ipynb.ipynb ├── 3 More Advanced Excel Tasks in Python.ipynb ├── AAPL.csv ├── Bayern Munich.xlsx ├── Boston_Neighborhoods.geojson ├── December.xlsx ├── Excel Files.zip ├── ExcelMagic.zip ├── Files.zip ├── List to String Python.py ├── Naive Bayes in Python.xlsx ├── November.xlsx ├── October.xlsx ├── PandasColumns.csv ├── PandasTips.xlsx ├── Pandas_read_files_tips.xlsx ├── README.md ├── Rename Files Tutorial.zip ├── Sales.xlsx ├── Sales2.xlsx ├── Sample.parquet ├── Scores.csv ├── Scores.xlsx ├── articles_community.csv ├── exceltopandas.xlsx ├── february.xlsx ├── fillna.xlsx ├── insurance.csv ├── iss-now.json ├── january.xlsx ├── listings.csv ├── march.xlsx ├── pandas merge.xlsx ├── populations.csv ├── pythonexcel.xlsx ├── sales.csv ├── sample.csv ├── sample.json ├── sample_pivot.xlsx ├── sort_values.xlsx ├── stocks-wide.csv ├── stocks.csv ├── toronto-weather.xlsx ├── unpivot.xlsx └── user-item-interactions.csv /3 Advanced Excel Tasks in Python.ipynb.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "# Learn How to (easily!!) do 3 Advanced Excel Tasks in Python\n", 8 | "Full Medium post can be found here: https://towardsdatascience.com/learn-how-to-easily-do-3-advanced-excel-tasks-in-python-925a6b7dd081" 9 | ] 10 | }, 11 | { 12 | "cell_type": "markdown", 13 | "metadata": {}, 14 | "source": [ 15 | "## Import Data" 16 | ] 17 | }, 18 | { 19 | "cell_type": "code", 20 | "execution_count": 1, 21 | "metadata": {}, 22 | "outputs": [], 23 | "source": [ 24 | "import pandas as pd\n", 25 | "sales = pd.read_excel('https://github.com/datagy/mediumdata/raw/master/pythonexcel.xlsx', sheet_name = 'sales')\n", 26 | "states = pd.read_excel('https://github.com/datagy/mediumdata/raw/master/pythonexcel.xlsx', sheet_name = 'states')" 27 | ] 28 | }, 29 | { 30 | "cell_type": "markdown", 31 | "metadata": {}, 32 | "source": [ 33 | "## Printing the first five rows" 34 | ] 35 | }, 36 | { 37 | "cell_type": "code", 38 | "execution_count": 2, 39 | "metadata": {}, 40 | "outputs": [ 41 | { 42 | "name": "stdout", 43 | "output_type": "stream", 44 | "text": [ 45 | " Product Sales Date City\n", 46 | "0 Bananas 121 2019-06-13 Atlanta\n", 47 | "1 Bananas 236 2019-10-20 Atlanta\n", 48 | "2 Apples 981 2019-03-12 Atlanta\n", 49 | "3 Bread 996 2019-07-28 New York City\n", 50 | "4 Brocolli 790 2019-10-22 New York City\n" 51 | ] 52 | } 53 | ], 54 | "source": [ 55 | "print(sales.head())" 56 | ] 57 | }, 58 | { 59 | "cell_type": "markdown", 60 | "metadata": {}, 61 | "source": [ 62 | "## If function in Pandas" 63 | ] 64 | }, 65 | { 66 | "cell_type": "code", 67 | "execution_count": 6, 68 | "metadata": {}, 69 | "outputs": [], 70 | "source": [ 71 | "sales['MoreThan500'] = ['Yes' if x > 500 else 'No' for x in sales['Sales']]" 72 | ] 73 | }, 74 | { 75 | "cell_type": "code", 76 | "execution_count": 7, 77 | "metadata": {}, 78 | "outputs": [ 79 | { 80 | "data": { 81 | "text/html": [ 82 | "
\n", 83 | "\n", 96 | "\n", 97 | " \n", 98 | " \n", 99 | " \n", 100 | " \n", 101 | " \n", 102 | " \n", 103 | " \n", 104 | " \n", 105 | " \n", 106 | " \n", 107 | " \n", 108 | " \n", 109 | " \n", 110 | " \n", 111 | " \n", 112 | " \n", 113 | " \n", 114 | " \n", 115 | " \n", 116 | " \n", 117 | " \n", 118 | " \n", 119 | " \n", 120 | " \n", 121 | " \n", 122 | " \n", 123 | " \n", 124 | " \n", 125 | " \n", 126 | " \n", 127 | " \n", 128 | " \n", 129 | " \n", 130 | " \n", 131 | " \n", 132 | " \n", 133 | " \n", 134 | " \n", 135 | " \n", 136 | " \n", 137 | " \n", 138 | " \n", 139 | " \n", 140 | " \n", 141 | " \n", 142 | " \n", 143 | " \n", 144 | " \n", 145 | " \n", 146 | " \n", 147 | " \n", 148 | " \n", 149 | "
ProductSalesDateCityMoreThan500
0Bananas1212019-06-13AtlantaNo
1Bananas2362019-10-20AtlantaNo
2Apples9812019-03-12AtlantaYes
3Bread9962019-07-28New York CityYes
4Brocolli7902019-10-22New York CityYes
\n", 150 | "
" 151 | ], 152 | "text/plain": [ 153 | " Product Sales Date City MoreThan500\n", 154 | "0 Bananas 121 2019-06-13 Atlanta No\n", 155 | "1 Bananas 236 2019-10-20 Atlanta No\n", 156 | "2 Apples 981 2019-03-12 Atlanta Yes\n", 157 | "3 Bread 996 2019-07-28 New York City Yes\n", 158 | "4 Brocolli 790 2019-10-22 New York City Yes" 159 | ] 160 | }, 161 | "execution_count": 7, 162 | "metadata": {}, 163 | "output_type": "execute_result" 164 | } 165 | ], 166 | "source": [ 167 | "sales.head()" 168 | ] 169 | }, 170 | { 171 | "cell_type": "markdown", 172 | "metadata": {}, 173 | "source": [ 174 | "## VLOOKUP" 175 | ] 176 | }, 177 | { 178 | "cell_type": "code", 179 | "execution_count": 8, 180 | "metadata": {}, 181 | "outputs": [], 182 | "source": [ 183 | "sales = pd.merge(sales, states, how='left', on='City')" 184 | ] 185 | }, 186 | { 187 | "cell_type": "code", 188 | "execution_count": 9, 189 | "metadata": {}, 190 | "outputs": [ 191 | { 192 | "data": { 193 | "text/html": [ 194 | "
\n", 195 | "\n", 208 | "\n", 209 | " \n", 210 | " \n", 211 | " \n", 212 | " \n", 213 | " \n", 214 | " \n", 215 | " \n", 216 | " \n", 217 | " \n", 218 | " \n", 219 | " \n", 220 | " \n", 221 | " \n", 222 | " \n", 223 | " \n", 224 | " \n", 225 | " \n", 226 | " \n", 227 | " \n", 228 | " \n", 229 | " \n", 230 | " \n", 231 | " \n", 232 | " \n", 233 | " \n", 234 | " \n", 235 | " \n", 236 | " \n", 237 | " \n", 238 | " \n", 239 | " \n", 240 | " \n", 241 | " \n", 242 | " \n", 243 | " \n", 244 | " \n", 245 | " \n", 246 | " \n", 247 | " \n", 248 | " \n", 249 | " \n", 250 | " \n", 251 | " \n", 252 | " \n", 253 | " \n", 254 | " \n", 255 | " \n", 256 | " \n", 257 | " \n", 258 | " \n", 259 | " \n", 260 | " \n", 261 | " \n", 262 | " \n", 263 | " \n", 264 | " \n", 265 | " \n", 266 | " \n", 267 | "
ProductSalesDateCityMoreThan500State
0Bananas1212019-06-13AtlantaNoGeorgia
1Bananas2362019-10-20AtlantaNoGeorgia
2Apples9812019-03-12AtlantaYesGeorgia
3Bread9962019-07-28New York CityYesNew York
4Brocolli7902019-10-22New York CityYesNew York
\n", 268 | "
" 269 | ], 270 | "text/plain": [ 271 | " Product Sales Date City MoreThan500 State\n", 272 | "0 Bananas 121 2019-06-13 Atlanta No Georgia\n", 273 | "1 Bananas 236 2019-10-20 Atlanta No Georgia\n", 274 | "2 Apples 981 2019-03-12 Atlanta Yes Georgia\n", 275 | "3 Bread 996 2019-07-28 New York City Yes New York\n", 276 | "4 Brocolli 790 2019-10-22 New York City Yes New York" 277 | ] 278 | }, 279 | "execution_count": 9, 280 | "metadata": {}, 281 | "output_type": "execute_result" 282 | } 283 | ], 284 | "source": [ 285 | "sales.head()" 286 | ] 287 | }, 288 | { 289 | "cell_type": "markdown", 290 | "metadata": {}, 291 | "source": [ 292 | "## Pivot Tables" 293 | ] 294 | }, 295 | { 296 | "cell_type": "code", 297 | "execution_count": 11, 298 | "metadata": {}, 299 | "outputs": [ 300 | { 301 | "data": { 302 | "text/html": [ 303 | "
\n", 304 | "\n", 317 | "\n", 318 | " \n", 319 | " \n", 320 | " \n", 321 | " \n", 322 | " \n", 323 | " \n", 324 | " \n", 325 | " \n", 326 | " \n", 327 | " \n", 328 | " \n", 329 | " \n", 330 | " \n", 331 | " \n", 332 | " \n", 333 | " \n", 334 | " \n", 335 | " \n", 336 | " \n", 337 | " \n", 338 | " \n", 339 | " \n", 340 | " \n", 341 | " \n", 342 | " \n", 343 | " \n", 344 | " \n", 345 | " \n", 346 | "
Sales
City
Atlanta7642
New York City8249
Portland4231
Toronto9571
\n", 347 | "
" 348 | ], 349 | "text/plain": [ 350 | " Sales\n", 351 | "City \n", 352 | "Atlanta 7642\n", 353 | "New York City 8249\n", 354 | "Portland 4231\n", 355 | "Toronto 9571" 356 | ] 357 | }, 358 | "execution_count": 11, 359 | "metadata": {}, 360 | "output_type": "execute_result" 361 | } 362 | ], 363 | "source": [ 364 | "sales.pivot_table(index = 'City', values = 'Sales', aggfunc = 'sum')" 365 | ] 366 | }, 367 | { 368 | "cell_type": "code", 369 | "execution_count": null, 370 | "metadata": {}, 371 | "outputs": [], 372 | "source": [] 373 | } 374 | ], 375 | "metadata": { 376 | "kernelspec": { 377 | "display_name": "Python 3", 378 | "language": "python", 379 | "name": "python3" 380 | }, 381 | "language_info": { 382 | "codemirror_mode": { 383 | "name": "ipython", 384 | "version": 3 385 | }, 386 | "file_extension": ".py", 387 | "mimetype": "text/x-python", 388 | "name": "python", 389 | "nbconvert_exporter": "python", 390 | "pygments_lexer": "ipython3", 391 | "version": "3.7.6" 392 | } 393 | }, 394 | "nbformat": 4, 395 | "nbformat_minor": 4 396 | } 397 | -------------------------------------------------------------------------------- /AAPL.csv: -------------------------------------------------------------------------------- 1 | ,Date,Open,Symbol 2 | 0,2020-03-30,62.685001,AAPL 3 | 1,2020-03-31,63.900002,AAPL 4 | 2,2020-04-01,61.625,AAPL 5 | 3,2020-04-02,60.084998999999996,AAPL 6 | 4,2020-04-03,60.700001,AAPL 7 | 5,2020-04-06,62.724998,AAPL 8 | 6,2020-04-07,67.699997,AAPL 9 | 7,2020-04-08,65.684998,AAPL 10 | 8,2020-04-09,67.175003,AAPL 11 | 9,2020-04-13,67.077499,AAPL 12 | 10,2020-04-14,70.0,AAPL 13 | 11,2020-04-15,70.599998,AAPL 14 | 12,2020-04-16,71.845001,AAPL 15 | 13,2020-04-17,71.172501,AAPL 16 | 14,2020-04-20,69.487503,AAPL 17 | 15,2020-04-21,69.07,AAPL 18 | 16,2020-04-22,68.402496,AAPL 19 | 17,2020-04-23,68.967499,AAPL 20 | 18,2020-04-24,69.300003,AAPL 21 | 19,2020-04-27,70.449997,AAPL 22 | 20,2020-04-28,71.269997,AAPL 23 | 21,2020-04-29,71.182503,AAPL 24 | 22,2020-04-30,72.489998,AAPL 25 | 23,2020-05-01,71.5625,AAPL 26 | 24,2020-05-04,72.292503,AAPL 27 | 25,2020-05-05,73.764999,AAPL 28 | 26,2020-05-06,75.114998,AAPL 29 | 27,2020-05-07,75.805,AAPL 30 | 28,2020-05-08,76.410004,AAPL 31 | 29,2020-05-11,77.025002,AAPL 32 | 30,2020-05-12,79.457497,AAPL 33 | 31,2020-05-13,78.037498,AAPL 34 | 32,2020-05-14,76.127502,AAPL 35 | 33,2020-05-15,75.087502,AAPL 36 | 34,2020-05-18,78.292503,AAPL 37 | 35,2020-05-19,78.7575,AAPL 38 | 36,2020-05-20,79.16999799999999,AAPL 39 | 37,2020-05-21,79.665001,AAPL 40 | 38,2020-05-22,78.942497,AAPL 41 | 39,2020-05-26,80.875,AAPL 42 | 40,2020-05-27,79.035004,AAPL 43 | 41,2020-05-28,79.192497,AAPL 44 | 42,2020-05-29,79.8125,AAPL 45 | 43,2020-06-01,79.4375,AAPL 46 | 44,2020-06-02,80.1875,AAPL 47 | 45,2020-06-03,81.165001,AAPL 48 | 46,2020-06-04,81.097504,AAPL 49 | 47,2020-06-05,80.837502,AAPL 50 | 48,2020-06-08,82.5625,AAPL 51 | 49,2020-06-09,83.035004,AAPL 52 | 50,2020-06-10,86.974998,AAPL 53 | 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189,2020-12-28,133.990005,AAPL 192 | 190,2020-12-29,138.050003,AAPL 193 | 191,2020-12-30,135.580002,AAPL 194 | 192,2020-12-31,134.080002,AAPL 195 | 193,2021-01-04,133.520004,AAPL 196 | 194,2021-01-05,128.889999,AAPL 197 | 195,2021-01-06,127.720001,AAPL 198 | 196,2021-01-07,128.360001,AAPL 199 | 197,2021-01-08,132.429993,AAPL 200 | 198,2021-01-11,129.190002,AAPL 201 | 199,2021-01-12,128.5,AAPL 202 | 200,2021-01-13,128.759995,AAPL 203 | 201,2021-01-14,130.800003,AAPL 204 | 202,2021-01-15,128.779999,AAPL 205 | 203,2021-01-19,127.779999,AAPL 206 | 204,2021-01-20,128.66000400000001,AAPL 207 | 205,2021-01-21,133.800003,AAPL 208 | 206,2021-01-22,136.279999,AAPL 209 | 207,2021-01-25,143.070007,AAPL 210 | 208,2021-01-26,143.600006,AAPL 211 | 209,2021-01-27,143.429993,AAPL 212 | 210,2021-01-28,139.520004,AAPL 213 | 211,2021-01-29,135.830002,AAPL 214 | 212,2021-02-01,133.75,AAPL 215 | 213,2021-02-02,135.729996,AAPL 216 | 214,2021-02-03,135.759995,AAPL 217 | 215,2021-02-04,136.300003,AAPL 218 | 216,2021-02-05,137.350006,AAPL 219 | 217,2021-02-08,136.029999,AAPL 220 | 218,2021-02-09,136.619995,AAPL 221 | 219,2021-02-10,136.479996,AAPL 222 | 220,2021-02-11,135.899994,AAPL 223 | 221,2021-02-12,134.350006,AAPL 224 | 222,2021-02-16,135.490005,AAPL 225 | 223,2021-02-17,131.25,AAPL 226 | 224,2021-02-18,129.199997,AAPL 227 | 225,2021-02-19,130.240005,AAPL 228 | 226,2021-02-22,128.009995,AAPL 229 | 227,2021-02-23,123.760002,AAPL 230 | 228,2021-02-24,124.940002,AAPL 231 | 229,2021-02-25,124.68,AAPL 232 | 230,2021-02-26,122.589996,AAPL 233 | 231,2021-03-01,123.75,AAPL 234 | 232,2021-03-02,128.41000400000001,AAPL 235 | 233,2021-03-03,124.809998,AAPL 236 | 234,2021-03-04,121.75,AAPL 237 | 235,2021-03-05,120.980003,AAPL 238 | 236,2021-03-08,120.93,AAPL 239 | 237,2021-03-09,119.029999,AAPL 240 | 238,2021-03-10,121.690002,AAPL 241 | 239,2021-03-11,122.540001,AAPL 242 | 240,2021-03-12,120.400002,AAPL 243 | 241,2021-03-15,121.410004,AAPL 244 | 242,2021-03-16,125.699997,AAPL 245 | 243,2021-03-17,124.050003,AAPL 246 | 244,2021-03-18,122.879997,AAPL 247 | 245,2021-03-19,119.900002,AAPL 248 | 246,2021-03-22,120.33000200000001,AAPL 249 | 247,2021-03-23,123.33000200000001,AAPL 250 | 248,2021-03-24,122.82,AAPL 251 | 249,2021-03-25,119.540001,AAPL 252 | 250,2021-03-26,120.349998,AAPL 253 | -------------------------------------------------------------------------------- /Bayern Munich.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/Bayern Munich.xlsx -------------------------------------------------------------------------------- /December.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/December.xlsx -------------------------------------------------------------------------------- /Excel Files.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/Excel Files.zip -------------------------------------------------------------------------------- /ExcelMagic.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/ExcelMagic.zip -------------------------------------------------------------------------------- /Files.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/Files.zip -------------------------------------------------------------------------------- /List to String Python.py: -------------------------------------------------------------------------------- 1 | our_list = ['I','am', 'learning', 'Python', 'with', 'datagy!'] 2 | 3 | def spaces(your_list): 4 | """Delimit your list by spaces.""" 5 | return ' '.join(your_list) 6 | 7 | space_string = spaces(our_list) 8 | print("Our list delimited by spaces:") 9 | print(space_string) 10 | 11 | def commas(your_list): 12 | """Delimit your list by commas.""" 13 | return ','.join(your_list) 14 | 15 | comma_string = commas(our_list) 16 | print("Our list delimited by commas:") 17 | print(comma_string) 18 | 19 | def new_lines(your_list): 20 | """Delimit your list by new lines.""" 21 | return '\n'.join(your_list) 22 | 23 | new_lines_string = new_lines(our_list) 24 | print("Our list delimited by new lines:") 25 | print(new_lines_string) 26 | -------------------------------------------------------------------------------- /Naive Bayes in Python.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/Naive Bayes in Python.xlsx -------------------------------------------------------------------------------- /November.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/November.xlsx -------------------------------------------------------------------------------- /October.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/October.xlsx -------------------------------------------------------------------------------- /PandasColumns.csv: -------------------------------------------------------------------------------- 1 | Date,Name,NumSold,Total,Active 2 | 01-Jan-23,Nik,14,329.67,TRUE 3 | 02-Jan-23,Evan,12,475.71,FALSE 4 | 03-Jan-23,Kyra,16,569.64,TRUE 5 | 04-Jan-23,Kate,13,528.23,FALSE 6 | 05-Jan-23,,19,974.65,TRUE -------------------------------------------------------------------------------- /PandasTips.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/PandasTips.xlsx -------------------------------------------------------------------------------- /Pandas_read_files_tips.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/Pandas_read_files_tips.xlsx -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # mediumdata 2 | 3 | Datasets required for various Medium articles, such as those published on Towards Data Science. 4 | 5 | Beyond the datasets, this repo doesn't provide too much value! 6 | -------------------------------------------------------------------------------- /Rename Files Tutorial.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/Rename Files Tutorial.zip -------------------------------------------------------------------------------- /Sales.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/Sales.xlsx -------------------------------------------------------------------------------- /Sales2.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/Sales2.xlsx -------------------------------------------------------------------------------- /Sample.parquet: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/Sample.parquet -------------------------------------------------------------------------------- /Scores.csv: -------------------------------------------------------------------------------- 1 | English,History 2 | 75.14822377735364,87.92960604103367 3 | 75.25109581766647,86.80744621741859 4 | 76.00652154906733,87.89138835515982 5 | 75.4329351346301,87.64617724792231 6 | 75.22250657789613,87.30383109841453 7 | 74.91311699520764,87.21271012316363 8 | 74.68061312496854,86.5310598590426 9 | 75.30892199937054,87.16003994295258 10 | 75.698563952756,87.74502523108133 11 | 74.42556477847505,86.34098652735383 12 | 75.75284077289125,87.2412921401948 13 | 75.33109974169005,87.02850241022202 14 | 75.67465773248217,88.63510788987118 15 | 74.63477999854408,87.0509927391072 16 | 74.74756074292581,86.83046462179809 17 | 74.67818543596371,86.31451105416993 18 | 75.29242502847097,87.33190586347713 19 | 74.76222484869197,86.34233488642397 20 | 75.48011319169649,88.10413271693018 21 | 74.4258606509607,86.66634600703203 22 | 74.82153752923647,86.8845610065829 23 | 74.42561778314258,86.41931367143386 24 | 76.00083468159553,88.29890407579504 25 | 75.45893231592507,87.7022580105224 26 | 74.31935282856475,87.0453576832672 27 | 75.14934907181255,87.1871111230884 28 | 75.80666458751396,87.80189505358558 29 | 73.46713255929082,85.57810014184031 30 | 77.12389001611855,89.35361690000664 31 | 75.9703330668099,87.93910643698065 32 | 74.86161640661659,86.86675459965197 33 | 73.20485674017668,84.77847734248421 34 | 75.09348087564176,87.0987684978613 35 | 74.22646539565672,86.58319580009487 36 | 76.8485132467831,88.95074516470353 37 | 73.4548325076812,86.01787836273789 38 | 74.66967687700897,87.07679192791737 39 | 74.8913636189085,86.13462325178972 40 | 74.93054843452121,87.37074082420524 41 | 74.13872460293217,86.23421241854061 42 | 74.72993501269532,85.9835020133504 43 | 74.78437197603738,86.42790898911164 44 | 74.10632882636708,86.73791555783525 45 | 75.7708029061949,87.88653143486027 46 | 73.13683230443971,85.28579831364402 47 | 75.85203858545177,87.6351871123175 48 | 74.64420133959267,86.43346251258245 49 | 77.02506809443723,87.97268537738869 50 | 74.35166076870422,87.126540900804 51 | 76.6634819616333,88.54132896813371 52 | 74.71079086119944,86.5082390434513 53 | 74.76846977627622,86.44962950092922 54 | 74.85405253749865,86.52509835050382 55 | 75.23666894038843,86.99931431722953 56 | 73.92957729924692,85.26864417727963 57 | 75.37034856358821,87.64262025869792 58 | 75.1330197349026,87.20741483174272 59 | 75.78542449527889,87.74860820819816 60 | 76.7128689685019,89.23530550700694 61 | 74.73804967725731,86.37235107555172 62 | 75.33890478121077,87.30078775010293 63 | 73.812425437829,85.98654247569843 64 | 74.32335916046806,86.20487884510352 65 | 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161 | 74.92717814262778,86.79873471659216 162 | 75.60007475697162,87.42930412560705 163 | 75.86198729873134,87.58090534081708 164 | 76.67335333272602,88.3520975662141 165 | 75.4802961406108,86.9227424142962 166 | 75.29691794429272,87.05920823135109 167 | 75.76307882279389,87.47645311756212 168 | 74.04962343595476,86.31883236587993 169 | 75.07769100919873,87.04874682898591 170 | 75.08577909555105,86.8780255926441 171 | 73.67390167601746,85.92323443097595 172 | 75.53474254155944,87.4248077754262 173 | 75.33162098522298,87.40699150837919 174 | 75.59886380183103,87.04153396833692 175 | 74.70883842991846,86.9457332331496 176 | 74.29502273506043,86.77673226629331 177 | 75.39233180633262,86.73696607919051 178 | 75.42210085789371,87.2339618784915 179 | 76.22246496640359,88.32801976108608 180 | 74.90437678049994,86.63970164571612 181 | 75.13215645421708,86.80312039189066 182 | 75.18153396568123,87.01094256850762 183 | 73.90494473825056,86.11634619736834 184 | 75.18547721327127,87.61187886148666 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https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/february.xlsx -------------------------------------------------------------------------------- /fillna.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/fillna.xlsx -------------------------------------------------------------------------------- /insurance.csv: -------------------------------------------------------------------------------- 1 | age,sex,bmi,children,smoker,region,charges 2 | 19,female,27.9,0,yes,southwest,16884.924 3 | 18,male,33.77,1,no,southeast,1725.5523 4 | 28,male,33,3,no,southeast,4449.462 5 | 33,male,22.705,0,no,northwest,21984.47061 6 | 32,male,28.88,0,no,northwest,3866.8552 7 | 31,female,25.74,0,no,southeast,3756.6216 8 | 46,female,33.44,1,no,southeast,8240.5896 9 | 37,female,27.74,3,no,northwest,7281.5056 10 | 37,male,29.83,2,no,northeast,6406.4107 11 | 60,female,25.84,0,no,northwest,28923.13692 12 | 25,male,26.22,0,no,northeast,2721.3208 13 | 62,female,26.29,0,yes,southeast,27808.7251 14 | 23,male,34.4,0,no,southwest,1826.843 15 | 56,female,39.82,0,no,southeast,11090.7178 16 | 27,male,42.13,0,yes,southeast,39611.7577 17 | 19,male,24.6,1,no,southwest,1837.237 18 | 52,female,30.78,1,no,northeast,10797.3362 19 | 23,male,23.845,0,no,northeast,2395.17155 20 | 56,male,40.3,0,no,southwest,10602.385 21 | 30,male,35.3,0,yes,southwest,36837.467 22 | 60,female,36.005,0,no,northeast,13228.84695 23 | 30,female,32.4,1,no,southwest,4149.736 24 | 18,male,34.1,0,no,southeast,1137.011 25 | 34,female,31.92,1,yes,northeast,37701.8768 26 | 37,male,28.025,2,no,northwest,6203.90175 27 | 59,female,27.72,3,no,southeast,14001.1338 28 | 63,female,23.085,0,no,northeast,14451.83515 29 | 55,female,32.775,2,no,northwest,12268.63225 30 | 23,male,17.385,1,no,northwest,2775.19215 31 | 31,male,36.3,2,yes,southwest,38711 32 | 22,male,35.6,0,yes,southwest,35585.576 33 | 18,female,26.315,0,no,northeast,2198.18985 34 | 19,female,28.6,5,no,southwest,4687.797 35 | 63,male,28.31,0,no,northwest,13770.0979 36 | 28,male,36.4,1,yes,southwest,51194.55914 37 | 19,male,20.425,0,no,northwest,1625.43375 38 | 62,female,32.965,3,no,northwest,15612.19335 39 | 26,male,20.8,0,no,southwest,2302.3 40 | 35,male,36.67,1,yes,northeast,39774.2763 41 | 60,male,39.9,0,yes,southwest,48173.361 42 | 24,female,26.6,0,no,northeast,3046.062 43 | 31,female,36.63,2,no,southeast,4949.7587 44 | 41,male,21.78,1,no,southeast,6272.4772 45 | 37,female,30.8,2,no,southeast,6313.759 46 | 38,male,37.05,1,no,northeast,6079.6715 47 | 55,male,37.3,0,no,southwest,20630.28351 48 | 18,female,38.665,2,no,northeast,3393.35635 49 | 28,female,34.77,0,no,northwest,3556.9223 50 | 60,female,24.53,0,no,southeast,12629.8967 51 | 36,male,35.2,1,yes,southeast,38709.176 52 | 18,female,35.625,0,no,northeast,2211.13075 53 | 21,female,33.63,2,no,northwest,3579.8287 54 | 48,male,28,1,yes,southwest,23568.272 55 | 36,male,34.43,0,yes,southeast,37742.5757 56 | 40,female,28.69,3,no,northwest,8059.6791 57 | 58,male,36.955,2,yes,northwest,47496.49445 58 | 58,female,31.825,2,no,northeast,13607.36875 59 | 18,male,31.68,2,yes,southeast,34303.1672 60 | 53,female,22.88,1,yes,southeast,23244.7902 61 | 34,female,37.335,2,no,northwest,5989.52365 62 | 43,male,27.36,3,no,northeast,8606.2174 63 | 25,male,33.66,4,no,southeast,4504.6624 64 | 64,male,24.7,1,no,northwest,30166.61817 65 | 28,female,25.935,1,no,northwest,4133.64165 66 | 20,female,22.42,0,yes,northwest,14711.7438 67 | 19,female,28.9,0,no,southwest,1743.214 68 | 61,female,39.1,2,no,southwest,14235.072 69 | 40,male,26.315,1,no,northwest,6389.37785 70 | 40,female,36.19,0,no,southeast,5920.1041 71 | 28,male,23.98,3,yes,southeast,17663.1442 72 | 27,female,24.75,0,yes,southeast,16577.7795 73 | 31,male,28.5,5,no,northeast,6799.458 74 | 53,female,28.1,3,no,southwest,11741.726 75 | 58,male,32.01,1,no,southeast,11946.6259 76 | 44,male,27.4,2,no,southwest,7726.854 77 | 57,male,34.01,0,no,northwest,11356.6609 78 | 29,female,29.59,1,no,southeast,3947.4131 79 | 21,male,35.53,0,no,southeast,1532.4697 80 | 22,female,39.805,0,no,northeast,2755.02095 81 | 41,female,32.965,0,no,northwest,6571.02435 82 | 31,male,26.885,1,no,northeast,4441.21315 83 | 45,female,38.285,0,no,northeast,7935.29115 84 | 22,male,37.62,1,yes,southeast,37165.1638 85 | 48,female,41.23,4,no,northwest,11033.6617 86 | 37,female,34.8,2,yes,southwest,39836.519 87 | 45,male,22.895,2,yes,northwest,21098.55405 88 | 57,female,31.16,0,yes,northwest,43578.9394 89 | 56,female,27.2,0,no,southwest,11073.176 90 | 46,female,27.74,0,no,northwest,8026.6666 91 | 55,female,26.98,0,no,northwest,11082.5772 92 | 21,female,39.49,0,no,southeast,2026.9741 93 | 53,female,24.795,1,no,northwest,10942.13205 94 | 59,male,29.83,3,yes,northeast,30184.9367 95 | 35,male,34.77,2,no,northwest,5729.0053 96 | 64,female,31.3,2,yes,southwest,47291.055 97 | 28,female,37.62,1,no,southeast,3766.8838 98 | 54,female,30.8,3,no,southwest,12105.32 99 | 55,male,38.28,0,no,southeast,10226.2842 100 | 56,male,19.95,0,yes,northeast,22412.6485 101 | 38,male,19.3,0,yes,southwest,15820.699 102 | 41,female,31.6,0,no,southwest,6186.127 103 | 30,male,25.46,0,no,northeast,3645.0894 104 | 18,female,30.115,0,no,northeast,21344.8467 105 | 61,female,29.92,3,yes,southeast,30942.1918 106 | 34,female,27.5,1,no,southwest,5003.853 107 | 20,male,28.025,1,yes,northwest,17560.37975 108 | 19,female,28.4,1,no,southwest,2331.519 109 | 26,male,30.875,2,no,northwest,3877.30425 110 | 29,male,27.94,0,no,southeast,2867.1196 111 | 63,male,35.09,0,yes,southeast,47055.5321 112 | 54,male,33.63,1,no,northwest,10825.2537 113 | 55,female,29.7,2,no,southwest,11881.358 114 | 37,male,30.8,0,no,southwest,4646.759 115 | 21,female,35.72,0,no,northwest,2404.7338 116 | 52,male,32.205,3,no,northeast,11488.31695 117 | 60,male,28.595,0,no,northeast,30259.99556 118 | 58,male,49.06,0,no,southeast,11381.3254 119 | 29,female,27.94,1,yes,southeast,19107.7796 120 | 49,female,27.17,0,no,southeast,8601.3293 121 | 37,female,23.37,2,no,northwest,6686.4313 122 | 44,male,37.1,2,no,southwest,7740.337 123 | 18,male,23.75,0,no,northeast,1705.6245 124 | 20,female,28.975,0,no,northwest,2257.47525 125 | 44,male,31.35,1,yes,northeast,39556.4945 126 | 47,female,33.915,3,no,northwest,10115.00885 127 | 26,female,28.785,0,no,northeast,3385.39915 128 | 19,female,28.3,0,yes,southwest,17081.08 129 | 52,female,37.4,0,no,southwest,9634.538 130 | 32,female,17.765,2,yes,northwest,32734.1863 131 | 38,male,34.7,2,no,southwest,6082.405 132 | 59,female,26.505,0,no,northeast,12815.44495 133 | 61,female,22.04,0,no,northeast,13616.3586 134 | 53,female,35.9,2,no,southwest,11163.568 135 | 19,male,25.555,0,no,northwest,1632.56445 136 | 20,female,28.785,0,no,northeast,2457.21115 137 | 22,female,28.05,0,no,southeast,2155.6815 138 | 19,male,34.1,0,no,southwest,1261.442 139 | 22,male,25.175,0,no,northwest,2045.68525 140 | 54,female,31.9,3,no,southeast,27322.73386 141 | 22,female,36,0,no,southwest,2166.732 142 | 34,male,22.42,2,no,northeast,27375.90478 143 | 26,male,32.49,1,no,northeast,3490.5491 144 | 34,male,25.3,2,yes,southeast,18972.495 145 | 29,male,29.735,2,no,northwest,18157.876 146 | 30,male,28.69,3,yes,northwest,20745.9891 147 | 29,female,38.83,3,no,southeast,5138.2567 148 | 46,male,30.495,3,yes,northwest,40720.55105 149 | 51,female,37.73,1,no,southeast,9877.6077 150 | 53,female,37.43,1,no,northwest,10959.6947 151 | 19,male,28.4,1,no,southwest,1842.519 152 | 35,male,24.13,1,no,northwest,5125.2157 153 | 48,male,29.7,0,no,southeast,7789.635 154 | 32,female,37.145,3,no,northeast,6334.34355 155 | 42,female,23.37,0,yes,northeast,19964.7463 156 | 40,female,25.46,1,no,northeast,7077.1894 157 | 44,male,39.52,0,no,northwest,6948.7008 158 | 48,male,24.42,0,yes,southeast,21223.6758 159 | 18,male,25.175,0,yes,northeast,15518.18025 160 | 30,male,35.53,0,yes,southeast,36950.2567 161 | 50,female,27.83,3,no,southeast,19749.38338 162 | 42,female,26.6,0,yes,northwest,21348.706 163 | 18,female,36.85,0,yes,southeast,36149.4835 164 | 54,male,39.6,1,no,southwest,10450.552 165 | 32,female,29.8,2,no,southwest,5152.134 166 | 37,male,29.64,0,no,northwest,5028.1466 167 | 47,male,28.215,4,no,northeast,10407.08585 168 | 20,female,37,5,no,southwest,4830.63 169 | 32,female,33.155,3,no,northwest,6128.79745 170 | 19,female,31.825,1,no,northwest,2719.27975 171 | 27,male,18.905,3,no,northeast,4827.90495 172 | 63,male,41.47,0,no,southeast,13405.3903 173 | 49,male,30.3,0,no,southwest,8116.68 174 | 18,male,15.96,0,no,northeast,1694.7964 175 | 35,female,34.8,1,no,southwest,5246.047 176 | 24,female,33.345,0,no,northwest,2855.43755 177 | 63,female,37.7,0,yes,southwest,48824.45 178 | 38,male,27.835,2,no,northwest,6455.86265 179 | 54,male,29.2,1,no,southwest,10436.096 180 | 46,female,28.9,2,no,southwest,8823.279 181 | 41,female,33.155,3,no,northeast,8538.28845 182 | 58,male,28.595,0,no,northwest,11735.87905 183 | 18,female,38.28,0,no,southeast,1631.8212 184 | 22,male,19.95,3,no,northeast,4005.4225 185 | 44,female,26.41,0,no,northwest,7419.4779 186 | 44,male,30.69,2,no,southeast,7731.4271 187 | 36,male,41.895,3,yes,northeast,43753.33705 188 | 26,female,29.92,2,no,southeast,3981.9768 189 | 30,female,30.9,3,no,southwest,5325.651 190 | 41,female,32.2,1,no,southwest,6775.961 191 | 29,female,32.11,2,no,northwest,4922.9159 192 | 61,male,31.57,0,no,southeast,12557.6053 193 | 36,female,26.2,0,no,southwest,4883.866 194 | 25,male,25.74,0,no,southeast,2137.6536 195 | 56,female,26.6,1,no,northwest,12044.342 196 | 18,male,34.43,0,no,southeast,1137.4697 197 | 19,male,30.59,0,no,northwest,1639.5631 198 | 39,female,32.8,0,no,southwest,5649.715 199 | 45,female,28.6,2,no,southeast,8516.829 200 | 51,female,18.05,0,no,northwest,9644.2525 201 | 64,female,39.33,0,no,northeast,14901.5167 202 | 19,female,32.11,0,no,northwest,2130.6759 203 | 48,female,32.23,1,no,southeast,8871.1517 204 | 60,female,24.035,0,no,northwest,13012.20865 205 | 27,female,36.08,0,yes,southeast,37133.8982 206 | 46,male,22.3,0,no,southwest,7147.105 207 | 28,female,28.88,1,no,northeast,4337.7352 208 | 59,male,26.4,0,no,southeast,11743.299 209 | 35,male,27.74,2,yes,northeast,20984.0936 210 | 63,female,31.8,0,no,southwest,13880.949 211 | 40,male,41.23,1,no,northeast,6610.1097 212 | 20,male,33,1,no,southwest,1980.07 213 | 40,male,30.875,4,no,northwest,8162.71625 214 | 24,male,28.5,2,no,northwest,3537.703 215 | 34,female,26.73,1,no,southeast,5002.7827 216 | 45,female,30.9,2,no,southwest,8520.026 217 | 41,female,37.1,2,no,southwest,7371.772 218 | 53,female,26.6,0,no,northwest,10355.641 219 | 27,male,23.1,0,no,southeast,2483.736 220 | 26,female,29.92,1,no,southeast,3392.9768 221 | 24,female,23.21,0,no,southeast,25081.76784 222 | 34,female,33.7,1,no,southwest,5012.471 223 | 53,female,33.25,0,no,northeast,10564.8845 224 | 32,male,30.8,3,no,southwest,5253.524 225 | 19,male,34.8,0,yes,southwest,34779.615 226 | 42,male,24.64,0,yes,southeast,19515.5416 227 | 55,male,33.88,3,no,southeast,11987.1682 228 | 28,male,38.06,0,no,southeast,2689.4954 229 | 58,female,41.91,0,no,southeast,24227.33724 230 | 41,female,31.635,1,no,northeast,7358.17565 231 | 47,male,25.46,2,no,northeast,9225.2564 232 | 42,female,36.195,1,no,northwest,7443.64305 233 | 59,female,27.83,3,no,southeast,14001.2867 234 | 19,female,17.8,0,no,southwest,1727.785 235 | 59,male,27.5,1,no,southwest,12333.828 236 | 39,male,24.51,2,no,northwest,6710.1919 237 | 40,female,22.22,2,yes,southeast,19444.2658 238 | 18,female,26.73,0,no,southeast,1615.7667 239 | 31,male,38.39,2,no,southeast,4463.2051 240 | 19,male,29.07,0,yes,northwest,17352.6803 241 | 44,male,38.06,1,no,southeast,7152.6714 242 | 23,female,36.67,2,yes,northeast,38511.6283 243 | 33,female,22.135,1,no,northeast,5354.07465 244 | 55,female,26.8,1,no,southwest,35160.13457 245 | 40,male,35.3,3,no,southwest,7196.867 246 | 63,female,27.74,0,yes,northeast,29523.1656 247 | 54,male,30.02,0,no,northwest,24476.47851 248 | 60,female,38.06,0,no,southeast,12648.7034 249 | 24,male,35.86,0,no,southeast,1986.9334 250 | 19,male,20.9,1,no,southwest,1832.094 251 | 29,male,28.975,1,no,northeast,4040.55825 252 | 18,male,17.29,2,yes,northeast,12829.4551 253 | 63,female,32.2,2,yes,southwest,47305.305 254 | 54,male,34.21,2,yes,southeast,44260.7499 255 | 27,male,30.3,3,no,southwest,4260.744 256 | 50,male,31.825,0,yes,northeast,41097.16175 257 | 55,female,25.365,3,no,northeast,13047.33235 258 | 56,male,33.63,0,yes,northwest,43921.1837 259 | 38,female,40.15,0,no,southeast,5400.9805 260 | 51,male,24.415,4,no,northwest,11520.09985 261 | 19,male,31.92,0,yes,northwest,33750.2918 262 | 58,female,25.2,0,no,southwest,11837.16 263 | 20,female,26.84,1,yes,southeast,17085.2676 264 | 52,male,24.32,3,yes,northeast,24869.8368 265 | 19,male,36.955,0,yes,northwest,36219.40545 266 | 53,female,38.06,3,no,southeast,20462.99766 267 | 46,male,42.35,3,yes,southeast,46151.1245 268 | 40,male,19.8,1,yes,southeast,17179.522 269 | 59,female,32.395,3,no,northeast,14590.63205 270 | 45,male,30.2,1,no,southwest,7441.053 271 | 49,male,25.84,1,no,northeast,9282.4806 272 | 18,male,29.37,1,no,southeast,1719.4363 273 | 50,male,34.2,2,yes,southwest,42856.838 274 | 41,male,37.05,2,no,northwest,7265.7025 275 | 50,male,27.455,1,no,northeast,9617.66245 276 | 25,male,27.55,0,no,northwest,2523.1695 277 | 47,female,26.6,2,no,northeast,9715.841 278 | 19,male,20.615,2,no,northwest,2803.69785 279 | 22,female,24.3,0,no,southwest,2150.469 280 | 59,male,31.79,2,no,southeast,12928.7911 281 | 51,female,21.56,1,no,southeast,9855.1314 282 | 40,female,28.12,1,yes,northeast,22331.5668 283 | 54,male,40.565,3,yes,northeast,48549.17835 284 | 30,male,27.645,1,no,northeast,4237.12655 285 | 55,female,32.395,1,no,northeast,11879.10405 286 | 52,female,31.2,0,no,southwest,9625.92 287 | 46,male,26.62,1,no,southeast,7742.1098 288 | 46,female,48.07,2,no,northeast,9432.9253 289 | 63,female,26.22,0,no,northwest,14256.1928 290 | 59,female,36.765,1,yes,northeast,47896.79135 291 | 52,male,26.4,3,no,southeast,25992.82104 292 | 28,female,33.4,0,no,southwest,3172.018 293 | 29,male,29.64,1,no,northeast,20277.80751 294 | 25,male,45.54,2,yes,southeast,42112.2356 295 | 22,female,28.82,0,no,southeast,2156.7518 296 | 25,male,26.8,3,no,southwest,3906.127 297 | 18,male,22.99,0,no,northeast,1704.5681 298 | 19,male,27.7,0,yes,southwest,16297.846 299 | 47,male,25.41,1,yes,southeast,21978.6769 300 | 31,male,34.39,3,yes,northwest,38746.3551 301 | 48,female,28.88,1,no,northwest,9249.4952 302 | 36,male,27.55,3,no,northeast,6746.7425 303 | 53,female,22.61,3,yes,northeast,24873.3849 304 | 56,female,37.51,2,no,southeast,12265.5069 305 | 28,female,33,2,no,southeast,4349.462 306 | 57,female,38,2,no,southwest,12646.207 307 | 29,male,33.345,2,no,northwest,19442.3535 308 | 28,female,27.5,2,no,southwest,20177.67113 309 | 30,female,33.33,1,no,southeast,4151.0287 310 | 58,male,34.865,0,no,northeast,11944.59435 311 | 41,female,33.06,2,no,northwest,7749.1564 312 | 50,male,26.6,0,no,southwest,8444.474 313 | 19,female,24.7,0,no,southwest,1737.376 314 | 43,male,35.97,3,yes,southeast,42124.5153 315 | 49,male,35.86,0,no,southeast,8124.4084 316 | 27,female,31.4,0,yes,southwest,34838.873 317 | 52,male,33.25,0,no,northeast,9722.7695 318 | 50,male,32.205,0,no,northwest,8835.26495 319 | 54,male,32.775,0,no,northeast,10435.06525 320 | 44,female,27.645,0,no,northwest,7421.19455 321 | 32,male,37.335,1,no,northeast,4667.60765 322 | 34,male,25.27,1,no,northwest,4894.7533 323 | 26,female,29.64,4,no,northeast,24671.66334 324 | 34,male,30.8,0,yes,southwest,35491.64 325 | 57,male,40.945,0,no,northeast,11566.30055 326 | 29,male,27.2,0,no,southwest,2866.091 327 | 40,male,34.105,1,no,northeast,6600.20595 328 | 27,female,23.21,1,no,southeast,3561.8889 329 | 45,male,36.48,2,yes,northwest,42760.5022 330 | 64,female,33.8,1,yes,southwest,47928.03 331 | 52,male,36.7,0,no,southwest,9144.565 332 | 61,female,36.385,1,yes,northeast,48517.56315 333 | 52,male,27.36,0,yes,northwest,24393.6224 334 | 61,female,31.16,0,no,northwest,13429.0354 335 | 56,female,28.785,0,no,northeast,11658.37915 336 | 43,female,35.72,2,no,northeast,19144.57652 337 | 64,male,34.5,0,no,southwest,13822.803 338 | 60,male,25.74,0,no,southeast,12142.5786 339 | 62,male,27.55,1,no,northwest,13937.6665 340 | 50,male,32.3,1,yes,northeast,41919.097 341 | 46,female,27.72,1,no,southeast,8232.6388 342 | 24,female,27.6,0,no,southwest,18955.22017 343 | 62,male,30.02,0,no,northwest,13352.0998 344 | 60,female,27.55,0,no,northeast,13217.0945 345 | 63,male,36.765,0,no,northeast,13981.85035 346 | 49,female,41.47,4,no,southeast,10977.2063 347 | 34,female,29.26,3,no,southeast,6184.2994 348 | 33,male,35.75,2,no,southeast,4889.9995 349 | 46,male,33.345,1,no,northeast,8334.45755 350 | 36,female,29.92,1,no,southeast,5478.0368 351 | 19,male,27.835,0,no,northwest,1635.73365 352 | 57,female,23.18,0,no,northwest,11830.6072 353 | 50,female,25.6,0,no,southwest,8932.084 354 | 30,female,27.7,0,no,southwest,3554.203 355 | 33,male,35.245,0,no,northeast,12404.8791 356 | 18,female,38.28,0,no,southeast,14133.03775 357 | 46,male,27.6,0,no,southwest,24603.04837 358 | 46,male,43.89,3,no,southeast,8944.1151 359 | 47,male,29.83,3,no,northwest,9620.3307 360 | 23,male,41.91,0,no,southeast,1837.2819 361 | 18,female,20.79,0,no,southeast,1607.5101 362 | 48,female,32.3,2,no,northeast,10043.249 363 | 35,male,30.5,1,no,southwest,4751.07 364 | 19,female,21.7,0,yes,southwest,13844.506 365 | 21,female,26.4,1,no,southwest,2597.779 366 | 21,female,21.89,2,no,southeast,3180.5101 367 | 49,female,30.78,1,no,northeast,9778.3472 368 | 56,female,32.3,3,no,northeast,13430.265 369 | 42,female,24.985,2,no,northwest,8017.06115 370 | 44,male,32.015,2,no,northwest,8116.26885 371 | 18,male,30.4,3,no,northeast,3481.868 372 | 61,female,21.09,0,no,northwest,13415.0381 373 | 57,female,22.23,0,no,northeast,12029.2867 374 | 42,female,33.155,1,no,northeast,7639.41745 375 | 26,male,32.9,2,yes,southwest,36085.219 376 | 20,male,33.33,0,no,southeast,1391.5287 377 | 23,female,28.31,0,yes,northwest,18033.9679 378 | 39,female,24.89,3,yes,northeast,21659.9301 379 | 24,male,40.15,0,yes,southeast,38126.2465 380 | 64,female,30.115,3,no,northwest,16455.70785 381 | 62,male,31.46,1,no,southeast,27000.98473 382 | 27,female,17.955,2,yes,northeast,15006.57945 383 | 55,male,30.685,0,yes,northeast,42303.69215 384 | 55,male,33,0,no,southeast,20781.48892 385 | 35,female,43.34,2,no,southeast,5846.9176 386 | 44,male,22.135,2,no,northeast,8302.53565 387 | 19,male,34.4,0,no,southwest,1261.859 388 | 58,female,39.05,0,no,southeast,11856.4115 389 | 50,male,25.365,2,no,northwest,30284.64294 390 | 26,female,22.61,0,no,northwest,3176.8159 391 | 24,female,30.21,3,no,northwest,4618.0799 392 | 48,male,35.625,4,no,northeast,10736.87075 393 | 19,female,37.43,0,no,northwest,2138.0707 394 | 48,male,31.445,1,no,northeast,8964.06055 395 | 49,male,31.35,1,no,northeast,9290.1395 396 | 46,female,32.3,2,no,northeast,9411.005 397 | 46,male,19.855,0,no,northwest,7526.70645 398 | 43,female,34.4,3,no,southwest,8522.003 399 | 21,male,31.02,0,no,southeast,16586.49771 400 | 64,male,25.6,2,no,southwest,14988.432 401 | 18,female,38.17,0,no,southeast,1631.6683 402 | 51,female,20.6,0,no,southwest,9264.797 403 | 47,male,47.52,1,no,southeast,8083.9198 404 | 64,female,32.965,0,no,northwest,14692.66935 405 | 49,male,32.3,3,no,northwest,10269.46 406 | 31,male,20.4,0,no,southwest,3260.199 407 | 52,female,38.38,2,no,northeast,11396.9002 408 | 33,female,24.31,0,no,southeast,4185.0979 409 | 47,female,23.6,1,no,southwest,8539.671 410 | 38,male,21.12,3,no,southeast,6652.5288 411 | 32,male,30.03,1,no,southeast,4074.4537 412 | 19,male,17.48,0,no,northwest,1621.3402 413 | 44,female,20.235,1,yes,northeast,19594.80965 414 | 26,female,17.195,2,yes,northeast,14455.64405 415 | 25,male,23.9,5,no,southwest,5080.096 416 | 19,female,35.15,0,no,northwest,2134.9015 417 | 43,female,35.64,1,no,southeast,7345.7266 418 | 52,male,34.1,0,no,southeast,9140.951 419 | 36,female,22.6,2,yes,southwest,18608.262 420 | 64,male,39.16,1,no,southeast,14418.2804 421 | 63,female,26.98,0,yes,northwest,28950.4692 422 | 64,male,33.88,0,yes,southeast,46889.2612 423 | 61,male,35.86,0,yes,southeast,46599.1084 424 | 40,male,32.775,1,yes,northeast,39125.33225 425 | 25,male,30.59,0,no,northeast,2727.3951 426 | 48,male,30.2,2,no,southwest,8968.33 427 | 45,male,24.31,5,no,southeast,9788.8659 428 | 38,female,27.265,1,no,northeast,6555.07035 429 | 18,female,29.165,0,no,northeast,7323.734819 430 | 21,female,16.815,1,no,northeast,3167.45585 431 | 27,female,30.4,3,no,northwest,18804.7524 432 | 19,male,33.1,0,no,southwest,23082.95533 433 | 29,female,20.235,2,no,northwest,4906.40965 434 | 42,male,26.9,0,no,southwest,5969.723 435 | 60,female,30.5,0,no,southwest,12638.195 436 | 31,male,28.595,1,no,northwest,4243.59005 437 | 60,male,33.11,3,no,southeast,13919.8229 438 | 22,male,31.73,0,no,northeast,2254.7967 439 | 35,male,28.9,3,no,southwest,5926.846 440 | 52,female,46.75,5,no,southeast,12592.5345 441 | 26,male,29.45,0,no,northeast,2897.3235 442 | 31,female,32.68,1,no,northwest,4738.2682 443 | 33,female,33.5,0,yes,southwest,37079.372 444 | 18,male,43.01,0,no,southeast,1149.3959 445 | 59,female,36.52,1,no,southeast,28287.89766 446 | 56,male,26.695,1,yes,northwest,26109.32905 447 | 45,female,33.1,0,no,southwest,7345.084 448 | 60,male,29.64,0,no,northeast,12730.9996 449 | 56,female,25.65,0,no,northwest,11454.0215 450 | 40,female,29.6,0,no,southwest,5910.944 451 | 35,male,38.6,1,no,southwest,4762.329 452 | 39,male,29.6,4,no,southwest,7512.267 453 | 30,male,24.13,1,no,northwest,4032.2407 454 | 24,male,23.4,0,no,southwest,1969.614 455 | 20,male,29.735,0,no,northwest,1769.53165 456 | 32,male,46.53,2,no,southeast,4686.3887 457 | 59,male,37.4,0,no,southwest,21797.0004 458 | 55,female,30.14,2,no,southeast,11881.9696 459 | 57,female,30.495,0,no,northwest,11840.77505 460 | 56,male,39.6,0,no,southwest,10601.412 461 | 40,female,33,3,no,southeast,7682.67 462 | 49,female,36.63,3,no,southeast,10381.4787 463 | 42,male,30,0,yes,southwest,22144.032 464 | 62,female,38.095,2,no,northeast,15230.32405 465 | 56,male,25.935,0,no,northeast,11165.41765 466 | 19,male,25.175,0,no,northwest,1632.03625 467 | 30,female,28.38,1,yes,southeast,19521.9682 468 | 60,female,28.7,1,no,southwest,13224.693 469 | 56,female,33.82,2,no,northwest,12643.3778 470 | 28,female,24.32,1,no,northeast,23288.9284 471 | 18,female,24.09,1,no,southeast,2201.0971 472 | 27,male,32.67,0,no,southeast,2497.0383 473 | 18,female,30.115,0,no,northeast,2203.47185 474 | 19,female,29.8,0,no,southwest,1744.465 475 | 47,female,33.345,0,no,northeast,20878.78443 476 | 54,male,25.1,3,yes,southwest,25382.297 477 | 61,male,28.31,1,yes,northwest,28868.6639 478 | 24,male,28.5,0,yes,northeast,35147.52848 479 | 25,male,35.625,0,no,northwest,2534.39375 480 | 21,male,36.85,0,no,southeast,1534.3045 481 | 23,male,32.56,0,no,southeast,1824.2854 482 | 63,male,41.325,3,no,northwest,15555.18875 483 | 49,male,37.51,2,no,southeast,9304.7019 484 | 18,female,31.35,0,no,southeast,1622.1885 485 | 51,female,39.5,1,no,southwest,9880.068 486 | 48,male,34.3,3,no,southwest,9563.029 487 | 31,female,31.065,0,no,northeast,4347.02335 488 | 54,female,21.47,3,no,northwest,12475.3513 489 | 19,male,28.7,0,no,southwest,1253.936 490 | 44,female,38.06,0,yes,southeast,48885.13561 491 | 53,male,31.16,1,no,northwest,10461.9794 492 | 19,female,32.9,0,no,southwest,1748.774 493 | 61,female,25.08,0,no,southeast,24513.09126 494 | 18,female,25.08,0,no,northeast,2196.4732 495 | 61,male,43.4,0,no,southwest,12574.049 496 | 21,male,25.7,4,yes,southwest,17942.106 497 | 20,male,27.93,0,no,northeast,1967.0227 498 | 31,female,23.6,2,no,southwest,4931.647 499 | 45,male,28.7,2,no,southwest,8027.968 500 | 44,female,23.98,2,no,southeast,8211.1002 501 | 62,female,39.2,0,no,southwest,13470.86 502 | 29,male,34.4,0,yes,southwest,36197.699 503 | 43,male,26.03,0,no,northeast,6837.3687 504 | 51,male,23.21,1,yes,southeast,22218.1149 505 | 19,male,30.25,0,yes,southeast,32548.3405 506 | 38,female,28.93,1,no,southeast,5974.3847 507 | 37,male,30.875,3,no,northwest,6796.86325 508 | 22,male,31.35,1,no,northwest,2643.2685 509 | 21,male,23.75,2,no,northwest,3077.0955 510 | 24,female,25.27,0,no,northeast,3044.2133 511 | 57,female,28.7,0,no,southwest,11455.28 512 | 56,male,32.11,1,no,northeast,11763.0009 513 | 27,male,33.66,0,no,southeast,2498.4144 514 | 51,male,22.42,0,no,northeast,9361.3268 515 | 19,male,30.4,0,no,southwest,1256.299 516 | 39,male,28.3,1,yes,southwest,21082.16 517 | 58,male,35.7,0,no,southwest,11362.755 518 | 20,male,35.31,1,no,southeast,27724.28875 519 | 45,male,30.495,2,no,northwest,8413.46305 520 | 35,female,31,1,no,southwest,5240.765 521 | 31,male,30.875,0,no,northeast,3857.75925 522 | 50,female,27.36,0,no,northeast,25656.57526 523 | 32,female,44.22,0,no,southeast,3994.1778 524 | 51,female,33.915,0,no,northeast,9866.30485 525 | 38,female,37.73,0,no,southeast,5397.6167 526 | 42,male,26.07,1,yes,southeast,38245.59327 527 | 18,female,33.88,0,no,southeast,11482.63485 528 | 19,female,30.59,2,no,northwest,24059.68019 529 | 51,female,25.8,1,no,southwest,9861.025 530 | 46,male,39.425,1,no,northeast,8342.90875 531 | 18,male,25.46,0,no,northeast,1708.0014 532 | 57,male,42.13,1,yes,southeast,48675.5177 533 | 62,female,31.73,0,no,northeast,14043.4767 534 | 59,male,29.7,2,no,southeast,12925.886 535 | 37,male,36.19,0,no,southeast,19214.70553 536 | 64,male,40.48,0,no,southeast,13831.1152 537 | 38,male,28.025,1,no,northeast,6067.12675 538 | 33,female,38.9,3,no,southwest,5972.378 539 | 46,female,30.2,2,no,southwest,8825.086 540 | 46,female,28.05,1,no,southeast,8233.0975 541 | 53,male,31.35,0,no,southeast,27346.04207 542 | 34,female,38,3,no,southwest,6196.448 543 | 20,female,31.79,2,no,southeast,3056.3881 544 | 63,female,36.3,0,no,southeast,13887.204 545 | 54,female,47.41,0,yes,southeast,63770.42801 546 | 54,male,30.21,0,no,northwest,10231.4999 547 | 49,male,25.84,2,yes,northwest,23807.2406 548 | 28,male,35.435,0,no,northeast,3268.84665 549 | 54,female,46.7,2,no,southwest,11538.421 550 | 25,female,28.595,0,no,northeast,3213.62205 551 | 43,female,46.2,0,yes,southeast,45863.205 552 | 63,male,30.8,0,no,southwest,13390.559 553 | 32,female,28.93,0,no,southeast,3972.9247 554 | 62,male,21.4,0,no,southwest,12957.118 555 | 52,female,31.73,2,no,northwest,11187.6567 556 | 25,female,41.325,0,no,northeast,17878.90068 557 | 28,male,23.8,2,no,southwest,3847.674 558 | 46,male,33.44,1,no,northeast,8334.5896 559 | 34,male,34.21,0,no,southeast,3935.1799 560 | 35,female,34.105,3,yes,northwest,39983.42595 561 | 19,male,35.53,0,no,northwest,1646.4297 562 | 46,female,19.95,2,no,northwest,9193.8385 563 | 54,female,32.68,0,no,northeast,10923.9332 564 | 27,male,30.5,0,no,southwest,2494.022 565 | 50,male,44.77,1,no,southeast,9058.7303 566 | 18,female,32.12,2,no,southeast,2801.2588 567 | 19,female,30.495,0,no,northwest,2128.43105 568 | 38,female,40.565,1,no,northwest,6373.55735 569 | 41,male,30.59,2,no,northwest,7256.7231 570 | 49,female,31.9,5,no,southwest,11552.904 571 | 48,male,40.565,2,yes,northwest,45702.02235 572 | 31,female,29.1,0,no,southwest,3761.292 573 | 18,female,37.29,1,no,southeast,2219.4451 574 | 30,female,43.12,2,no,southeast,4753.6368 575 | 62,female,36.86,1,no,northeast,31620.00106 576 | 57,female,34.295,2,no,northeast,13224.05705 577 | 58,female,27.17,0,no,northwest,12222.8983 578 | 22,male,26.84,0,no,southeast,1664.9996 579 | 31,female,38.095,1,yes,northeast,58571.07448 580 | 52,male,30.2,1,no,southwest,9724.53 581 | 25,female,23.465,0,no,northeast,3206.49135 582 | 59,male,25.46,1,no,northeast,12913.9924 583 | 19,male,30.59,0,no,northwest,1639.5631 584 | 39,male,45.43,2,no,southeast,6356.2707 585 | 32,female,23.65,1,no,southeast,17626.23951 586 | 19,male,20.7,0,no,southwest,1242.816 587 | 33,female,28.27,1,no,southeast,4779.6023 588 | 21,male,20.235,3,no,northeast,3861.20965 589 | 34,female,30.21,1,yes,northwest,43943.8761 590 | 61,female,35.91,0,no,northeast,13635.6379 591 | 38,female,30.69,1,no,southeast,5976.8311 592 | 58,female,29,0,no,southwest,11842.442 593 | 47,male,19.57,1,no,northwest,8428.0693 594 | 20,male,31.13,2,no,southeast,2566.4707 595 | 21,female,21.85,1,yes,northeast,15359.1045 596 | 41,male,40.26,0,no,southeast,5709.1644 597 | 46,female,33.725,1,no,northeast,8823.98575 598 | 42,female,29.48,2,no,southeast,7640.3092 599 | 34,female,33.25,1,no,northeast,5594.8455 600 | 43,male,32.6,2,no,southwest,7441.501 601 | 52,female,37.525,2,no,northwest,33471.97189 602 | 18,female,39.16,0,no,southeast,1633.0444 603 | 51,male,31.635,0,no,northwest,9174.13565 604 | 56,female,25.3,0,no,southwest,11070.535 605 | 64,female,39.05,3,no,southeast,16085.1275 606 | 19,female,28.31,0,yes,northwest,17468.9839 607 | 51,female,34.1,0,no,southeast,9283.562 608 | 27,female,25.175,0,no,northeast,3558.62025 609 | 59,female,23.655,0,yes,northwest,25678.77845 610 | 28,male,26.98,2,no,northeast,4435.0942 611 | 30,male,37.8,2,yes,southwest,39241.442 612 | 47,female,29.37,1,no,southeast,8547.6913 613 | 38,female,34.8,2,no,southwest,6571.544 614 | 18,female,33.155,0,no,northeast,2207.69745 615 | 34,female,19,3,no,northeast,6753.038 616 | 20,female,33,0,no,southeast,1880.07 617 | 47,female,36.63,1,yes,southeast,42969.8527 618 | 56,female,28.595,0,no,northeast,11658.11505 619 | 49,male,25.6,2,yes,southwest,23306.547 620 | 19,female,33.11,0,yes,southeast,34439.8559 621 | 55,female,37.1,0,no,southwest,10713.644 622 | 30,male,31.4,1,no,southwest,3659.346 623 | 37,male,34.1,4,yes,southwest,40182.246 624 | 49,female,21.3,1,no,southwest,9182.17 625 | 18,male,33.535,0,yes,northeast,34617.84065 626 | 59,male,28.785,0,no,northwest,12129.61415 627 | 29,female,26.03,0,no,northwest,3736.4647 628 | 36,male,28.88,3,no,northeast,6748.5912 629 | 33,male,42.46,1,no,southeast,11326.71487 630 | 58,male,38,0,no,southwest,11365.952 631 | 44,female,38.95,0,yes,northwest,42983.4585 632 | 53,male,36.1,1,no,southwest,10085.846 633 | 24,male,29.3,0,no,southwest,1977.815 634 | 29,female,35.53,0,no,southeast,3366.6697 635 | 40,male,22.705,2,no,northeast,7173.35995 636 | 51,male,39.7,1,no,southwest,9391.346 637 | 64,male,38.19,0,no,northeast,14410.9321 638 | 19,female,24.51,1,no,northwest,2709.1119 639 | 35,female,38.095,2,no,northeast,24915.04626 640 | 39,male,26.41,0,yes,northeast,20149.3229 641 | 56,male,33.66,4,no,southeast,12949.1554 642 | 33,male,42.4,5,no,southwest,6666.243 643 | 42,male,28.31,3,yes,northwest,32787.45859 644 | 61,male,33.915,0,no,northeast,13143.86485 645 | 23,female,34.96,3,no,northwest,4466.6214 646 | 43,male,35.31,2,no,southeast,18806.14547 647 | 48,male,30.78,3,no,northeast,10141.1362 648 | 39,male,26.22,1,no,northwest,6123.5688 649 | 40,female,23.37,3,no,northeast,8252.2843 650 | 18,male,28.5,0,no,northeast,1712.227 651 | 58,female,32.965,0,no,northeast,12430.95335 652 | 49,female,42.68,2,no,southeast,9800.8882 653 | 53,female,39.6,1,no,southeast,10579.711 654 | 48,female,31.13,0,no,southeast,8280.6227 655 | 45,female,36.3,2,no,southeast,8527.532 656 | 59,female,35.2,0,no,southeast,12244.531 657 | 52,female,25.3,2,yes,southeast,24667.419 658 | 26,female,42.4,1,no,southwest,3410.324 659 | 27,male,33.155,2,no,northwest,4058.71245 660 | 48,female,35.91,1,no,northeast,26392.26029 661 | 57,female,28.785,4,no,northeast,14394.39815 662 | 37,male,46.53,3,no,southeast,6435.6237 663 | 57,female,23.98,1,no,southeast,22192.43711 664 | 32,female,31.54,1,no,northeast,5148.5526 665 | 18,male,33.66,0,no,southeast,1136.3994 666 | 64,female,22.99,0,yes,southeast,27037.9141 667 | 43,male,38.06,2,yes,southeast,42560.4304 668 | 49,male,28.7,1,no,southwest,8703.456 669 | 40,female,32.775,2,yes,northwest,40003.33225 670 | 62,male,32.015,0,yes,northeast,45710.20785 671 | 40,female,29.81,1,no,southeast,6500.2359 672 | 30,male,31.57,3,no,southeast,4837.5823 673 | 29,female,31.16,0,no,northeast,3943.5954 674 | 36,male,29.7,0,no,southeast,4399.731 675 | 41,female,31.02,0,no,southeast,6185.3208 676 | 44,female,43.89,2,yes,southeast,46200.9851 677 | 45,male,21.375,0,no,northwest,7222.78625 678 | 55,female,40.81,3,no,southeast,12485.8009 679 | 60,male,31.35,3,yes,northwest,46130.5265 680 | 56,male,36.1,3,no,southwest,12363.547 681 | 49,female,23.18,2,no,northwest,10156.7832 682 | 21,female,17.4,1,no,southwest,2585.269 683 | 19,male,20.3,0,no,southwest,1242.26 684 | 39,male,35.3,2,yes,southwest,40103.89 685 | 53,male,24.32,0,no,northwest,9863.4718 686 | 33,female,18.5,1,no,southwest,4766.022 687 | 53,male,26.41,2,no,northeast,11244.3769 688 | 42,male,26.125,2,no,northeast,7729.64575 689 | 40,male,41.69,0,no,southeast,5438.7491 690 | 47,female,24.1,1,no,southwest,26236.57997 691 | 27,male,31.13,1,yes,southeast,34806.4677 692 | 21,male,27.36,0,no,northeast,2104.1134 693 | 47,male,36.2,1,no,southwest,8068.185 694 | 20,male,32.395,1,no,northwest,2362.22905 695 | 24,male,23.655,0,no,northwest,2352.96845 696 | 27,female,34.8,1,no,southwest,3577.999 697 | 26,female,40.185,0,no,northwest,3201.24515 698 | 53,female,32.3,2,no,northeast,29186.48236 699 | 41,male,35.75,1,yes,southeast,40273.6455 700 | 56,male,33.725,0,no,northwest,10976.24575 701 | 23,female,39.27,2,no,southeast,3500.6123 702 | 21,female,34.87,0,no,southeast,2020.5523 703 | 50,female,44.745,0,no,northeast,9541.69555 704 | 53,male,41.47,0,no,southeast,9504.3103 705 | 34,female,26.41,1,no,northwest,5385.3379 706 | 47,female,29.545,1,no,northwest,8930.93455 707 | 33,female,32.9,2,no,southwest,5375.038 708 | 51,female,38.06,0,yes,southeast,44400.4064 709 | 49,male,28.69,3,no,northwest,10264.4421 710 | 31,female,30.495,3,no,northeast,6113.23105 711 | 36,female,27.74,0,no,northeast,5469.0066 712 | 18,male,35.2,1,no,southeast,1727.54 713 | 50,female,23.54,2,no,southeast,10107.2206 714 | 43,female,30.685,2,no,northwest,8310.83915 715 | 20,male,40.47,0,no,northeast,1984.4533 716 | 24,female,22.6,0,no,southwest,2457.502 717 | 60,male,28.9,0,no,southwest,12146.971 718 | 49,female,22.61,1,no,northwest,9566.9909 719 | 60,male,24.32,1,no,northwest,13112.6048 720 | 51,female,36.67,2,no,northwest,10848.1343 721 | 58,female,33.44,0,no,northwest,12231.6136 722 | 51,female,40.66,0,no,northeast,9875.6804 723 | 53,male,36.6,3,no,southwest,11264.541 724 | 62,male,37.4,0,no,southwest,12979.358 725 | 19,male,35.4,0,no,southwest,1263.249 726 | 50,female,27.075,1,no,northeast,10106.13425 727 | 30,female,39.05,3,yes,southeast,40932.4295 728 | 41,male,28.405,1,no,northwest,6664.68595 729 | 29,female,21.755,1,yes,northeast,16657.71745 730 | 18,female,40.28,0,no,northeast,2217.6012 731 | 41,female,36.08,1,no,southeast,6781.3542 732 | 35,male,24.42,3,yes,southeast,19361.9988 733 | 53,male,21.4,1,no,southwest,10065.413 734 | 24,female,30.1,3,no,southwest,4234.927 735 | 48,female,27.265,1,no,northeast,9447.25035 736 | 59,female,32.1,3,no,southwest,14007.222 737 | 49,female,34.77,1,no,northwest,9583.8933 738 | 37,female,38.39,0,yes,southeast,40419.0191 739 | 26,male,23.7,2,no,southwest,3484.331 740 | 23,male,31.73,3,yes,northeast,36189.1017 741 | 29,male,35.5,2,yes,southwest,44585.45587 742 | 45,male,24.035,2,no,northeast,8604.48365 743 | 27,male,29.15,0,yes,southeast,18246.4955 744 | 53,male,34.105,0,yes,northeast,43254.41795 745 | 31,female,26.62,0,no,southeast,3757.8448 746 | 50,male,26.41,0,no,northwest,8827.2099 747 | 50,female,30.115,1,no,northwest,9910.35985 748 | 34,male,27,2,no,southwest,11737.84884 749 | 19,male,21.755,0,no,northwest,1627.28245 750 | 47,female,36,1,no,southwest,8556.907 751 | 28,male,30.875,0,no,northwest,3062.50825 752 | 37,female,26.4,0,yes,southeast,19539.243 753 | 21,male,28.975,0,no,northwest,1906.35825 754 | 64,male,37.905,0,no,northwest,14210.53595 755 | 58,female,22.77,0,no,southeast,11833.7823 756 | 24,male,33.63,4,no,northeast,17128.42608 757 | 31,male,27.645,2,no,northeast,5031.26955 758 | 39,female,22.8,3,no,northeast,7985.815 759 | 47,female,27.83,0,yes,southeast,23065.4207 760 | 30,male,37.43,3,no,northeast,5428.7277 761 | 18,male,38.17,0,yes,southeast,36307.7983 762 | 22,female,34.58,2,no,northeast,3925.7582 763 | 23,male,35.2,1,no,southwest,2416.955 764 | 33,male,27.1,1,yes,southwest,19040.876 765 | 27,male,26.03,0,no,northeast,3070.8087 766 | 45,female,25.175,2,no,northeast,9095.06825 767 | 57,female,31.825,0,no,northwest,11842.62375 768 | 47,male,32.3,1,no,southwest,8062.764 769 | 42,female,29,1,no,southwest,7050.642 770 | 64,female,39.7,0,no,southwest,14319.031 771 | 38,female,19.475,2,no,northwest,6933.24225 772 | 61,male,36.1,3,no,southwest,27941.28758 773 | 53,female,26.7,2,no,southwest,11150.78 774 | 44,female,36.48,0,no,northeast,12797.20962 775 | 19,female,28.88,0,yes,northwest,17748.5062 776 | 41,male,34.2,2,no,northwest,7261.741 777 | 51,male,33.33,3,no,southeast,10560.4917 778 | 40,male,32.3,2,no,northwest,6986.697 779 | 45,male,39.805,0,no,northeast,7448.40395 780 | 35,male,34.32,3,no,southeast,5934.3798 781 | 53,male,28.88,0,no,northwest,9869.8102 782 | 30,male,24.4,3,yes,southwest,18259.216 783 | 18,male,41.14,0,no,southeast,1146.7966 784 | 51,male,35.97,1,no,southeast,9386.1613 785 | 50,female,27.6,1,yes,southwest,24520.264 786 | 31,female,29.26,1,no,southeast,4350.5144 787 | 35,female,27.7,3,no,southwest,6414.178 788 | 60,male,36.955,0,no,northeast,12741.16745 789 | 21,male,36.86,0,no,northwest,1917.3184 790 | 29,male,22.515,3,no,northeast,5209.57885 791 | 62,female,29.92,0,no,southeast,13457.9608 792 | 39,female,41.8,0,no,southeast,5662.225 793 | 19,male,27.6,0,no,southwest,1252.407 794 | 22,female,23.18,0,no,northeast,2731.9122 795 | 53,male,20.9,0,yes,southeast,21195.818 796 | 39,female,31.92,2,no,northwest,7209.4918 797 | 27,male,28.5,0,yes,northwest,18310.742 798 | 30,male,44.22,2,no,southeast,4266.1658 799 | 30,female,22.895,1,no,northeast,4719.52405 800 | 58,female,33.1,0,no,southwest,11848.141 801 | 33,male,24.795,0,yes,northeast,17904.52705 802 | 42,female,26.18,1,no,southeast,7046.7222 803 | 64,female,35.97,0,no,southeast,14313.8463 804 | 21,male,22.3,1,no,southwest,2103.08 805 | 18,female,42.24,0,yes,southeast,38792.6856 806 | 23,male,26.51,0,no,southeast,1815.8759 807 | 45,female,35.815,0,no,northwest,7731.85785 808 | 40,female,41.42,1,no,northwest,28476.73499 809 | 19,female,36.575,0,no,northwest,2136.88225 810 | 18,male,30.14,0,no,southeast,1131.5066 811 | 25,male,25.84,1,no,northeast,3309.7926 812 | 46,female,30.8,3,no,southwest,9414.92 813 | 33,female,42.94,3,no,northwest,6360.9936 814 | 54,male,21.01,2,no,southeast,11013.7119 815 | 28,male,22.515,2,no,northeast,4428.88785 816 | 36,male,34.43,2,no,southeast,5584.3057 817 | 20,female,31.46,0,no,southeast,1877.9294 818 | 24,female,24.225,0,no,northwest,2842.76075 819 | 23,male,37.1,3,no,southwest,3597.596 820 | 47,female,26.125,1,yes,northeast,23401.30575 821 | 33,female,35.53,0,yes,northwest,55135.40209 822 | 45,male,33.7,1,no,southwest,7445.918 823 | 26,male,17.67,0,no,northwest,2680.9493 824 | 18,female,31.13,0,no,southeast,1621.8827 825 | 44,female,29.81,2,no,southeast,8219.2039 826 | 60,male,24.32,0,no,northwest,12523.6048 827 | 64,female,31.825,2,no,northeast,16069.08475 828 | 56,male,31.79,2,yes,southeast,43813.8661 829 | 36,male,28.025,1,yes,northeast,20773.62775 830 | 41,male,30.78,3,yes,northeast,39597.4072 831 | 39,male,21.85,1,no,northwest,6117.4945 832 | 63,male,33.1,0,no,southwest,13393.756 833 | 36,female,25.84,0,no,northwest,5266.3656 834 | 28,female,23.845,2,no,northwest,4719.73655 835 | 58,male,34.39,0,no,northwest,11743.9341 836 | 36,male,33.82,1,no,northwest,5377.4578 837 | 42,male,35.97,2,no,southeast,7160.3303 838 | 36,male,31.5,0,no,southwest,4402.233 839 | 56,female,28.31,0,no,northeast,11657.7189 840 | 35,female,23.465,2,no,northeast,6402.29135 841 | 59,female,31.35,0,no,northwest,12622.1795 842 | 21,male,31.1,0,no,southwest,1526.312 843 | 59,male,24.7,0,no,northeast,12323.936 844 | 23,female,32.78,2,yes,southeast,36021.0112 845 | 57,female,29.81,0,yes,southeast,27533.9129 846 | 53,male,30.495,0,no,northeast,10072.05505 847 | 60,female,32.45,0,yes,southeast,45008.9555 848 | 51,female,34.2,1,no,southwest,9872.701 849 | 23,male,50.38,1,no,southeast,2438.0552 850 | 27,female,24.1,0,no,southwest,2974.126 851 | 55,male,32.775,0,no,northwest,10601.63225 852 | 37,female,30.78,0,yes,northeast,37270.1512 853 | 61,male,32.3,2,no,northwest,14119.62 854 | 46,female,35.53,0,yes,northeast,42111.6647 855 | 53,female,23.75,2,no,northeast,11729.6795 856 | 49,female,23.845,3,yes,northeast,24106.91255 857 | 20,female,29.6,0,no,southwest,1875.344 858 | 48,female,33.11,0,yes,southeast,40974.1649 859 | 25,male,24.13,0,yes,northwest,15817.9857 860 | 25,female,32.23,1,no,southeast,18218.16139 861 | 57,male,28.1,0,no,southwest,10965.446 862 | 37,female,47.6,2,yes,southwest,46113.511 863 | 38,female,28,3,no,southwest,7151.092 864 | 55,female,33.535,2,no,northwest,12269.68865 865 | 36,female,19.855,0,no,northeast,5458.04645 866 | 51,male,25.4,0,no,southwest,8782.469 867 | 40,male,29.9,2,no,southwest,6600.361 868 | 18,male,37.29,0,no,southeast,1141.4451 869 | 57,male,43.7,1,no,southwest,11576.13 870 | 61,male,23.655,0,no,northeast,13129.60345 871 | 25,female,24.3,3,no,southwest,4391.652 872 | 50,male,36.2,0,no,southwest,8457.818 873 | 26,female,29.48,1,no,southeast,3392.3652 874 | 42,male,24.86,0,no,southeast,5966.8874 875 | 43,male,30.1,1,no,southwest,6849.026 876 | 44,male,21.85,3,no,northeast,8891.1395 877 | 23,female,28.12,0,no,northwest,2690.1138 878 | 49,female,27.1,1,no,southwest,26140.3603 879 | 33,male,33.44,5,no,southeast,6653.7886 880 | 41,male,28.8,1,no,southwest,6282.235 881 | 37,female,29.5,2,no,southwest,6311.952 882 | 22,male,34.8,3,no,southwest,3443.064 883 | 23,male,27.36,1,no,northwest,2789.0574 884 | 21,female,22.135,0,no,northeast,2585.85065 885 | 51,female,37.05,3,yes,northeast,46255.1125 886 | 25,male,26.695,4,no,northwest,4877.98105 887 | 32,male,28.93,1,yes,southeast,19719.6947 888 | 57,male,28.975,0,yes,northeast,27218.43725 889 | 36,female,30.02,0,no,northwest,5272.1758 890 | 22,male,39.5,0,no,southwest,1682.597 891 | 57,male,33.63,1,no,northwest,11945.1327 892 | 64,female,26.885,0,yes,northwest,29330.98315 893 | 36,female,29.04,4,no,southeast,7243.8136 894 | 54,male,24.035,0,no,northeast,10422.91665 895 | 47,male,38.94,2,yes,southeast,44202.6536 896 | 62,male,32.11,0,no,northeast,13555.0049 897 | 61,female,44,0,no,southwest,13063.883 898 | 43,female,20.045,2,yes,northeast,19798.05455 899 | 19,male,25.555,1,no,northwest,2221.56445 900 | 18,female,40.26,0,no,southeast,1634.5734 901 | 19,female,22.515,0,no,northwest,2117.33885 902 | 49,male,22.515,0,no,northeast,8688.85885 903 | 60,male,40.92,0,yes,southeast,48673.5588 904 | 26,male,27.265,3,no,northeast,4661.28635 905 | 49,male,36.85,0,no,southeast,8125.7845 906 | 60,female,35.1,0,no,southwest,12644.589 907 | 26,female,29.355,2,no,northeast,4564.19145 908 | 27,male,32.585,3,no,northeast,4846.92015 909 | 44,female,32.34,1,no,southeast,7633.7206 910 | 63,male,39.8,3,no,southwest,15170.069 911 | 32,female,24.6,0,yes,southwest,17496.306 912 | 22,male,28.31,1,no,northwest,2639.0429 913 | 18,male,31.73,0,yes,northeast,33732.6867 914 | 59,female,26.695,3,no,northwest,14382.70905 915 | 44,female,27.5,1,no,southwest,7626.993 916 | 33,male,24.605,2,no,northwest,5257.50795 917 | 24,female,33.99,0,no,southeast,2473.3341 918 | 43,female,26.885,0,yes,northwest,21774.32215 919 | 45,male,22.895,0,yes,northeast,35069.37452 920 | 61,female,28.2,0,no,southwest,13041.921 921 | 35,female,34.21,1,no,southeast,5245.2269 922 | 62,female,25,0,no,southwest,13451.122 923 | 62,female,33.2,0,no,southwest,13462.52 924 | 38,male,31,1,no,southwest,5488.262 925 | 34,male,35.815,0,no,northwest,4320.41085 926 | 43,male,23.2,0,no,southwest,6250.435 927 | 50,male,32.11,2,no,northeast,25333.33284 928 | 19,female,23.4,2,no,southwest,2913.569 929 | 57,female,20.1,1,no,southwest,12032.326 930 | 62,female,39.16,0,no,southeast,13470.8044 931 | 41,male,34.21,1,no,southeast,6289.7549 932 | 26,male,46.53,1,no,southeast,2927.0647 933 | 39,female,32.5,1,no,southwest,6238.298 934 | 46,male,25.8,5,no,southwest,10096.97 935 | 45,female,35.3,0,no,southwest,7348.142 936 | 32,male,37.18,2,no,southeast,4673.3922 937 | 59,female,27.5,0,no,southwest,12233.828 938 | 44,male,29.735,2,no,northeast,32108.66282 939 | 39,female,24.225,5,no,northwest,8965.79575 940 | 18,male,26.18,2,no,southeast,2304.0022 941 | 53,male,29.48,0,no,southeast,9487.6442 942 | 18,male,23.21,0,no,southeast,1121.8739 943 | 50,female,46.09,1,no,southeast,9549.5651 944 | 18,female,40.185,0,no,northeast,2217.46915 945 | 19,male,22.61,0,no,northwest,1628.4709 946 | 62,male,39.93,0,no,southeast,12982.8747 947 | 56,female,35.8,1,no,southwest,11674.13 948 | 42,male,35.8,2,no,southwest,7160.094 949 | 37,male,34.2,1,yes,northeast,39047.285 950 | 42,male,31.255,0,no,northwest,6358.77645 951 | 25,male,29.7,3,yes,southwest,19933.458 952 | 57,male,18.335,0,no,northeast,11534.87265 953 | 51,male,42.9,2,yes,southeast,47462.894 954 | 30,female,28.405,1,no,northwest,4527.18295 955 | 44,male,30.2,2,yes,southwest,38998.546 956 | 34,male,27.835,1,yes,northwest,20009.63365 957 | 31,male,39.49,1,no,southeast,3875.7341 958 | 54,male,30.8,1,yes,southeast,41999.52 959 | 24,male,26.79,1,no,northwest,12609.88702 960 | 43,male,34.96,1,yes,northeast,41034.2214 961 | 48,male,36.67,1,no,northwest,28468.91901 962 | 19,female,39.615,1,no,northwest,2730.10785 963 | 29,female,25.9,0,no,southwest,3353.284 964 | 63,female,35.2,1,no,southeast,14474.675 965 | 46,male,24.795,3,no,northeast,9500.57305 966 | 52,male,36.765,2,no,northwest,26467.09737 967 | 35,male,27.1,1,no,southwest,4746.344 968 | 51,male,24.795,2,yes,northwest,23967.38305 969 | 44,male,25.365,1,no,northwest,7518.02535 970 | 21,male,25.745,2,no,northeast,3279.86855 971 | 39,female,34.32,5,no,southeast,8596.8278 972 | 50,female,28.16,3,no,southeast,10702.6424 973 | 34,female,23.56,0,no,northeast,4992.3764 974 | 22,female,20.235,0,no,northwest,2527.81865 975 | 19,female,40.5,0,no,southwest,1759.338 976 | 26,male,35.42,0,no,southeast,2322.6218 977 | 29,male,22.895,0,yes,northeast,16138.76205 978 | 48,male,40.15,0,no,southeast,7804.1605 979 | 26,male,29.15,1,no,southeast,2902.9065 980 | 45,female,39.995,3,no,northeast,9704.66805 981 | 36,female,29.92,0,no,southeast,4889.0368 982 | 54,male,25.46,1,no,northeast,25517.11363 983 | 34,male,21.375,0,no,northeast,4500.33925 984 | 31,male,25.9,3,yes,southwest,19199.944 985 | 27,female,30.59,1,no,northeast,16796.41194 986 | 20,male,30.115,5,no,northeast,4915.05985 987 | 44,female,25.8,1,no,southwest,7624.63 988 | 43,male,30.115,3,no,northwest,8410.04685 989 | 45,female,27.645,1,no,northwest,28340.18885 990 | 34,male,34.675,0,no,northeast,4518.82625 991 | 24,female,20.52,0,yes,northeast,14571.8908 992 | 26,female,19.8,1,no,southwest,3378.91 993 | 38,female,27.835,2,no,northeast,7144.86265 994 | 50,female,31.6,2,no,southwest,10118.424 995 | 38,male,28.27,1,no,southeast,5484.4673 996 | 27,female,20.045,3,yes,northwest,16420.49455 997 | 39,female,23.275,3,no,northeast,7986.47525 998 | 39,female,34.1,3,no,southwest,7418.522 999 | 63,female,36.85,0,no,southeast,13887.9685 1000 | 33,female,36.29,3,no,northeast,6551.7501 1001 | 36,female,26.885,0,no,northwest,5267.81815 1002 | 30,male,22.99,2,yes,northwest,17361.7661 1003 | 24,male,32.7,0,yes,southwest,34472.841 1004 | 24,male,25.8,0,no,southwest,1972.95 1005 | 48,male,29.6,0,no,southwest,21232.18226 1006 | 47,male,19.19,1,no,northeast,8627.5411 1007 | 29,male,31.73,2,no,northwest,4433.3877 1008 | 28,male,29.26,2,no,northeast,4438.2634 1009 | 47,male,28.215,3,yes,northwest,24915.22085 1010 | 25,male,24.985,2,no,northeast,23241.47453 1011 | 51,male,27.74,1,no,northeast,9957.7216 1012 | 48,female,22.8,0,no,southwest,8269.044 1013 | 43,male,20.13,2,yes,southeast,18767.7377 1014 | 61,female,33.33,4,no,southeast,36580.28216 1015 | 48,male,32.3,1,no,northwest,8765.249 1016 | 38,female,27.6,0,no,southwest,5383.536 1017 | 59,male,25.46,0,no,northwest,12124.9924 1018 | 19,female,24.605,1,no,northwest,2709.24395 1019 | 26,female,34.2,2,no,southwest,3987.926 1020 | 54,female,35.815,3,no,northwest,12495.29085 1021 | 21,female,32.68,2,no,northwest,26018.95052 1022 | 51,male,37,0,no,southwest,8798.593 1023 | 22,female,31.02,3,yes,southeast,35595.5898 1024 | 47,male,36.08,1,yes,southeast,42211.1382 1025 | 18,male,23.32,1,no,southeast,1711.0268 1026 | 47,female,45.32,1,no,southeast,8569.8618 1027 | 21,female,34.6,0,no,southwest,2020.177 1028 | 19,male,26.03,1,yes,northwest,16450.8947 1029 | 23,male,18.715,0,no,northwest,21595.38229 1030 | 54,male,31.6,0,no,southwest,9850.432 1031 | 37,female,17.29,2,no,northeast,6877.9801 1032 | 46,female,23.655,1,yes,northwest,21677.28345 1033 | 55,female,35.2,0,yes,southeast,44423.803 1034 | 30,female,27.93,0,no,northeast,4137.5227 1035 | 18,male,21.565,0,yes,northeast,13747.87235 1036 | 61,male,38.38,0,no,northwest,12950.0712 1037 | 54,female,23,3,no,southwest,12094.478 1038 | 22,male,37.07,2,yes,southeast,37484.4493 1039 | 45,female,30.495,1,yes,northwest,39725.51805 1040 | 22,male,28.88,0,no,northeast,2250.8352 1041 | 19,male,27.265,2,no,northwest,22493.65964 1042 | 35,female,28.025,0,yes,northwest,20234.85475 1043 | 18,male,23.085,0,no,northeast,1704.70015 1044 | 20,male,30.685,0,yes,northeast,33475.81715 1045 | 28,female,25.8,0,no,southwest,3161.454 1046 | 55,male,35.245,1,no,northeast,11394.06555 1047 | 43,female,24.7,2,yes,northwest,21880.82 1048 | 43,female,25.08,0,no,northeast,7325.0482 1049 | 22,male,52.58,1,yes,southeast,44501.3982 1050 | 25,female,22.515,1,no,northwest,3594.17085 1051 | 49,male,30.9,0,yes,southwest,39727.614 1052 | 44,female,36.955,1,no,northwest,8023.13545 1053 | 64,male,26.41,0,no,northeast,14394.5579 1054 | 49,male,29.83,1,no,northeast,9288.0267 1055 | 47,male,29.8,3,yes,southwest,25309.489 1056 | 27,female,21.47,0,no,northwest,3353.4703 1057 | 55,male,27.645,0,no,northwest,10594.50155 1058 | 48,female,28.9,0,no,southwest,8277.523 1059 | 45,female,31.79,0,no,southeast,17929.30337 1060 | 24,female,39.49,0,no,southeast,2480.9791 1061 | 32,male,33.82,1,no,northwest,4462.7218 1062 | 24,male,32.01,0,no,southeast,1981.5819 1063 | 57,male,27.94,1,no,southeast,11554.2236 1064 | 59,male,41.14,1,yes,southeast,48970.2476 1065 | 36,male,28.595,3,no,northwest,6548.19505 1066 | 29,female,25.6,4,no,southwest,5708.867 1067 | 42,female,25.3,1,no,southwest,7045.499 1068 | 48,male,37.29,2,no,southeast,8978.1851 1069 | 39,male,42.655,0,no,northeast,5757.41345 1070 | 63,male,21.66,1,no,northwest,14349.8544 1071 | 54,female,31.9,1,no,southeast,10928.849 1072 | 37,male,37.07,1,yes,southeast,39871.7043 1073 | 63,male,31.445,0,no,northeast,13974.45555 1074 | 21,male,31.255,0,no,northwest,1909.52745 1075 | 54,female,28.88,2,no,northeast,12096.6512 1076 | 60,female,18.335,0,no,northeast,13204.28565 1077 | 32,female,29.59,1,no,southeast,4562.8421 1078 | 47,female,32,1,no,southwest,8551.347 1079 | 21,male,26.03,0,no,northeast,2102.2647 1080 | 28,male,31.68,0,yes,southeast,34672.1472 1081 | 63,male,33.66,3,no,southeast,15161.5344 1082 | 18,male,21.78,2,no,southeast,11884.04858 1083 | 32,male,27.835,1,no,northwest,4454.40265 1084 | 38,male,19.95,1,no,northwest,5855.9025 1085 | 32,male,31.5,1,no,southwest,4076.497 1086 | 62,female,30.495,2,no,northwest,15019.76005 1087 | 39,female,18.3,5,yes,southwest,19023.26 1088 | 55,male,28.975,0,no,northeast,10796.35025 1089 | 57,male,31.54,0,no,northwest,11353.2276 1090 | 52,male,47.74,1,no,southeast,9748.9106 1091 | 56,male,22.1,0,no,southwest,10577.087 1092 | 47,male,36.19,0,yes,southeast,41676.0811 1093 | 55,female,29.83,0,no,northeast,11286.5387 1094 | 23,male,32.7,3,no,southwest,3591.48 1095 | 22,female,30.4,0,yes,northwest,33907.548 1096 | 50,female,33.7,4,no,southwest,11299.343 1097 | 18,female,31.35,4,no,northeast,4561.1885 1098 | 51,female,34.96,2,yes,northeast,44641.1974 1099 | 22,male,33.77,0,no,southeast,1674.6323 1100 | 52,female,30.875,0,no,northeast,23045.56616 1101 | 25,female,33.99,1,no,southeast,3227.1211 1102 | 33,female,19.095,2,yes,northeast,16776.30405 1103 | 53,male,28.6,3,no,southwest,11253.421 1104 | 29,male,38.94,1,no,southeast,3471.4096 1105 | 58,male,36.08,0,no,southeast,11363.2832 1106 | 37,male,29.8,0,no,southwest,20420.60465 1107 | 54,female,31.24,0,no,southeast,10338.9316 1108 | 49,female,29.925,0,no,northwest,8988.15875 1109 | 50,female,26.22,2,no,northwest,10493.9458 1110 | 26,male,30,1,no,southwest,2904.088 1111 | 45,male,20.35,3,no,southeast,8605.3615 1112 | 54,female,32.3,1,no,northeast,11512.405 1113 | 38,male,38.39,3,yes,southeast,41949.2441 1114 | 48,female,25.85,3,yes,southeast,24180.9335 1115 | 28,female,26.315,3,no,northwest,5312.16985 1116 | 23,male,24.51,0,no,northeast,2396.0959 1117 | 55,male,32.67,1,no,southeast,10807.4863 1118 | 41,male,29.64,5,no,northeast,9222.4026 1119 | 25,male,33.33,2,yes,southeast,36124.5737 1120 | 33,male,35.75,1,yes,southeast,38282.7495 1121 | 30,female,19.95,3,no,northwest,5693.4305 1122 | 23,female,31.4,0,yes,southwest,34166.273 1123 | 46,male,38.17,2,no,southeast,8347.1643 1124 | 53,female,36.86,3,yes,northwest,46661.4424 1125 | 27,female,32.395,1,no,northeast,18903.49141 1126 | 23,female,42.75,1,yes,northeast,40904.1995 1127 | 63,female,25.08,0,no,northwest,14254.6082 1128 | 55,male,29.9,0,no,southwest,10214.636 1129 | 35,female,35.86,2,no,southeast,5836.5204 1130 | 34,male,32.8,1,no,southwest,14358.36437 1131 | 19,female,18.6,0,no,southwest,1728.897 1132 | 39,female,23.87,5,no,southeast,8582.3023 1133 | 27,male,45.9,2,no,southwest,3693.428 1134 | 57,male,40.28,0,no,northeast,20709.02034 1135 | 52,female,18.335,0,no,northwest,9991.03765 1136 | 28,male,33.82,0,no,northwest,19673.33573 1137 | 50,female,28.12,3,no,northwest,11085.5868 1138 | 44,female,25,1,no,southwest,7623.518 1139 | 26,female,22.23,0,no,northwest,3176.2877 1140 | 33,male,30.25,0,no,southeast,3704.3545 1141 | 19,female,32.49,0,yes,northwest,36898.73308 1142 | 50,male,37.07,1,no,southeast,9048.0273 1143 | 41,female,32.6,3,no,southwest,7954.517 1144 | 52,female,24.86,0,no,southeast,27117.99378 1145 | 39,male,32.34,2,no,southeast,6338.0756 1146 | 50,male,32.3,2,no,southwest,9630.397 1147 | 52,male,32.775,3,no,northwest,11289.10925 1148 | 60,male,32.8,0,yes,southwest,52590.82939 1149 | 20,female,31.92,0,no,northwest,2261.5688 1150 | 55,male,21.5,1,no,southwest,10791.96 1151 | 42,male,34.1,0,no,southwest,5979.731 1152 | 18,female,30.305,0,no,northeast,2203.73595 1153 | 58,female,36.48,0,no,northwest,12235.8392 1154 | 43,female,32.56,3,yes,southeast,40941.2854 1155 | 35,female,35.815,1,no,northwest,5630.45785 1156 | 48,female,27.93,4,no,northwest,11015.1747 1157 | 36,female,22.135,3,no,northeast,7228.21565 1158 | 19,male,44.88,0,yes,southeast,39722.7462 1159 | 23,female,23.18,2,no,northwest,14426.07385 1160 | 20,female,30.59,0,no,northeast,2459.7201 1161 | 32,female,41.1,0,no,southwest,3989.841 1162 | 43,female,34.58,1,no,northwest,7727.2532 1163 | 34,male,42.13,2,no,southeast,5124.1887 1164 | 30,male,38.83,1,no,southeast,18963.17192 1165 | 18,female,28.215,0,no,northeast,2200.83085 1166 | 41,female,28.31,1,no,northwest,7153.5539 1167 | 35,female,26.125,0,no,northeast,5227.98875 1168 | 57,male,40.37,0,no,southeast,10982.5013 1169 | 29,female,24.6,2,no,southwest,4529.477 1170 | 32,male,35.2,2,no,southwest,4670.64 1171 | 37,female,34.105,1,no,northwest,6112.35295 1172 | 18,male,27.36,1,yes,northeast,17178.6824 1173 | 43,female,26.7,2,yes,southwest,22478.6 1174 | 56,female,41.91,0,no,southeast,11093.6229 1175 | 38,male,29.26,2,no,northwest,6457.8434 1176 | 29,male,32.11,2,no,northwest,4433.9159 1177 | 22,female,27.1,0,no,southwest,2154.361 1178 | 52,female,24.13,1,yes,northwest,23887.6627 1179 | 40,female,27.4,1,no,southwest,6496.886 1180 | 23,female,34.865,0,no,northeast,2899.48935 1181 | 31,male,29.81,0,yes,southeast,19350.3689 1182 | 42,female,41.325,1,no,northeast,7650.77375 1183 | 24,female,29.925,0,no,northwest,2850.68375 1184 | 25,female,30.3,0,no,southwest,2632.992 1185 | 48,female,27.36,1,no,northeast,9447.3824 1186 | 23,female,28.49,1,yes,southeast,18328.2381 1187 | 45,male,23.56,2,no,northeast,8603.8234 1188 | 20,male,35.625,3,yes,northwest,37465.34375 1189 | 62,female,32.68,0,no,northwest,13844.7972 1190 | 43,female,25.27,1,yes,northeast,21771.3423 1191 | 23,female,28,0,no,southwest,13126.67745 1192 | 31,female,32.775,2,no,northwest,5327.40025 1193 | 41,female,21.755,1,no,northeast,13725.47184 1194 | 58,female,32.395,1,no,northeast,13019.16105 1195 | 48,female,36.575,0,no,northwest,8671.19125 1196 | 31,female,21.755,0,no,northwest,4134.08245 1197 | 19,female,27.93,3,no,northwest,18838.70366 1198 | 19,female,30.02,0,yes,northwest,33307.5508 1199 | 41,male,33.55,0,no,southeast,5699.8375 1200 | 40,male,29.355,1,no,northwest,6393.60345 1201 | 31,female,25.8,2,no,southwest,4934.705 1202 | 37,male,24.32,2,no,northwest,6198.7518 1203 | 46,male,40.375,2,no,northwest,8733.22925 1204 | 22,male,32.11,0,no,northwest,2055.3249 1205 | 51,male,32.3,1,no,northeast,9964.06 1206 | 18,female,27.28,3,yes,southeast,18223.4512 1207 | 35,male,17.86,1,no,northwest,5116.5004 1208 | 59,female,34.8,2,no,southwest,36910.60803 1209 | 36,male,33.4,2,yes,southwest,38415.474 1210 | 37,female,25.555,1,yes,northeast,20296.86345 1211 | 59,male,37.1,1,no,southwest,12347.172 1212 | 36,male,30.875,1,no,northwest,5373.36425 1213 | 39,male,34.1,2,no,southeast,23563.01618 1214 | 18,male,21.47,0,no,northeast,1702.4553 1215 | 52,female,33.3,2,no,southwest,10806.839 1216 | 27,female,31.255,1,no,northwest,3956.07145 1217 | 18,male,39.14,0,no,northeast,12890.05765 1218 | 40,male,25.08,0,no,southeast,5415.6612 1219 | 29,male,37.29,2,no,southeast,4058.1161 1220 | 46,female,34.6,1,yes,southwest,41661.602 1221 | 38,female,30.21,3,no,northwest,7537.1639 1222 | 30,female,21.945,1,no,northeast,4718.20355 1223 | 40,male,24.97,2,no,southeast,6593.5083 1224 | 50,male,25.3,0,no,southeast,8442.667 1225 | 20,female,24.42,0,yes,southeast,26125.67477 1226 | 41,male,23.94,1,no,northeast,6858.4796 1227 | 33,female,39.82,1,no,southeast,4795.6568 1228 | 38,male,16.815,2,no,northeast,6640.54485 1229 | 42,male,37.18,2,no,southeast,7162.0122 1230 | 56,male,34.43,0,no,southeast,10594.2257 1231 | 58,male,30.305,0,no,northeast,11938.25595 1232 | 52,male,34.485,3,yes,northwest,60021.39897 1233 | 20,female,21.8,0,yes,southwest,20167.33603 1234 | 54,female,24.605,3,no,northwest,12479.70895 1235 | 58,male,23.3,0,no,southwest,11345.519 1236 | 45,female,27.83,2,no,southeast,8515.7587 1237 | 26,male,31.065,0,no,northwest,2699.56835 1238 | 63,female,21.66,0,no,northeast,14449.8544 1239 | 58,female,28.215,0,no,northwest,12224.35085 1240 | 37,male,22.705,3,no,northeast,6985.50695 1241 | 25,female,42.13,1,no,southeast,3238.4357 1242 | 52,male,41.8,2,yes,southeast,47269.854 1243 | 64,male,36.96,2,yes,southeast,49577.6624 1244 | 22,female,21.28,3,no,northwest,4296.2712 1245 | 28,female,33.11,0,no,southeast,3171.6149 1246 | 18,male,33.33,0,no,southeast,1135.9407 1247 | 28,male,24.3,5,no,southwest,5615.369 1248 | 45,female,25.7,3,no,southwest,9101.798 1249 | 33,male,29.4,4,no,southwest,6059.173 1250 | 18,female,39.82,0,no,southeast,1633.9618 1251 | 32,male,33.63,1,yes,northeast,37607.5277 1252 | 24,male,29.83,0,yes,northeast,18648.4217 1253 | 19,male,19.8,0,no,southwest,1241.565 1254 | 20,male,27.3,0,yes,southwest,16232.847 1255 | 40,female,29.3,4,no,southwest,15828.82173 1256 | 34,female,27.72,0,no,southeast,4415.1588 1257 | 42,female,37.9,0,no,southwest,6474.013 1258 | 51,female,36.385,3,no,northwest,11436.73815 1259 | 54,female,27.645,1,no,northwest,11305.93455 1260 | 55,male,37.715,3,no,northwest,30063.58055 1261 | 52,female,23.18,0,no,northeast,10197.7722 1262 | 32,female,20.52,0,no,northeast,4544.2348 1263 | 28,male,37.1,1,no,southwest,3277.161 1264 | 41,female,28.05,1,no,southeast,6770.1925 1265 | 43,female,29.9,1,no,southwest,7337.748 1266 | 49,female,33.345,2,no,northeast,10370.91255 1267 | 64,male,23.76,0,yes,southeast,26926.5144 1268 | 55,female,30.5,0,no,southwest,10704.47 1269 | 24,male,31.065,0,yes,northeast,34254.05335 1270 | 20,female,33.3,0,no,southwest,1880.487 1271 | 45,male,27.5,3,no,southwest,8615.3 1272 | 26,male,33.915,1,no,northwest,3292.52985 1273 | 25,female,34.485,0,no,northwest,3021.80915 1274 | 43,male,25.52,5,no,southeast,14478.33015 1275 | 35,male,27.61,1,no,southeast,4747.0529 1276 | 26,male,27.06,0,yes,southeast,17043.3414 1277 | 57,male,23.7,0,no,southwest,10959.33 1278 | 22,female,30.4,0,no,northeast,2741.948 1279 | 32,female,29.735,0,no,northwest,4357.04365 1280 | 39,male,29.925,1,yes,northeast,22462.04375 1281 | 25,female,26.79,2,no,northwest,4189.1131 1282 | 48,female,33.33,0,no,southeast,8283.6807 1283 | 47,female,27.645,2,yes,northwest,24535.69855 1284 | 18,female,21.66,0,yes,northeast,14283.4594 1285 | 18,male,30.03,1,no,southeast,1720.3537 1286 | 61,male,36.3,1,yes,southwest,47403.88 1287 | 47,female,24.32,0,no,northeast,8534.6718 1288 | 28,female,17.29,0,no,northeast,3732.6251 1289 | 36,female,25.9,1,no,southwest,5472.449 1290 | 20,male,39.4,2,yes,southwest,38344.566 1291 | 44,male,34.32,1,no,southeast,7147.4728 1292 | 38,female,19.95,2,no,northeast,7133.9025 1293 | 19,male,34.9,0,yes,southwest,34828.654 1294 | 21,male,23.21,0,no,southeast,1515.3449 1295 | 46,male,25.745,3,no,northwest,9301.89355 1296 | 58,male,25.175,0,no,northeast,11931.12525 1297 | 20,male,22,1,no,southwest,1964.78 1298 | 18,male,26.125,0,no,northeast,1708.92575 1299 | 28,female,26.51,2,no,southeast,4340.4409 1300 | 33,male,27.455,2,no,northwest,5261.46945 1301 | 19,female,25.745,1,no,northwest,2710.82855 1302 | 45,male,30.36,0,yes,southeast,62592.87309 1303 | 62,male,30.875,3,yes,northwest,46718.16325 1304 | 25,female,20.8,1,no,southwest,3208.787 1305 | 43,male,27.8,0,yes,southwest,37829.7242 1306 | 42,male,24.605,2,yes,northeast,21259.37795 1307 | 24,female,27.72,0,no,southeast,2464.6188 1308 | 29,female,21.85,0,yes,northeast,16115.3045 1309 | 32,male,28.12,4,yes,northwest,21472.4788 1310 | 25,female,30.2,0,yes,southwest,33900.653 1311 | 41,male,32.2,2,no,southwest,6875.961 1312 | 42,male,26.315,1,no,northwest,6940.90985 1313 | 33,female,26.695,0,no,northwest,4571.41305 1314 | 34,male,42.9,1,no,southwest,4536.259 1315 | 19,female,34.7,2,yes,southwest,36397.576 1316 | 30,female,23.655,3,yes,northwest,18765.87545 1317 | 18,male,28.31,1,no,northeast,11272.33139 1318 | 19,female,20.6,0,no,southwest,1731.677 1319 | 18,male,53.13,0,no,southeast,1163.4627 1320 | 35,male,39.71,4,no,northeast,19496.71917 1321 | 39,female,26.315,2,no,northwest,7201.70085 1322 | 31,male,31.065,3,no,northwest,5425.02335 1323 | 62,male,26.695,0,yes,northeast,28101.33305 1324 | 62,male,38.83,0,no,southeast,12981.3457 1325 | 42,female,40.37,2,yes,southeast,43896.3763 1326 | 31,male,25.935,1,no,northwest,4239.89265 1327 | 61,male,33.535,0,no,northeast,13143.33665 1328 | 42,female,32.87,0,no,northeast,7050.0213 1329 | 51,male,30.03,1,no,southeast,9377.9047 1330 | 23,female,24.225,2,no,northeast,22395.74424 1331 | 52,male,38.6,2,no,southwest,10325.206 1332 | 57,female,25.74,2,no,southeast,12629.1656 1333 | 23,female,33.4,0,no,southwest,10795.93733 1334 | 52,female,44.7,3,no,southwest,11411.685 1335 | 50,male,30.97,3,no,northwest,10600.5483 1336 | 18,female,31.92,0,no,northeast,2205.9808 1337 | 18,female,36.85,0,no,southeast,1629.8335 1338 | 21,female,25.8,0,no,southwest,2007.945 1339 | 61,female,29.07,0,yes,northwest,29141.3603 1340 | -------------------------------------------------------------------------------- /iss-now.json: -------------------------------------------------------------------------------- 1 | {"message": "success", "iss_position": {"latitude": "41.8157", "longitude": "-138.3051"}, "timestamp": 1652700632} -------------------------------------------------------------------------------- /january.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/january.xlsx -------------------------------------------------------------------------------- /march.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/march.xlsx -------------------------------------------------------------------------------- /pandas merge.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/pandas merge.xlsx -------------------------------------------------------------------------------- /populations.csv: -------------------------------------------------------------------------------- 1 | Age Group,Year,Males,Females 2 | 0 to 4 years,1971,"938,835","897,314" 3 | ,1972,"921,965","879,950" 4 | ,1973,"916,686","871,480" 5 | ,1974,"911,727","865,968" 6 | ,1975,"908,801","862,260" 7 | ,1976,"902,201","857,116" 8 | ,1977,"902,405","858,401" 9 | ,1978,"905,661","861,724" 10 | ,1979,"913,235","867,487" 11 | ,1980,"919,129","872,638" 12 | ,1981,"924,653","878,754" 13 | ,1982,"933,739","887,275" 14 | ,1983,"943,685","895,230" 15 | ,1984,"948,816","900,118" 16 | ,1985,"948,389","899,433" 17 | ,1986,"943,666","897,446" 18 | ,1987,"951,182","905,766" 19 | ,1988,"956,597","911,798" 20 | ,1989,"970,553","924,420" 21 | ,1990,"988,944","942,343" 22 | ,1991,"1,002,210","956,232" 23 | ,1992,"1,020,551","972,865" 24 | ,1993,"1,031,613","982,054" 25 | ,1994,"1,030,173","980,281" 26 | ,1995,"1,017,574","967,307" 27 | ,1996,"1,004,433","956,161" 28 | ,1997,"983,136","933,588" 29 | ,1998,"959,260","912,765" 30 | ,1999,"936,068","892,108" 31 | ,2000,"916,180","874,519" 32 | ,2001,"898,031","856,323" 33 | ,2002,"881,975","841,317" 34 | ,2003,"873,741","831,535" 35 | ,2004,"874,686","830,344" 36 | ,2005,"877,651","830,594" 37 | ,2006,"888,125","839,384" 38 | ,2007,"900,318","853,157" 39 | ,2008,"919,548","874,004" 40 | ,2009,"938,644","892,987" 41 | ,2010,"958,928","912,977" 42 | ,2011,"973,013","926,799" 43 | ,2012,"980,985","936,353" 44 | ,2013,"985,155","939,499" 45 | ,2014,"986,082","941,623" 46 | ,2015,"986,676","942,202" 47 | ,2016,"993,580","949,211" 48 | ,2017,"994,502","947,336" 49 | ,2018,"994,268","946,215" 50 | ,2019,"990,725","942,059" 51 | ,2020,"984,057","935,770" 52 | ,2021,"965,385","917,186" 53 | 5 to 9 years,1971,"1,159,468","1,108,326" 54 | ,1972,"1,119,235","1,068,703" 55 | ,1973,"1,065,372","1,017,625" 56 | ,1974,"1,019,412","972,430" 57 | ,1975,"989,755","943,977" 58 | ,1976,"978,589","931,028" 59 | ,1977,"964,249","915,179" 60 | ,1978,"953,510","903,489" 61 | ,1979,"938,774","890,434" 62 | ,1980,"930,485","882,093" 63 | ,1981,"921,617","873,100" 64 | ,1982,"919,265","873,776" 65 | ,1983,"918,756","874,791" 66 | ,1984,"925,732","880,391" 67 | ,1985,"931,570","884,379" 68 | ,1986,"939,125","890,322" 69 | ,1987,"949,714","898,889" 70 | ,1988,"963,081","911,934" 71 | ,1989,"977,537","926,131" 72 | ,1990,"987,239","936,252" 73 | ,1991,"991,222","943,493" 74 | ,1992,"997,989","950,345" 75 | ,1993,"1,001,051","953,369" 76 | ,1994,"1,008,418","959,727" 77 | ,1995,"1,020,229","971,748" 78 | ,1996,"1,032,530","983,350" 79 | ,1997,"1,044,772","995,661" 80 | ,1998,"1,054,726","1,005,130" 81 | ,1999,"1,053,148","1,003,151" 82 | ,2000,"1,043,712","993,237" 83 | ,2001,"1,032,429","984,620" 84 | ,2002,"1,018,791","969,963" 85 | ,2003,"997,085","950,572" 86 | ,2004,"975,051","929,999" 87 | ,2005,"954,781","910,001" 88 | ,2006,"936,688","887,847" 89 | ,2007,"925,431","876,503" 90 | ,2008,"920,060","870,429" 91 | ,2009,"920,911","870,876" 92 | ,2010,"920,043","871,126" 93 | ,2011,"928,425","882,489" 94 | ,2012,"945,652","901,853" 95 | ,2013,"966,874","925,856" 96 | ,2014,"985,043","945,996" 97 | ,2015,"1,003,138","966,354" 98 | ,2016,"1,019,960","983,263" 99 | ,2017,"1,030,316","991,248" 100 | ,2018,"1,038,162","995,151" 101 | ,2019,"1,042,811","998,467" 102 | ,2020,"1,047,225","1,000,141" 103 | ,2021,"1,046,126","998,111" 104 | 10 to 14 years,1971,"1,190,275","1,139,048" 105 | ,1972,"1,201,022","1,148,118" 106 | ,1973,"1,210,738","1,157,451" 107 | ,1974,"1,213,871","1,159,938" 108 | ,1975,"1,204,861","1,150,206" 109 | ,1976,"1,172,190","1,119,525" 110 | ,1977,"1,138,873","1,086,943" 111 | ,1978,"1,090,445","1,039,331" 112 | ,1979,"1,042,532","993,009" 113 | ,1980,"1,009,002","959,634" 114 | ,1981,"991,870","942,694" 115 | ,1982,"981,179","930,293" 116 | ,1983,"970,865","919,762" 117 | ,1984,"955,286","908,206" 118 | ,1985,"942,149","898,657" 119 | ,1986,"928,219","886,817" 120 | ,1987,"931,144","888,575" 121 | ,1988,"938,076","893,317" 122 | ,1989,"951,730","904,394" 123 | ,1990,"961,743","913,191" 124 | ,1991,"975,794","926,609" 125 | ,1992,"991,139","939,534" 126 | ,1993,"1,005,051","952,918" 127 | ,1994,"1,016,851","965,529" 128 | ,1995,"1,024,939","972,711" 129 | ,1996,"1,031,500","977,825" 130 | ,1997,"1,037,515","983,098" 131 | ,1998,"1,040,112","986,474" 132 | ,1999,"1,043,607","990,952" 133 | ,2000,"1,053,098","1,002,745" 134 | ,2001,"1,065,250","1,014,489" 135 | ,2002,"1,083,427","1,031,319" 136 | ,2003,"1,096,137","1,043,013" 137 | ,2004,"1,096,803","1,045,029" 138 | ,2005,"1,086,955","1,037,575" 139 | ,2006,"1,071,000","1,025,117" 140 | ,2007,"1,058,155","1,007,756" 141 | ,2008,"1,042,424","989,874" 142 | ,2009,"1,025,166","971,570" 143 | ,2010,"1,006,314","952,785" 144 | ,2011,"986,954","931,141" 145 | ,2012,"974,448","921,003" 146 | ,2013,"969,050","917,618" 147 | ,2014,"970,398","922,866" 148 | ,2015,"968,904","926,559" 149 | ,2016,"978,544","941,266" 150 | ,2017,"992,477","956,204" 151 | ,2018,"1,014,167","978,222" 152 | ,2019,"1,035,393","997,915" 153 | ,2020,"1,056,546","1,017,994" 154 | ,2021,"1,065,941","1,025,335" 155 | 15 to 19 years,1971,"1,100,056","1,064,036" 156 | ,1972,"1,129,532","1,091,745" 157 | ,1973,"1,155,890","1,116,116" 158 | ,1974,"1,177,623","1,136,547" 159 | ,1975,"1,195,731","1,152,126" 160 | ,1976,"1,217,714","1,171,537" 161 | ,1977,"1,226,598","1,180,579" 162 | ,1978,"1,233,960","1,189,588" 163 | ,1979,"1,238,001","1,191,490" 164 | ,1980,"1,235,028","1,185,597" 165 | ,1981,"1,211,509","1,158,173" 166 | ,1982,"1,174,789","1,118,563" 167 | ,1983,"1,123,436","1,067,652" 168 | ,1984,"1,073,038","1,018,589" 169 | ,1985,"1,035,290","980,729" 170 | ,1986,"1,020,407","966,731" 171 | ,1987,"1,005,038","953,023" 172 | ,1988,"997,677","947,317" 173 | ,1989,"994,870","945,080" 174 | ,1990,"994,954","943,535" 175 | ,1991,"991,134","936,386" 176 | ,1992,"989,645","937,211" 177 | ,1993,"992,128","940,007" 178 | ,1994,"1,005,733","951,086" 179 | ,1995,"1,018,765","962,420" 180 | ,1996,"1,033,204","976,694" 181 | ,1997,"1,042,839","985,278" 182 | ,1998,"1,054,951","997,656" 183 | ,1999,"1,066,125","1,008,779" 184 | ,2000,"1,077,494","1,018,415" 185 | ,2001,"1,088,281","1,027,634" 186 | ,2002,"1,094,685","1,033,579" 187 | ,2003,"1,095,603","1,034,315" 188 | ,2004,"1,103,402","1,040,749" 189 | ,2005,"1,119,372","1,056,787" 190 | ,2006,"1,136,295","1,075,234" 191 | ,2007,"1,142,457","1,089,626" 192 | ,2008,"1,149,464","1,101,483" 193 | ,2009,"1,151,361","1,104,420" 194 | ,2010,"1,149,965","1,098,911" 195 | ,2011,"1,145,788","1,090,409" 196 | ,2012,"1,132,074","1,065,567" 197 | ,2013,"1,112,409","1,042,464" 198 | ,2014,"1,094,406","1,024,483" 199 | ,2015,"1,080,291","1,012,670" 200 | ,2016,"1,074,818","1,009,025" 201 | ,2017,"1,076,108","1,014,490" 202 | ,2018,"1,082,239","1,024,156" 203 | ,2019,"1,083,358","1,031,292" 204 | ,2020,"1,075,008","1,027,394" 205 | ,2021,"1,049,426","1,008,023" 206 | 20 to 24 years,1971,"991,602","985,312" 207 | ,1972,"1,002,087","987,680" 208 | ,1973,"1,024,047","1,008,646" 209 | ,1974,"1,062,655","1,043,240" 210 | ,1975,"1,103,548","1,086,131" 211 | ,1976,"1,133,641","1,118,503" 212 | ,1977,"1,157,155","1,142,844" 213 | ,1978,"1,177,760","1,161,097" 214 | ,1979,"1,196,939","1,178,101" 215 | ,1980,"1,223,225","1,200,663" 216 | ,1981,"1,249,840","1,226,753" 217 | ,1982,"1,261,167","1,232,671" 218 | ,1983,"1,271,871","1,235,434" 219 | ,1984,"1,280,364","1,234,949" 220 | ,1985,"1,275,621","1,225,337" 221 | ,1986,"1,249,187","1,196,138" 222 | ,1987,"1,208,448","1,154,094" 223 | ,1988,"1,151,677","1,104,258" 224 | ,1989,"1,110,742","1,072,434" 225 | ,1990,"1,077,716","1,042,735" 226 | ,1991,"1,061,978","1,023,850" 227 | ,1992,"1,051,986","1,015,763" 228 | ,1993,"1,041,399","1,004,060" 229 | ,1994,"1,030,001","994,093" 230 | ,1995,"1,021,422","987,065" 231 | ,1996,"1,017,687","983,288" 232 | ,1997,"1,023,408","983,764" 233 | ,1998,"1,027,574","985,193" 234 | ,1999,"1,042,649","995,891" 235 | ,2000,"1,058,812","1,009,565" 236 | ,2001,"1,078,970","1,030,027" 237 | ,2002,"1,094,908","1,047,380" 238 | ,2003,"1,113,265","1,064,767" 239 | ,2004,"1,129,998","1,080,971" 240 | ,2005,"1,142,940","1,091,380" 241 | ,2006,"1,152,981","1,098,759" 242 | ,2007,"1,155,932","1,105,399" 243 | ,2008,"1,154,716","1,109,909" 244 | ,2009,"1,163,650","1,122,351" 245 | ,2010,"1,178,481","1,143,491" 246 | ,2011,"1,193,322","1,159,133" 247 | ,2012,"1,220,026","1,169,935" 248 | ,2013,"1,241,717","1,174,716" 249 | ,2014,"1,252,785","1,170,249" 250 | ,2015,"1,244,697","1,150,926" 251 | ,2016,"1,242,113","1,145,078" 252 | ,2017,"1,250,319","1,151,100" 253 | ,2018,"1,270,494","1,165,965" 254 | ,2019,"1,292,734","1,182,769" 255 | ,2020,"1,295,901","1,188,412" 256 | ,2021,"1,279,464","1,173,237" 257 | 25 to 29 years,1971,"838,454","804,810" 258 | ,1972,"885,832","865,827" 259 | ,1973,"929,628","906,679" 260 | ,1974,"969,278","946,937" 261 | ,1975,"1,012,834","984,565" 262 | ,1976,"1,045,701","1,016,989" 263 | ,1977,"1,051,696","1,029,061" 264 | ,1978,"1,061,619","1,046,852" 265 | ,1979,"1,078,859","1,068,682" 266 | ,1980,"1,106,042","1,099,466" 267 | ,1981,"1,129,177","1,121,835" 268 | ,1982,"1,163,787","1,157,830" 269 | ,1983,"1,192,474","1,184,669" 270 | ,1984,"1,212,520","1,200,660" 271 | ,1985,"1,229,387","1,210,646" 272 | ,1986,"1,252,899","1,225,492" 273 | ,1987,"1,275,246","1,240,651" 274 | ,1988,"1,291,289","1,257,450" 275 | ,1989,"1,312,219","1,279,477" 276 | ,1990,"1,306,343","1,276,895" 277 | ,1991,"1,272,329","1,235,874" 278 | ,1992,"1,230,926","1,201,033" 279 | ,1993,"1,182,339","1,154,538" 280 | ,1994,"1,136,797","1,112,171" 281 | ,1995,"1,101,624","1,079,045" 282 | ,1996,"1,085,556","1,065,920" 283 | ,1997,"1,076,689","1,053,045" 284 | ,1998,"1,064,174","1,041,386" 285 | ,1999,"1,054,528","1,030,184" 286 | ,2000,"1,050,780","1,023,432" 287 | ,2001,"1,052,680","1,020,439" 288 | ,2002,"1,057,727","1,027,945" 289 | ,2003,"1,062,820","1,035,890" 290 | ,2004,"1,073,774","1,051,259" 291 | ,2005,"1,084,867","1,066,230" 292 | ,2006,"1,099,354","1,085,322" 293 | ,2007,"1,118,900","1,105,727" 294 | ,2008,"1,143,370","1,129,482" 295 | ,2009,"1,168,019","1,153,909" 296 | ,2010,"1,184,964","1,172,419" 297 | ,2011,"1,188,376","1,179,921" 298 | ,2012,"1,199,716","1,184,211" 299 | ,2013,"1,209,043","1,184,534" 300 | ,2014,"1,225,550","1,187,946" 301 | ,2015,"1,239,356","1,190,201" 302 | ,2016,"1,264,270","1,201,836" 303 | ,2017,"1,290,055","1,223,602" 304 | ,2018,"1,325,044","1,250,045" 305 | ,2019,"1,353,906","1,272,298" 306 | ,2020,"1,366,739","1,280,974" 307 | ,2021,"1,367,482","1,272,628" 308 | 30 to 34 years,1971,"685,790","656,954" 309 | ,1972,"713,542","680,338" 310 | ,1973,"744,904","714,928" 311 | ,1974,"784,887","750,287" 312 | ,1975,"820,349","788,173" 313 | ,1976,"857,096","825,094" 314 | ,1977,"913,390","881,460" 315 | ,1978,"951,942","922,014" 316 | ,1979,"984,319","958,877" 317 | ,1980,"1,021,012","1,000,081" 318 | ,1981,"1,049,461","1,034,371" 319 | ,1982,"1,053,909","1,041,150" 320 | ,1983,"1,064,474","1,055,938" 321 | ,1984,"1,085,458","1,080,894" 322 | ,1985,"1,113,106","1,113,290" 323 | ,1986,"1,141,237","1,142,174" 324 | ,1987,"1,179,327","1,175,227" 325 | ,1988,"1,211,771","1,204,207" 326 | ,1989,"1,248,250","1,236,075" 327 | ,1990,"1,271,918","1,261,474" 328 | ,1991,"1,301,807","1,283,472" 329 | ,1992,"1,310,907","1,293,444" 330 | ,1993,"1,322,893","1,303,864" 331 | ,1994,"1,331,842","1,308,137" 332 | ,1995,"1,327,016","1,301,887" 333 | ,1996,"1,298,177","1,273,499" 334 | ,1997,"1,263,973","1,238,172" 335 | ,1998,"1,211,050","1,191,860" 336 | ,1999,"1,165,817","1,148,264" 337 | ,2000,"1,136,367","1,117,071" 338 | ,2001,"1,130,642","1,109,732" 339 | ,2002,"1,127,602","1,103,900" 340 | ,2003,"1,119,906","1,095,145" 341 | ,2004,"1,108,478","1,086,222" 342 | ,2005,"1,099,816","1,082,294" 343 | ,2006,"1,092,313","1,078,944" 344 | ,2007,"1,094,111","1,088,063" 345 | ,2008,"1,103,818","1,103,570" 346 | ,2009,"1,121,021","1,124,324" 347 | ,2010,"1,138,881","1,144,355" 348 | ,2011,"1,159,976","1,166,280" 349 | ,2012,"1,179,945","1,188,128" 350 | ,2013,"1,202,017","1,209,632" 351 | ,2014,"1,222,168","1,225,669" 352 | ,2015,"1,230,618","1,229,883" 353 | ,2016,"1,249,488","1,239,172" 354 | ,2017,"1,266,458","1,248,629" 355 | ,2018,"1,289,327","1,263,972" 356 | ,2019,"1,319,340","1,286,054" 357 | ,2020,"1,351,551","1,312,935" 358 | ,2021,"1,371,210","1,326,578" 359 | 35 to 39 years,1971,"661,274","625,028" 360 | ,1972,"653,739","623,562" 361 | ,1973,"652,925","623,836" 362 | ,1974,"660,289","634,289" 363 | ,1975,"673,151","646,723" 364 | ,1976,"689,911","664,328" 365 | ,1977,"717,435","689,749" 366 | ,1978,"752,117","723,576" 367 | ,1979,"784,227","754,878" 368 | ,1980,"816,743","784,697" 369 | ,1981,"851,242","818,571" 370 | ,1982,"908,035","878,536" 371 | ,1983,"948,657","922,858" 372 | ,1984,"982,380","961,037" 373 | ,1985,"1,015,893","997,225" 374 | ,1986,"1,043,301","1,026,671" 375 | ,1987,"1,053,001","1,040,328" 376 | ,1988,"1,072,388","1,067,009" 377 | ,1989,"1,107,833","1,105,764" 378 | ,1990,"1,142,381","1,145,232" 379 | ,1991,"1,174,389","1,173,294" 380 | ,1992,"1,204,928","1,207,438" 381 | ,1993,"1,239,438","1,238,282" 382 | ,1994,"1,264,078","1,261,805" 383 | ,1995,"1,287,509","1,283,215" 384 | ,1996,"1,312,547","1,306,984" 385 | ,1997,"1,331,251","1,320,651" 386 | ,1998,"1,345,394","1,333,250" 387 | ,1999,"1,356,733","1,338,852" 388 | ,2000,"1,354,673","1,334,113" 389 | ,2001,"1,330,955","1,308,165" 390 | ,2002,"1,300,743","1,277,585" 391 | ,2003,"1,255,674","1,234,608" 392 | ,2004,"1,214,103","1,193,193" 393 | ,2005,"1,184,813","1,161,519" 394 | ,2006,"1,172,793","1,149,974" 395 | ,2007,"1,163,066","1,144,071" 396 | ,2008,"1,157,914","1,142,051" 397 | ,2009,"1,148,824","1,139,232" 398 | ,2010,"1,142,061","1,140,242" 399 | ,2011,"1,133,933","1,138,492" 400 | ,2012,"1,140,950","1,151,047" 401 | ,2013,"1,151,645","1,165,822" 402 | ,2014,"1,165,475","1,183,797" 403 | ,2015,"1,174,086","1,197,143" 404 | ,2016,"1,193,244","1,216,781" 405 | ,2017,"1,217,891","1,238,035" 406 | ,2018,"1,251,700","1,265,639" 407 | ,2019,"1,288,726","1,292,320" 408 | ,2020,"1,318,229","1,314,158" 409 | ,2021,"1,340,088","1,326,559" 410 | 40 to 44 years,1971,"655,406","628,748" 411 | ,1972,"660,165","629,301" 412 | ,1973,"662,343","630,716" 413 | ,1974,"662,988","630,689" 414 | ,1975,"658,769","629,135" 415 | ,1976,"656,726","629,336" 416 | ,1977,"652,225","627,845" 417 | ,1978,"650,553","626,822" 418 | ,1979,"660,668","637,293" 419 | ,1980,"675,973","651,546" 420 | ,1981,"697,231","671,213" 421 | ,1982,"719,626","693,597" 422 | ,1983,"748,811","724,428" 423 | ,1984,"777,772","754,928" 424 | ,1985,"808,479","785,070" 425 | ,1986,"844,577","821,462" 426 | ,1987,"901,782","879,949" 427 | ,1988,"946,183","926,431" 428 | ,1989,"990,707","974,721" 429 | ,1990,"1,032,724","1,022,052" 430 | ,1991,"1,069,653","1,061,711" 431 | ,1992,"1,074,605","1,072,063" 432 | ,1993,"1,089,326","1,092,612" 433 | ,1994,"1,116,243","1,122,280" 434 | ,1995,"1,149,564","1,157,618" 435 | ,1996,"1,181,315","1,189,973" 436 | ,1997,"1,218,811","1,227,382" 437 | ,1998,"1,251,699","1,258,559" 438 | ,1999,"1,275,360","1,280,760" 439 | ,2000,"1,299,531","1,301,404" 440 | ,2001,"1,329,876","1,326,009" 441 | ,2002,"1,350,625","1,341,052" 442 | ,2003,"1,369,714","1,356,042" 443 | ,2004,"1,386,921","1,367,835" 444 | ,2005,"1,390,861","1,369,357" 445 | ,2006,"1,370,062","1,345,529" 446 | ,2007,"1,332,425","1,308,806" 447 | ,2008,"1,283,966","1,264,719" 448 | ,2009,"1,240,231","1,225,300" 449 | ,2010,"1,207,096","1,195,963" 450 | ,2011,"1,195,287","1,190,494" 451 | ,2012,"1,191,249","1,190,224" 452 | ,2013,"1,186,258","1,188,477" 453 | ,2014,"1,177,103","1,185,309" 454 | ,2015,"1,167,211","1,182,711" 455 | ,2016,"1,160,414","1,181,764" 456 | ,2017,"1,164,184","1,189,546" 457 | ,2018,"1,178,063","1,203,513" 458 | ,2019,"1,198,647","1,223,242" 459 | ,2020,"1,220,668","1,244,906" 460 | ,2021,"1,244,626","1,265,038" 461 | 45 to 49 years,1971,"623,256","629,289" 462 | ,1972,"623,286","628,019" 463 | ,1973,"628,697","629,003" 464 | ,1974,"630,948","627,191" 465 | ,1975,"636,730","627,431" 466 | ,1976,"640,599","626,249" 467 | ,1977,"646,868","627,459" 468 | ,1978,"650,568","629,206" 469 | ,1979,"649,165","627,071" 470 | ,1980,"644,165","623,583" 471 | ,1981,"641,999","622,674" 472 | ,1982,"639,252","622,708" 473 | ,1983,"639,719","624,592" 474 | ,1984,"648,948","635,075" 475 | ,1985,"658,448","645,531" 476 | ,1986,"674,117","662,003" 477 | ,1987,"701,215","687,247" 478 | ,1988,"737,108","722,291" 479 | ,1989,"773,081","757,503" 480 | ,1990,"807,181","791,373" 481 | ,1991,"844,293","829,585" 482 | ,1992,"900,503","889,989" 483 | ,1993,"946,112","939,560" 484 | ,1994,"987,468","985,934" 485 | ,1995,"1,029,464","1,030,656" 486 | ,1996,"1,063,357","1,066,168" 487 | ,1997,"1,075,125","1,078,358" 488 | ,1998,"1,091,661","1,099,487" 489 | ,1999,"1,118,039","1,130,053" 490 | ,2000,"1,150,069","1,165,359" 491 | ,2001,"1,181,591","1,197,789" 492 | ,2002,"1,220,971","1,235,194" 493 | ,2003,"1,257,196","1,267,090" 494 | ,2004,"1,284,695","1,290,133" 495 | ,2005,"1,310,010","1,310,423" 496 | ,2006,"1,338,471","1,334,092" 497 | ,2007,"1,360,297","1,351,375" 498 | ,2008,"1,384,258","1,370,542" 499 | ,2009,"1,401,175","1,383,531" 500 | ,2010,"1,399,339","1,380,836" 501 | ,2011,"1,369,619","1,350,361" 502 | ,2012,"1,336,245","1,321,536" 503 | ,2013,"1,292,960","1,284,569" 504 | ,2014,"1,252,324","1,251,287" 505 | ,2015,"1,220,275","1,225,541" 506 | ,2016,"1,210,028","1,221,090" 507 | ,2017,"1,202,542","1,215,550" 508 | ,2018,"1,196,874","1,210,692" 509 | ,2019,"1,191,221","1,207,157" 510 | ,2020,"1,186,424","1,205,941" 511 | ,2021,"1,181,047","1,203,426" 512 | 50 to 54 years,1971,"526,548","539,116" 513 | ,1972,"548,221","563,871" 514 | ,1973,"567,508","586,894" 515 | ,1974,"586,783","608,629" 516 | ,1975,"594,967","620,291" 517 | ,1976,"601,494","627,670" 518 | ,1977,"602,178","624,328" 519 | ,1978,"606,972","622,763" 520 | ,1979,"610,731","619,934" 521 | ,1980,"619,227","622,014" 522 | ,1981,"626,629","623,743" 523 | ,1982,"633,464","627,033" 524 | ,1983,"635,857","627,801" 525 | ,1984,"633,330","625,566" 526 | ,1985,"627,733","621,616" 527 | ,1986,"625,021","620,252" 528 | ,1987,"623,066","618,569" 529 | ,1988,"626,109","620,339" 530 | ,1989,"639,893","633,077" 531 | ,1990,"654,145","646,655" 532 | ,1991,"675,039","667,929" 533 | ,1992,"698,991","693,592" 534 | ,1993,"730,094","727,077" 535 | ,1994,"760,293","760,220" 536 | ,1995,"790,309","792,755" 537 | ,1996,"825,093","829,470" 538 | ,1997,"885,687","889,347" 539 | ,1998,"934,389","937,913" 540 | ,1999,"976,696","981,421" 541 | ,2000,"1,018,908","1,025,786" 542 | ,2001,"1,053,763","1,063,704" 543 | ,2002,"1,064,112","1,077,360" 544 | ,2003,"1,081,165","1,098,576" 545 | ,2004,"1,110,602","1,130,355" 546 | ,2005,"1,146,838","1,166,887" 547 | ,2006,"1,182,039","1,200,952" 548 | ,2007,"1,222,813","1,235,418" 549 | ,2008,"1,261,673","1,265,892" 550 | ,2009,"1,292,908","1,290,617" 551 | ,2010,"1,320,504","1,313,888" 552 | ,2011,"1,350,060","1,340,989" 553 | ,2012,"1,367,055","1,359,154" 554 | ,2013,"1,383,470","1,377,344" 555 | ,2014,"1,396,037","1,390,545" 556 | ,2015,"1,392,935","1,390,415" 557 | ,2016,"1,367,448","1,367,116" 558 | ,2017,"1,330,958","1,333,934" 559 | ,2018,"1,286,609","1,293,519" 560 | ,2019,"1,247,044","1,258,000" 561 | ,2020,"1,219,306","1,232,973" 562 | ,2021,"1,206,634","1,223,700" 563 | 55 to 59 years,1971,"478,899","486,085" 564 | ,1972,"480,194","491,977" 565 | ,1973,"479,118","495,682" 566 | ,1974,"476,924","499,090" 567 | ,1975,"484,874","510,727" 568 | ,1976,"499,544","531,309" 569 | ,1977,"520,189","556,886" 570 | ,1978,"538,714","580,439" 571 | ,1979,"556,776","600,769" 572 | ,1980,"565,596","610,186" 573 | ,1981,"572,920","615,352" 574 | ,1982,"576,922","615,094" 575 | ,1983,"584,570","617,974" 576 | ,1984,"589,848","617,184" 577 | ,1985,"598,361","619,780" 578 | ,1986,"605,715","621,669" 579 | ,1987,"612,628","624,349" 580 | ,1988,"616,791","624,741" 581 | ,1989,"618,199","623,137" 582 | ,1990,"616,542","620,613" 583 | ,1991,"616,719","618,673" 584 | ,1992,"613,492","618,269" 585 | ,1993,"616,800","623,228" 586 | ,1994,"628,825","637,731" 587 | ,1995,"640,975","651,829" 588 | ,1996,"658,356","671,325" 589 | ,1997,"681,254","694,457" 590 | ,1998,"711,047","724,255" 591 | ,1999,"741,210","753,822" 592 | ,2000,"772,497","783,496" 593 | ,2001,"809,433","819,360" 594 | ,2002,"869,072","880,913" 595 | ,2003,"916,701","931,433" 596 | ,2004,"957,289","975,656" 597 | ,2005,"997,634","1,018,725" 598 | ,2006,"1,032,647","1,055,280" 599 | ,2007,"1,045,863","1,065,953" 600 | ,2008,"1,067,306","1,085,345" 601 | ,2009,"1,099,729","1,114,393" 602 | ,2010,"1,137,887","1,148,173" 603 | ,2011,"1,173,395","1,179,504" 604 | ,2012,"1,211,390","1,220,401" 605 | ,2013,"1,249,247","1,258,923" 606 | ,2014,"1,277,271","1,289,088" 607 | ,2015,"1,300,456","1,314,212" 608 | ,2016,"1,324,747","1,341,103" 609 | ,2017,"1,340,429","1,356,255" 610 | ,2018,"1,356,011","1,371,999" 611 | ,2019,"1,368,379","1,383,293" 612 | ,2020,"1,365,800","1,380,973" 613 | ,2021,"1,342,592","1,357,589" 614 | 60 to 64 years,1971,"386,266","399,427" 615 | ,1972,"398,901","414,234" 616 | ,1973,"410,557","429,344" 617 | ,1974,"424,254","446,642" 618 | ,1975,"435,891","464,194" 619 | ,1976,"440,819","472,310" 620 | ,1977,"442,524","479,895" 621 | ,1978,"442,124","484,896" 622 | ,1979,"440,833","488,357" 623 | ,1980,"450,554","501,540" 624 | ,1981,"466,088","521,483" 625 | ,1982,"485,747","546,079" 626 | ,1983,"503,993","569,272" 627 | ,1984,"522,230","590,447" 628 | ,1985,"529,489","598,075" 629 | ,1986,"536,418","602,649" 630 | ,1987,"543,959","604,890" 631 | ,1988,"554,357","608,815" 632 | ,1989,"562,007","609,158" 633 | ,1990,"571,593","611,205" 634 | ,1991,"579,778","611,479" 635 | ,1992,"587,841","614,991" 636 | ,1993,"592,319","616,488" 637 | ,1994,"594,584","615,875" 638 | ,1995,"593,667","614,518" 639 | ,1996,"592,731","613,831" 640 | ,1997,"590,778","613,580" 641 | ,1998,"593,724","617,410" 642 | ,1999,"603,086","628,494" 643 | ,2000,"613,561","639,653" 644 | ,2001,"630,932","657,929" 645 | ,2002,"655,716","682,834" 646 | ,2003,"687,348","713,976" 647 | ,2004,"720,207","746,552" 648 | ,2005,"752,916","778,534" 649 | ,2006,"788,278","814,788" 650 | ,2007,"844,340","871,684" 651 | ,2008,"891,262","918,923" 652 | ,2009,"933,466","960,955" 653 | ,2010,"977,853","1,003,392" 654 | ,2011,"1,013,565","1,036,368" 655 | ,2012,"1,023,315","1,046,823" 656 | ,2013,"1,041,252","1,069,420" 657 | ,2014,"1,069,392","1,102,217" 658 | ,2015,"1,102,960","1,140,251" 659 | ,2016,"1,135,977","1,177,183" 660 | ,2017,"1,172,720","1,215,336" 661 | ,2018,"1,208,301","1,249,185" 662 | ,2019,"1,236,940","1,277,130" 663 | ,2020,"1,260,909","1,300,768" 664 | ,2021,"1,283,211","1,323,674" 665 | 65 to 69 years,1971,"299,341","327,180" 666 | ,1972,"306,648","338,307" 667 | ,1973,"314,202","348,894" 668 | ,1974,"321,671","359,222" 669 | ,1975,"331,191","369,655" 670 | ,1976,"343,264","385,248" 671 | ,1977,"354,839","400,235" 672 | ,1978,"364,277","413,736" 673 | ,1979,"375,720","429,131" 674 | ,1980,"386,038","445,933" 675 | ,1981,"392,590","456,610" 676 | ,1982,"396,475","464,584" 677 | ,1983,"395,909","467,219" 678 | ,1984,"395,439","470,621" 679 | ,1985,"405,220","484,557" 680 | ,1986,"420,150","505,417" 681 | ,1987,"440,357","529,175" 682 | ,1988,"458,827","551,081" 683 | ,1989,"478,763","572,888" 684 | ,1990,"489,667","582,517" 685 | ,1991,"498,506","587,571" 686 | ,1992,"502,964","586,515" 687 | ,1993,"510,437","587,987" 688 | ,1994,"515,979","586,428" 689 | ,1995,"524,327","587,631" 690 | ,1996,"532,803","589,813" 691 | ,1997,"543,037","593,490" 692 | ,1998,"548,346","595,146" 693 | ,1999,"550,543","594,100" 694 | ,2000,"549,891","592,084" 695 | ,2001,"550,143","591,873" 696 | ,2002,"548,769","592,209" 697 | ,2003,"552,422","596,919" 698 | ,2004,"562,749","608,920" 699 | ,2005,"574,224","620,019" 700 | ,2006,"594,873","640,242" 701 | ,2007,"619,639","665,000" 702 | ,2008,"649,039","695,014" 703 | ,2009,"679,231","725,384" 704 | ,2010,"709,616","754,710" 705 | ,2011,"744,664","787,301" 706 | ,2012,"801,443","843,134" 707 | ,2013,"849,102","891,949" 708 | ,2014,"888,164","934,364" 709 | ,2015,"926,287","976,717" 710 | ,2016,"957,632","1,011,549" 711 | ,2017,"969,894","1,026,145" 712 | ,2018,"988,509","1,047,723" 713 | ,2019,"1,017,464","1,080,678" 714 | ,2020,"1,051,300","1,117,410" 715 | ,2021,"1,082,592","1,151,401" 716 | 70 to 74 years,1971,"207,978","254,087" 717 | ,1972,"214,655","259,748" 718 | ,1973,"223,146","268,175" 719 | ,1974,"231,382","277,308" 720 | ,1975,"238,096","286,232" 721 | ,1976,"244,532","294,583" 722 | ,1977,"250,882","306,407" 723 | ,1978,"257,863","318,132" 724 | ,1979,"264,946","329,898" 725 | ,1980,"273,774","341,496" 726 | ,1981,"283,082","354,799" 727 | ,1982,"291,746","366,780" 728 | ,1983,"301,547","380,229" 729 | ,1984,"312,293","395,273" 730 | ,1985,"321,858","410,646" 731 | ,1986,"327,825","420,012" 732 | ,1987,"332,954","428,790" 733 | ,1988,"334,628","432,512" 734 | ,1989,"336,996","437,024" 735 | ,1990,"348,484","451,135" 736 | ,1991,"364,432","470,193" 737 | ,1992,"381,693","492,270" 738 | ,1993,"396,877","511,744" 739 | ,1994,"412,194","529,555" 740 | ,1995,"420,003","536,517" 741 | ,1996,"426,048","540,478" 742 | ,1997,"432,147","540,941" 743 | ,1998,"441,182","543,470" 744 | ,1999,"448,533","543,203" 745 | ,2000,"458,814","546,211" 746 | ,2001,"469,449","550,109" 747 | ,2002,"479,207","554,039" 748 | ,2003,"484,531","556,066" 749 | ,2004,"487,565","556,009" 750 | ,2005,"488,185","555,542" 751 | ,2006,"489,997","556,480" 752 | ,2007,"491,123","557,988" 753 | ,2008,"497,659","563,861" 754 | ,2009,"510,213","576,668" 755 | ,2010,"524,094","590,594" 756 | ,2011,"542,589","610,293" 757 | ,2012,"564,079","629,968" 758 | ,2013,"592,170","656,031" 759 | ,2014,"621,283","682,739" 760 | ,2015,"649,566","708,146" 761 | ,2016,"682,973","740,214" 762 | ,2017,"736,099","797,239" 763 | ,2018,"779,386","846,230" 764 | ,2019,"818,263","890,350" 765 | ,2020,"855,213","932,911" 766 | ,2021,"885,817","967,719" 767 | 75 to 79 years,1971,"141,292","187,291" 768 | ,1972,"141,484","192,139" 769 | ,1973,"141,720","195,817" 770 | ,1974,"143,573","200,588" 771 | ,1975,"147,316","206,603" 772 | ,1976,"152,527","213,666" 773 | ,1977,"157,846","219,280" 774 | ,1978,"164,284","227,104" 775 | ,1979,"170,862","235,828" 776 | ,1980,"176,332","244,660" 777 | ,1981,"181,644","254,209" 778 | ,1982,"186,988","264,974" 779 | ,1983,"192,470","275,067" 780 | ,1984,"198,386","284,563" 781 | ,1985,"205,644","294,425" 782 | ,1986,"212,535","305,195" 783 | ,1987,"220,878","317,375" 784 | ,1988,"229,933","329,857" 785 | ,1989,"239,933","344,759" 786 | ,1990,"249,816","359,400" 787 | ,1991,"255,667","366,896" 788 | ,1992,"259,131","373,336" 789 | ,1993,"260,594","376,339" 790 | ,1994,"261,541","378,607" 791 | ,1995,"269,726","389,955" 792 | ,1996,"282,170","406,896" 793 | ,1997,"297,215","426,750" 794 | ,1998,"311,273","445,516" 795 | ,1999,"325,269","462,603" 796 | ,2000,"334,440","470,473" 797 | ,2001,"343,126","475,809" 798 | ,2002,"350,520","478,432" 799 | ,2003,"360,152","482,173" 800 | ,2004,"368,094","483,053" 801 | ,2005,"377,188","486,257" 802 | ,2006,"387,233","490,152" 803 | ,2007,"396,494","495,067" 804 | ,2008,"403,051","498,777" 805 | ,2009,"407,556","500,289" 806 | ,2010,"411,363","502,028" 807 | ,2011,"415,677","503,266" 808 | ,2012,"420,270","504,878" 809 | ,2013,"428,838","510,427" 810 | ,2014,"440,683","520,864" 811 | ,2015,"452,282","530,742" 812 | ,2016,"468,088","546,213" 813 | ,2017,"489,679","568,011" 814 | ,2018,"515,938","593,747" 815 | ,2019,"543,578","621,756" 816 | ,2020,"570,476","649,433" 817 | ,2021,"599,691","680,852" 818 | 80 to 84 years,1971,"86,512","119,662" 819 | ,1972,"86,812","123,037" 820 | ,1973,"86,523","126,296" 821 | ,1974,"86,084","128,708" 822 | ,1975,"85,737","131,883" 823 | ,1976,"86,262","136,349" 824 | ,1977,"87,277","141,530" 825 | ,1978,"88,022","145,761" 826 | ,1979,"90,068","151,450" 827 | ,1980,"92,565","157,092" 828 | ,1981,"95,673","162,975" 829 | ,1982,"99,935","167,685" 830 | ,1983,"104,530","174,049" 831 | ,1984,"109,440","182,184" 832 | ,1985,"113,282","189,809" 833 | ,1986,"116,819","197,235" 834 | ,1987,"121,437","206,231" 835 | ,1988,"125,740","214,308" 836 | ,1989,"130,647","222,859" 837 | ,1990,"136,176","231,113" 838 | ,1991,"142,053","240,000" 839 | ,1992,"147,879","249,531" 840 | ,1993,"153,830","259,328" 841 | ,1994,"160,060","270,310" 842 | ,1995,"166,297","281,296" 843 | ,1996,"170,084","287,169" 844 | ,1997,"172,892","292,285" 845 | ,1998,"174,265","295,083" 846 | ,1999,"176,145","299,205" 847 | ,2000,"184,430","310,956" 848 | ,2001,"195,937","327,206" 849 | ,2002,"209,371","344,893" 850 | ,2003,"221,920","361,394" 851 | ,2004,"233,940","376,884" 852 | ,2005,"243,248","385,336" 853 | ,2006,"251,773","391,593" 854 | ,2007,"257,076","393,720" 855 | ,2008,"264,613","397,286" 856 | ,2009,"271,555","399,533" 857 | ,2010,"280,606","404,471" 858 | ,2011,"290,476","410,251" 859 | ,2012,"299,922","414,465" 860 | ,2013,"307,258","416,490" 861 | ,2014,"313,199","417,585" 862 | ,2015,"317,644","417,363" 863 | ,2016,"323,647","418,932" 864 | ,2017,"329,293","422,348" 865 | ,2018,"337,168","429,331" 866 | ,2019,"348,450","440,589" 867 | ,2020,"360,079","452,534" 868 | ,2021,"373,517","468,771" 869 | 85 to 89 years,1971,"41,058","60,059" 870 | ,1972,"41,562","62,381" 871 | ,1973,"41,997","64,939" 872 | ,1974,"42,349","67,672" 873 | ,1975,"42,142","69,375" 874 | ,1976,"41,927","71,479" 875 | ,1977,"42,101","74,240" 876 | ,1978,"42,175","76,856" 877 | ,1979,"42,449","79,285" 878 | ,1980,"43,074","82,906" 879 | ,1981,"44,265","87,700" 880 | ,1982,"44,683","91,551" 881 | ,1983,"45,067","94,387" 882 | ,1984,"46,073","97,677" 883 | ,1985,"47,463","101,256" 884 | ,1986,"49,249","105,293" 885 | ,1987,"52,341","109,660" 886 | ,1988,"55,125","114,512" 887 | ,1989,"58,127","120,308" 888 | ,1990,"60,555","125,721" 889 | ,1991,"62,040","130,115" 890 | ,1992,"63,705","135,497" 891 | ,1993,"65,832","140,763" 892 | ,1994,"68,117","145,966" 893 | ,1995,"70,995","151,073" 894 | ,1996,"74,421","157,547" 895 | ,1997,"76,861","163,687" 896 | ,1998,"80,229","170,489" 897 | ,1999,"84,029","178,304" 898 | ,2000,"88,469","186,940" 899 | ,2001,"91,989","191,979" 900 | ,2002,"94,427","196,695" 901 | ,2003,"96,618","199,889" 902 | ,2004,"99,378","203,956" 903 | ,2005,"106,013","214,475" 904 | ,2006,"115,731","229,168" 905 | ,2007,"124,422","242,572" 906 | ,2008,"131,926","254,697" 907 | ,2009,"139,420","266,188" 908 | ,2010,"144,979","272,920" 909 | ,2011,"149,290","277,217" 910 | ,2012,"155,870","281,245" 911 | ,2013,"163,301","285,102" 912 | ,2014,"170,273","287,314" 913 | ,2015,"177,089","290,076" 914 | ,2016,"185,348","295,329" 915 | ,2017,"193,048","300,639" 916 | ,2018,"199,661","304,115" 917 | ,2019,"205,760","307,445" 918 | ,2020,"209,743","309,702" 919 | ,2021,"213,144","312,032" -------------------------------------------------------------------------------- /pythonexcel.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/pythonexcel.xlsx -------------------------------------------------------------------------------- /sales.csv: -------------------------------------------------------------------------------- 1 | Date,Sales 2 | 3/19/2020,44 3 | 3/20/2020,60 4 | 3/21/2020,59 5 | 3/22/2020,48 6 | 3/23/2020,78 7 | 3/24/2020,85 8 | 3/25/2020,100 9 | 3/26/2020,170 10 | 3/27/2020,135 11 | 3/28/2020,151 12 | 3/29/2020,211 13 | 3/30/2020,351 14 | 3/31/2020,260 15 | 4/1/2020,426 16 | 4/2/2020,401 17 | 4/3/2020,462 18 | 4/4/2020,375 19 | 4/5/2020,408 20 | 4/6/2020,309 21 | 4/7/2020,379 22 | 4/8/2020,550 23 | 4/9/2020,483 24 | 4/10/2020,478 25 | 4/11/2020,411 26 | 4/12/2020,401 27 | 4/13/2020,421 28 | 4/14/2020,483 29 | 4/15/2020,494 30 | 4/16/2020,514 31 | 4/17/2020,564 32 | 4/18/2020,485 33 | 4/19/2020,568 34 | 4/20/2020,606 35 | 4/21/2020,551 36 | 4/22/2020,510 37 | 4/23/2020,634 38 | 4/24/2020,640 39 | 4/25/2020,476 40 | 4/26/2020,437 41 | 4/27/2020,424 42 | 4/28/2020,525 43 | 4/29/2020,347 44 | 4/30/2020,459 45 | 5/1/2020,421 46 | 5/2/2020,511 47 | 5/3/2020,434 48 | 5/4/2020,370 49 | 5/5/2020,387 50 | 5/6/2020,412 51 | 5/7/2020,399 52 | 5/8/2020,477 53 | 5/9/2020,346 54 | 5/10/2020,294 55 | 5/11/2020,308 56 | 5/12/2020,361 57 | 5/13/2020,329 58 | 5/14/2020,345 59 | 5/15/2020,341 60 | 5/16/2020,391 61 | 5/17/2020,340 62 | 5/18/2020,304 63 | 5/19/2020,427 64 | 5/20/2020,390 65 | 5/21/2020,413 66 | -------------------------------------------------------------------------------- /sample.csv: -------------------------------------------------------------------------------- 1 | Name,Height,Weight 2 | Nik,70,170 3 | John,68,175 4 | Alex,71, 5 | Kate,, 6 | Jane,56,135 7 | Melissa,57,130 8 | -------------------------------------------------------------------------------- /sample.json: -------------------------------------------------------------------------------- 1 | {"activity":"Plan a trip to another country","type":"recreational","participants":1,"price":0,"link":"","key":"5554727","accessibility":0} -------------------------------------------------------------------------------- /sample_pivot.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/sample_pivot.xlsx -------------------------------------------------------------------------------- /sort_values.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/sort_values.xlsx -------------------------------------------------------------------------------- /stocks-wide.csv: -------------------------------------------------------------------------------- 1 | ,Date,AAPL,GOOG,TSLA 2 | 0,2020-03-30,62.685001,1125.040039,102.052002 3 | 1,2020-03-31,63.900002,1147.300049,100.25 4 | 2,2020-04-01,61.625,1122.0,100.800003 5 | 3,2020-04-02,60.084999,1098.26001,96.206001 6 | 4,2020-04-03,60.700001,1119.015015,101.900002 7 | 5,2020-04-06,62.724998,1138.0,102.239998 8 | 6,2020-04-07,67.699997,1221.0,109.0 9 | 7,2020-04-08,65.684998,1206.5,110.839996 10 | 8,2020-04-09,67.175003,1224.079956,112.417999 11 | 9,2020-04-13,67.077499,1209.180054,118.031998 12 | 10,2020-04-14,70.0,1245.089966,139.794006 13 | 11,2020-04-15,70.599998,1245.609985,148.399994 14 | 12,2020-04-16,71.845001,1274.099976,143.388 15 | 13,2020-04-17,71.172501,1284.849976,154.455994 16 | 14,2020-04-20,69.487503,1271.0,146.53999299999995 17 | 15,2020-04-21,69.07,1247.0,146.024002 18 | 16,2020-04-22,68.402496,1245.540039,140.796005 19 | 17,2020-04-23,68.967499,1271.550049,145.520004 20 | 18,2020-04-24,69.300003,1261.170044,142.162003 21 | 19,2020-04-27,70.449997,1296.0,147.522003 22 | 20,2020-04-28,71.269997,1287.930054,159.128006 23 | 21,2020-04-29,71.182503,1341.459961,158.033997 24 | 22,2020-04-30,72.489998,1324.880005,171.037994 25 | 23,2020-05-01,71.5625,1328.5,151.0 26 | 24,2020-05-04,72.292503,1308.22998,140.199997 27 | 25,2020-05-05,73.764999,1337.920044,157.957993 28 | 26,2020-05-06,75.114998,1361.689941,155.300003 29 | 27,2020-05-07,75.805,1365.939941,155.442001 30 | 28,2020-05-08,76.410004,1383.130005,158.753998 31 | 29,2020-05-11,77.025002,1378.280029,158.102005 32 | 30,2020-05-12,79.457497,1407.119995,165.399994 33 | 31,2020-05-13,78.037498,1377.050049,164.166 34 | 32,2020-05-14,76.127502,1335.02002,156.0 35 | 33,2020-05-15,75.087502,1350.0,158.070007 36 | 34,2020-05-18,78.292503,1361.75,165.55599999999998 37 | 35,2020-05-19,78.7575,1386.996948,163.033997 38 | 36,2020-05-20,79.16999799999998,1389.579956,164.100006 39 | 37,2020-05-21,79.665001,1408.0,163.199997 40 | 38,2020-05-22,78.942497,1396.709961,164.434006 41 | 39,2020-05-26,80.875,1437.27002,166.899994 42 | 40,2020-05-27,79.035004,1417.25,164.171997 43 | 41,2020-05-28,79.192497,1396.859985,162.701996 44 | 42,2020-05-29,79.8125,1416.939941,161.75 45 | 43,2020-06-01,79.4375,1418.390015,171.600006 46 | 44,2020-06-02,80.1875,1430.550049,178.940002 47 | 45,2020-06-03,81.165001,1438.300049,177.62399299999996 48 | 46,2020-06-04,81.097504,1430.400024,177.975998 49 | 47,2020-06-05,80.837502,1413.170044,175.567993 50 | 48,2020-06-08,82.5625,1422.339966,183.800003 51 | 49,2020-06-09,83.035004,1445.359985,188.001999 52 | 50,2020-06-10,86.974998,1459.540039,198.376007 53 | 51,2020-06-11,87.327499,1442.47998,198.039993 54 | 52,2020-06-12,86.18,1428.48999,196.0 55 | 53,2020-06-15,83.3125,1390.800049,183.557999 56 | 54,2020-06-16,87.864998,1445.219971,202.369995 57 | 55,2020-06-17,88.787498,1447.160034,197.542007 58 | 56,2020-06-18,87.852501,1449.160034,200.600006 59 | 57,2020-06-19,88.660004,1444.0,202.55599999999998 60 | 58,2020-06-22,87.834999,1429.0,199.990005 61 | 59,2020-06-23,91.0,1455.640015,199.776001 62 | 60,2020-06-24,91.25,1461.51001,198.822006 63 | 61,2020-06-25,90.175003,1429.900024,190.854004 64 | 62,2020-06-26,91.102501,1431.390015,198.955994 65 | 63,2020-06-29,88.3125,1358.180054,193.802002 66 | 64,2020-06-30,90.019997,1390.439941,201.300003 67 | 65,2020-07-01,91.279999,1411.099976,216.600006 68 | 66,2020-07-02,91.962502,1446.939941,244.296005 69 | 67,2020-07-06,92.5,1480.060059,255.33799700000003 70 | 68,2020-07-07,93.852501,1490.0,281.00201400000003 71 | 69,2020-07-08,94.18,1494.319946,281.0 72 | 70,2020-07-09,96.262497,1506.449951,279.39801 73 | 71,2020-07-10,95.334999,1506.150024,279.200012 74 | 72,2020-07-13,97.264999,1550.0,331.799988 75 | 73,2020-07-14,94.839996,1490.310059,311.200012 76 | 74,2020-07-15,98.989998,1523.130005,308.600006 77 | 75,2020-07-16,96.5625,1500.0,295.432007 78 | 76,2020-07-17,96.987503,1521.619995,302.690002 79 | 77,2020-07-20,96.417503,1515.26001,303.802002 80 | 78,2020-07-21,99.172501,1586.98999,327.985992 81 | 79,2020-07-22,96.692497,1560.5,319.799988 82 | 80,2020-07-23,96.997498,1566.969971,335.790009 83 | 81,2020-07-24,90.987503,1498.930054,283.201996 84 | 82,2020-07-27,93.709999,1515.599976,287.0 85 | 83,2020-07-28,94.3675,1525.180054,300.799988 86 | 84,2020-07-29,93.75,1506.319946,300.200012 87 | 85,2020-07-30,94.1875,1497.0,297.600006 88 | 86,2020-07-31,102.885002,1505.01001,303.0 89 | 87,2020-08-03,108.199997,1486.640015,289.839996 90 | 88,2020-08-04,109.1325,1476.569946,299.0020140000001 91 | 89,2020-08-05,109.377502,1469.300049,298.597992 92 | 90,2020-08-06,110.404999,1471.75,298.1659850000001 93 | 91,2020-08-07,113.205002,1500.0,299.90799 94 | 92,2020-08-10,112.599998,1487.180054,289.600006 95 | 93,2020-08-11,111.970001,1492.439941,279.200012 96 | 94,2020-08-12,110.497498,1485.579956,294.0 97 | 95,2020-08-13,114.43,1510.339966,322.200012 98 | 96,2020-08-14,114.830002,1515.660034,332.997986 99 | 97,2020-08-17,116.0625,1514.670044,335.399994 100 | 98,2020-08-18,114.352501,1526.180054,379.798004 101 | 99,2020-08-19,115.982498,1553.310059,373.0 102 | 100,2020-08-20,115.75,1543.449951,372.135986 103 | 101,2020-08-21,119.262497,1577.030029,408.951996 104 | 102,2020-08-24,128.697495,1593.97998,425.256012 105 | 103,2020-08-25,124.697502,1582.069946,394.977997 106 | 104,2020-08-26,126.18,1608.0,412.0 107 | 105,2020-08-27,127.142502,1653.680054,436.09201 108 | 106,2020-08-28,126.012497,1633.48999,459.023987 109 | 107,2020-08-31,127.580002,1647.890015,444.609985 110 | 108,2020-09-01,132.759995,1636.630005,502.14001500000006 111 | 109,2020-09-02,137.589996,1673.775024,478.98999 112 | 110,2020-09-03,126.910004,1709.713989,407.230011 113 | 111,2020-09-04,120.07,1624.26001,402.809998 114 | 112,2020-09-08,113.949997,1533.51001,356.0 115 | 113,2020-09-09,117.260002,1557.530029,356.600006 116 | 114,2020-09-10,120.360001,1560.640015,386.209991 117 | 115,2020-09-11,114.57,1536.0,381.940002 118 | 116,2020-09-14,114.720001,1539.005005,380.950012 119 | 117,2020-09-15,118.330002,1536.0,436.55999800000006 120 | 118,2020-09-16,115.230003,1555.540039,439.869995 121 | 119,2020-09-17,109.720001,1496.0,415.600006 122 | 120,2020-09-18,110.400002,1498.01001,447.940002 123 | 121,2020-09-21,104.540001,1440.060059,453.130005 124 | 122,2020-09-22,112.68,1450.089966,429.600006 125 | 123,2020-09-23,111.620003,1458.780029,405.160004 126 | 124,2020-09-24,105.169998,1411.030029,363.799988 127 | 125,2020-09-25,108.43,1432.630005,393.470001 128 | 126,2020-09-28,115.010002,1474.209961,424.619995 129 | 127,2020-09-29,114.550003,1470.390015,416.0 130 | 128,2020-09-30,113.790001,1466.800049,421.320007 131 | 129,2020-10-01,117.639999,1484.27002,440.76001 132 | 130,2020-10-02,112.889999,1462.030029,421.39001500000006 133 | 131,2020-10-05,113.910004,1466.209961,423.350006 134 | 132,2020-10-06,115.699997,1475.579956,423.790009 135 | 133,2020-10-07,114.620003,1464.290039,419.869995 136 | 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149,2020-10-29,112.370003,AAPL 152 | 150,2020-10-30,111.059998,AAPL 153 | 151,2020-11-02,109.110001,AAPL 154 | 152,2020-11-03,109.660004,AAPL 155 | 153,2020-11-04,114.139999,AAPL 156 | 154,2020-11-05,117.949997,AAPL 157 | 155,2020-11-06,118.32,AAPL 158 | 156,2020-11-09,120.5,AAPL 159 | 157,2020-11-10,115.550003,AAPL 160 | 158,2020-11-11,117.190002,AAPL 161 | 159,2020-11-12,119.620003,AAPL 162 | 160,2020-11-13,119.440002,AAPL 163 | 161,2020-11-16,118.91999799999999,AAPL 164 | 162,2020-11-17,119.550003,AAPL 165 | 163,2020-11-18,118.610001,AAPL 166 | 164,2020-11-19,117.589996,AAPL 167 | 165,2020-11-20,118.639999,AAPL 168 | 166,2020-11-23,117.18,AAPL 169 | 167,2020-11-24,113.910004,AAPL 170 | 168,2020-11-25,115.550003,AAPL 171 | 169,2020-11-27,116.57,AAPL 172 | 170,2020-11-30,116.970001,AAPL 173 | 171,2020-12-01,121.010002,AAPL 174 | 172,2020-12-02,122.019997,AAPL 175 | 173,2020-12-03,123.519997,AAPL 176 | 174,2020-12-04,122.599998,AAPL 177 | 175,2020-12-07,122.309998,AAPL 178 | 176,2020-12-08,124.370003,AAPL 179 | 177,2020-12-09,124.529999,AAPL 180 | 178,2020-12-10,120.5,AAPL 181 | 179,2020-12-11,122.43,AAPL 182 | 180,2020-12-14,122.599998,AAPL 183 | 181,2020-12-15,124.339996,AAPL 184 | 182,2020-12-16,127.410004,AAPL 185 | 183,2020-12-17,128.899994,AAPL 186 | 184,2020-12-18,128.96000700000002,AAPL 187 | 185,2020-12-21,125.019997,AAPL 188 | 186,2020-12-22,131.610001,AAPL 189 | 187,2020-12-23,132.16000400000001,AAPL 190 | 188,2020-12-24,131.320007,AAPL 191 | 189,2020-12-28,133.990005,AAPL 192 | 190,2020-12-29,138.050003,AAPL 193 | 191,2020-12-30,135.580002,AAPL 194 | 192,2020-12-31,134.080002,AAPL 195 | 193,2021-01-04,133.520004,AAPL 196 | 194,2021-01-05,128.889999,AAPL 197 | 195,2021-01-06,127.720001,AAPL 198 | 196,2021-01-07,128.360001,AAPL 199 | 197,2021-01-08,132.429993,AAPL 200 | 198,2021-01-11,129.190002,AAPL 201 | 199,2021-01-12,128.5,AAPL 202 | 200,2021-01-13,128.759995,AAPL 203 | 201,2021-01-14,130.800003,AAPL 204 | 202,2021-01-15,128.779999,AAPL 205 | 203,2021-01-19,127.779999,AAPL 206 | 204,2021-01-20,128.66000400000001,AAPL 207 | 205,2021-01-21,133.800003,AAPL 208 | 206,2021-01-22,136.279999,AAPL 209 | 207,2021-01-25,143.070007,AAPL 210 | 208,2021-01-26,143.600006,AAPL 211 | 209,2021-01-27,143.429993,AAPL 212 | 210,2021-01-28,139.520004,AAPL 213 | 211,2021-01-29,135.830002,AAPL 214 | 212,2021-02-01,133.75,AAPL 215 | 213,2021-02-02,135.729996,AAPL 216 | 214,2021-02-03,135.759995,AAPL 217 | 215,2021-02-04,136.300003,AAPL 218 | 216,2021-02-05,137.350006,AAPL 219 | 217,2021-02-08,136.029999,AAPL 220 | 218,2021-02-09,136.619995,AAPL 221 | 219,2021-02-10,136.479996,AAPL 222 | 220,2021-02-11,135.899994,AAPL 223 | 221,2021-02-12,134.350006,AAPL 224 | 222,2021-02-16,135.490005,AAPL 225 | 223,2021-02-17,131.25,AAPL 226 | 224,2021-02-18,129.199997,AAPL 227 | 225,2021-02-19,130.240005,AAPL 228 | 226,2021-02-22,128.009995,AAPL 229 | 227,2021-02-23,123.760002,AAPL 230 | 228,2021-02-24,124.940002,AAPL 231 | 229,2021-02-25,124.68,AAPL 232 | 230,2021-02-26,122.589996,AAPL 233 | 231,2021-03-01,123.75,AAPL 234 | 232,2021-03-02,128.41000400000001,AAPL 235 | 233,2021-03-03,124.809998,AAPL 236 | 234,2021-03-04,121.75,AAPL 237 | 235,2021-03-05,120.980003,AAPL 238 | 236,2021-03-08,120.93,AAPL 239 | 237,2021-03-09,119.029999,AAPL 240 | 238,2021-03-10,121.690002,AAPL 241 | 239,2021-03-11,122.540001,AAPL 242 | 240,2021-03-12,120.400002,AAPL 243 | 241,2021-03-15,121.410004,AAPL 244 | 242,2021-03-16,125.699997,AAPL 245 | 243,2021-03-17,124.050003,AAPL 246 | 244,2021-03-18,122.879997,AAPL 247 | 245,2021-03-19,119.900002,AAPL 248 | 246,2021-03-22,120.33000200000001,AAPL 249 | 247,2021-03-23,123.33000200000001,AAPL 250 | 248,2021-03-24,122.82,AAPL 251 | 249,2021-03-25,119.540001,AAPL 252 | 250,2021-03-26,120.349998,AAPL 253 | 0,2020-03-30,1125.040039,GOOG 254 | 1,2020-03-31,1147.300049,GOOG 255 | 2,2020-04-01,1122.0,GOOG 256 | 3,2020-04-02,1098.26001,GOOG 257 | 4,2020-04-03,1119.015015,GOOG 258 | 5,2020-04-06,1138.0,GOOG 259 | 6,2020-04-07,1221.0,GOOG 260 | 7,2020-04-08,1206.5,GOOG 261 | 8,2020-04-09,1224.079956,GOOG 262 | 9,2020-04-13,1209.180054,GOOG 263 | 10,2020-04-14,1245.089966,GOOG 264 | 11,2020-04-15,1245.609985,GOOG 265 | 12,2020-04-16,1274.099976,GOOG 266 | 13,2020-04-17,1284.849976,GOOG 267 | 14,2020-04-20,1271.0,GOOG 268 | 15,2020-04-21,1247.0,GOOG 269 | 16,2020-04-22,1245.540039,GOOG 270 | 17,2020-04-23,1271.550049,GOOG 271 | 18,2020-04-24,1261.170044,GOOG 272 | 19,2020-04-27,1296.0,GOOG 273 | 20,2020-04-28,1287.930054,GOOG 274 | 21,2020-04-29,1341.459961,GOOG 275 | 22,2020-04-30,1324.880005,GOOG 276 | 23,2020-05-01,1328.5,GOOG 277 | 24,2020-05-04,1308.22998,GOOG 278 | 25,2020-05-05,1337.920044,GOOG 279 | 26,2020-05-06,1361.689941,GOOG 280 | 27,2020-05-07,1365.939941,GOOG 281 | 28,2020-05-08,1383.130005,GOOG 282 | 29,2020-05-11,1378.280029,GOOG 283 | 30,2020-05-12,1407.119995,GOOG 284 | 31,2020-05-13,1377.050049,GOOG 285 | 32,2020-05-14,1335.02002,GOOG 286 | 33,2020-05-15,1350.0,GOOG 287 | 34,2020-05-18,1361.75,GOOG 288 | 35,2020-05-19,1386.996948,GOOG 289 | 36,2020-05-20,1389.579956,GOOG 290 | 37,2020-05-21,1408.0,GOOG 291 | 38,2020-05-22,1396.709961,GOOG 292 | 39,2020-05-26,1437.27002,GOOG 293 | 40,2020-05-27,1417.25,GOOG 294 | 41,2020-05-28,1396.859985,GOOG 295 | 42,2020-05-29,1416.939941,GOOG 296 | 43,2020-06-01,1418.390015,GOOG 297 | 44,2020-06-02,1430.550049,GOOG 298 | 45,2020-06-03,1438.300049,GOOG 299 | 46,2020-06-04,1430.400024,GOOG 300 | 47,2020-06-05,1413.170044,GOOG 301 | 48,2020-06-08,1422.339966,GOOG 302 | 49,2020-06-09,1445.359985,GOOG 303 | 50,2020-06-10,1459.540039,GOOG 304 | 51,2020-06-11,1442.47998,GOOG 305 | 52,2020-06-12,1428.48999,GOOG 306 | 53,2020-06-15,1390.800049,GOOG 307 | 54,2020-06-16,1445.219971,GOOG 308 | 55,2020-06-17,1447.160034,GOOG 309 | 56,2020-06-18,1449.160034,GOOG 310 | 57,2020-06-19,1444.0,GOOG 311 | 58,2020-06-22,1429.0,GOOG 312 | 59,2020-06-23,1455.640015,GOOG 313 | 60,2020-06-24,1461.51001,GOOG 314 | 61,2020-06-25,1429.900024,GOOG 315 | 62,2020-06-26,1431.390015,GOOG 316 | 63,2020-06-29,1358.180054,GOOG 317 | 64,2020-06-30,1390.439941,GOOG 318 | 65,2020-07-01,1411.099976,GOOG 319 | 66,2020-07-02,1446.939941,GOOG 320 | 67,2020-07-06,1480.060059,GOOG 321 | 68,2020-07-07,1490.0,GOOG 322 | 69,2020-07-08,1494.319946,GOOG 323 | 70,2020-07-09,1506.449951,GOOG 324 | 71,2020-07-10,1506.150024,GOOG 325 | 72,2020-07-13,1550.0,GOOG 326 | 73,2020-07-14,1490.310059,GOOG 327 | 74,2020-07-15,1523.130005,GOOG 328 | 75,2020-07-16,1500.0,GOOG 329 | 76,2020-07-17,1521.619995,GOOG 330 | 77,2020-07-20,1515.26001,GOOG 331 | 78,2020-07-21,1586.98999,GOOG 332 | 79,2020-07-22,1560.5,GOOG 333 | 80,2020-07-23,1566.969971,GOOG 334 | 81,2020-07-24,1498.930054,GOOG 335 | 82,2020-07-27,1515.599976,GOOG 336 | 83,2020-07-28,1525.180054,GOOG 337 | 84,2020-07-29,1506.319946,GOOG 338 | 85,2020-07-30,1497.0,GOOG 339 | 86,2020-07-31,1505.01001,GOOG 340 | 87,2020-08-03,1486.640015,GOOG 341 | 88,2020-08-04,1476.569946,GOOG 342 | 89,2020-08-05,1469.300049,GOOG 343 | 90,2020-08-06,1471.75,GOOG 344 | 91,2020-08-07,1500.0,GOOG 345 | 92,2020-08-10,1487.180054,GOOG 346 | 93,2020-08-11,1492.439941,GOOG 347 | 94,2020-08-12,1485.579956,GOOG 348 | 95,2020-08-13,1510.339966,GOOG 349 | 96,2020-08-14,1515.660034,GOOG 350 | 97,2020-08-17,1514.670044,GOOG 351 | 98,2020-08-18,1526.180054,GOOG 352 | 99,2020-08-19,1553.310059,GOOG 353 | 100,2020-08-20,1543.449951,GOOG 354 | 101,2020-08-21,1577.030029,GOOG 355 | 102,2020-08-24,1593.97998,GOOG 356 | 103,2020-08-25,1582.069946,GOOG 357 | 104,2020-08-26,1608.0,GOOG 358 | 105,2020-08-27,1653.680054,GOOG 359 | 106,2020-08-28,1633.48999,GOOG 360 | 107,2020-08-31,1647.890015,GOOG 361 | 108,2020-09-01,1636.630005,GOOG 362 | 109,2020-09-02,1673.775024,GOOG 363 | 110,2020-09-03,1709.713989,GOOG 364 | 111,2020-09-04,1624.26001,GOOG 365 | 112,2020-09-08,1533.51001,GOOG 366 | 113,2020-09-09,1557.530029,GOOG 367 | 114,2020-09-10,1560.640015,GOOG 368 | 115,2020-09-11,1536.0,GOOG 369 | 116,2020-09-14,1539.005005,GOOG 370 | 117,2020-09-15,1536.0,GOOG 371 | 118,2020-09-16,1555.540039,GOOG 372 | 119,2020-09-17,1496.0,GOOG 373 | 120,2020-09-18,1498.01001,GOOG 374 | 121,2020-09-21,1440.060059,GOOG 375 | 122,2020-09-22,1450.089966,GOOG 376 | 123,2020-09-23,1458.780029,GOOG 377 | 124,2020-09-24,1411.030029,GOOG 378 | 125,2020-09-25,1432.630005,GOOG 379 | 126,2020-09-28,1474.209961,GOOG 380 | 127,2020-09-29,1470.390015,GOOG 381 | 128,2020-09-30,1466.800049,GOOG 382 | 129,2020-10-01,1484.27002,GOOG 383 | 130,2020-10-02,1462.030029,GOOG 384 | 131,2020-10-05,1466.209961,GOOG 385 | 132,2020-10-06,1475.579956,GOOG 386 | 133,2020-10-07,1464.290039,GOOG 387 | 134,2020-10-08,1465.089966,GOOG 388 | 135,2020-10-09,1494.699951,GOOG 389 | 136,2020-10-12,1543.0,GOOG 390 | 137,2020-10-13,1583.72998,GOOG 391 | 138,2020-10-14,1578.589966,GOOG 392 | 139,2020-10-15,1547.150024,GOOG 393 | 140,2020-10-16,1565.849976,GOOG 394 | 141,2020-10-19,1580.459961,GOOG 395 | 142,2020-10-20,1527.050049,GOOG 396 | 143,2020-10-21,1573.329956,GOOG 397 | 144,2020-10-22,1593.050049,GOOG 398 | 145,2020-10-23,1626.069946,GOOG 399 | 146,2020-10-26,1625.01001,GOOG 400 | 147,2020-10-27,1595.670044,GOOG 401 | 148,2020-10-28,1559.73999,GOOG 402 | 149,2020-10-29,1522.359985,GOOG 403 | 150,2020-10-30,1672.109985,GOOG 404 | 151,2020-11-02,1628.160034,GOOG 405 | 152,2020-11-03,1631.780029,GOOG 406 | 153,2020-11-04,1710.280029,GOOG 407 | 154,2020-11-05,1781.0,GOOG 408 | 155,2020-11-06,1753.949951,GOOG 409 | 156,2020-11-09,1790.9000239999998,GOOG 410 | 157,2020-11-10,1731.089966,GOOG 411 | 158,2020-11-11,1750.0,GOOG 412 | 159,2020-11-12,1747.630005,GOOG 413 | 160,2020-11-13,1757.630005,GOOG 414 | 161,2020-11-16,1771.699951,GOOG 415 | 162,2020-11-17,1776.939941,GOOG 416 | 163,2020-11-18,1765.22998,GOOG 417 | 164,2020-11-19,1738.380005,GOOG 418 | 165,2020-11-20,1765.209961,GOOG 419 | 166,2020-11-23,1749.5999760000002,GOOG 420 | 167,2020-11-24,1730.5,GOOG 421 | 168,2020-11-25,1772.890015,GOOG 422 | 169,2020-11-27,1773.089966,GOOG 423 | 170,2020-11-30,1781.18396,GOOG 424 | 171,2020-12-01,1774.369995,GOOG 425 | 172,2020-12-02,1798.0999760000002,GOOG 426 | 173,2020-12-03,1824.0100100000002,GOOG 427 | 174,2020-12-04,1824.52002,GOOG 428 | 175,2020-12-07,1819.0,GOOG 429 | 176,2020-12-08,1810.0999760000002,GOOG 430 | 177,2020-12-09,1812.0100100000002,GOOG 431 | 178,2020-12-10,1769.800049,GOOG 432 | 179,2020-12-11,1763.060059,GOOG 433 | 180,2020-12-14,1775.0,GOOG 434 | 181,2020-12-15,1764.4200440000002,GOOG 435 | 182,2020-12-16,1772.880005,GOOG 436 | 183,2020-12-17,1768.5100100000002,GOOG 437 | 184,2020-12-18,1754.180054,GOOG 438 | 185,2020-12-21,1713.5100100000002,GOOG 439 | 186,2020-12-22,1734.430054,GOOG 440 | 187,2020-12-23,1728.109985,GOOG 441 | 188,2020-12-24,1735.0,GOOG 442 | 189,2020-12-28,1751.6350100000002,GOOG 443 | 190,2020-12-29,1787.790039,GOOG 444 | 191,2020-12-30,1762.0100100000002,GOOG 445 | 192,2020-12-31,1735.4200440000002,GOOG 446 | 193,2021-01-04,1757.540039,GOOG 447 | 194,2021-01-05,1725.0,GOOG 448 | 195,2021-01-06,1702.630005,GOOG 449 | 196,2021-01-07,1740.060059,GOOG 450 | 197,2021-01-08,1787.97998,GOOG 451 | 198,2021-01-11,1786.069946,GOOG 452 | 199,2021-01-12,1753.9200440000002,GOOG 453 | 200,2021-01-13,1738.5799559999998,GOOG 454 | 201,2021-01-14,1753.619995,GOOG 455 | 202,2021-01-15,1738.189941,GOOG 456 | 203,2021-01-19,1752.25,GOOG 457 | 204,2021-01-20,1831.459961,GOOG 458 | 205,2021-01-21,1898.0,GOOG 459 | 206,2021-01-22,1895.680054,GOOG 460 | 207,2021-01-25,1920.6700440000002,GOOG 461 | 208,2021-01-26,1888.839966,GOOG 462 | 209,2021-01-27,1882.530029,GOOG 463 | 210,2021-01-28,1843.939941,GOOG 464 | 211,2021-01-29,1846.1700440000002,GOOG 465 | 212,2021-02-01,1853.569946,GOOG 466 | 213,2021-02-02,1922.560059,GOOG 467 | 214,2021-02-03,2073.0,GOOG 468 | 215,2021-02-04,2068.889893,GOOG 469 | 216,2021-02-05,2070.0,GOOG 470 | 217,2021-02-08,2105.909912,GOOG 471 | 218,2021-02-09,2078.540039,GOOG 472 | 219,2021-02-10,2094.209961,GOOG 473 | 220,2021-02-11,2099.51001,GOOG 474 | 221,2021-02-12,2090.25,GOOG 475 | 222,2021-02-16,2104.360107,GOOG 476 | 223,2021-02-17,2100.0,GOOG 477 | 224,2021-02-18,2110.389893,GOOG 478 | 225,2021-02-19,2119.27002,GOOG 479 | 226,2021-02-22,2067.0,GOOG 480 | 227,2021-02-23,2025.0100100000002,GOOG 481 | 228,2021-02-24,2041.8299559999998,GOOG 482 | 229,2021-02-25,2067.449951,GOOG 483 | 230,2021-02-26,2050.52002,GOOG 484 | 231,2021-03-01,2056.52002,GOOG 485 | 232,2021-03-02,2076.189941,GOOG 486 | 233,2021-03-03,2067.209961,GOOG 487 | 234,2021-03-04,2023.369995,GOOG 488 | 235,2021-03-05,2073.1201170000004,GOOG 489 | 236,2021-03-08,2101.1298829999996,GOOG 490 | 237,2021-03-09,2070.0,GOOG 491 | 238,2021-03-10,2071.76001,GOOG 492 | 239,2021-03-11,2074.060059,GOOG 493 | 240,2021-03-12,2085.0,GOOG 494 | 241,2021-03-15,2062.300049,GOOG 495 | 242,2021-03-16,2078.98999,GOOG 496 | 243,2021-03-17,2076.030029,GOOG 497 | 244,2021-03-18,2061.0,GOOG 498 | 245,2021-03-19,2042.050049,GOOG 499 | 246,2021-03-22,2041.839966,GOOG 500 | 247,2021-03-23,2051.699951,GOOG 501 | 248,2021-03-24,2065.3701170000004,GOOG 502 | 249,2021-03-25,2044.810059,GOOG 503 | 250,2021-03-26,2038.859985,GOOG 504 | 0,2020-03-30,102.052002,TSLA 505 | 1,2020-03-31,100.25,TSLA 506 | 2,2020-04-01,100.800003,TSLA 507 | 3,2020-04-02,96.206001,TSLA 508 | 4,2020-04-03,101.900002,TSLA 509 | 5,2020-04-06,102.239998,TSLA 510 | 6,2020-04-07,109.0,TSLA 511 | 7,2020-04-08,110.839996,TSLA 512 | 8,2020-04-09,112.417999,TSLA 513 | 9,2020-04-13,118.031998,TSLA 514 | 10,2020-04-14,139.794006,TSLA 515 | 11,2020-04-15,148.399994,TSLA 516 | 12,2020-04-16,143.388,TSLA 517 | 13,2020-04-17,154.455994,TSLA 518 | 14,2020-04-20,146.53999299999998,TSLA 519 | 15,2020-04-21,146.024002,TSLA 520 | 16,2020-04-22,140.796005,TSLA 521 | 17,2020-04-23,145.520004,TSLA 522 | 18,2020-04-24,142.162003,TSLA 523 | 19,2020-04-27,147.522003,TSLA 524 | 20,2020-04-28,159.128006,TSLA 525 | 21,2020-04-29,158.033997,TSLA 526 | 22,2020-04-30,171.037994,TSLA 527 | 23,2020-05-01,151.0,TSLA 528 | 24,2020-05-04,140.199997,TSLA 529 | 25,2020-05-05,157.957993,TSLA 530 | 26,2020-05-06,155.300003,TSLA 531 | 27,2020-05-07,155.442001,TSLA 532 | 28,2020-05-08,158.753998,TSLA 533 | 29,2020-05-11,158.102005,TSLA 534 | 30,2020-05-12,165.399994,TSLA 535 | 31,2020-05-13,164.166,TSLA 536 | 32,2020-05-14,156.0,TSLA 537 | 33,2020-05-15,158.070007,TSLA 538 | 34,2020-05-18,165.556,TSLA 539 | 35,2020-05-19,163.033997,TSLA 540 | 36,2020-05-20,164.100006,TSLA 541 | 37,2020-05-21,163.199997,TSLA 542 | 38,2020-05-22,164.434006,TSLA 543 | 39,2020-05-26,166.899994,TSLA 544 | 40,2020-05-27,164.171997,TSLA 545 | 41,2020-05-28,162.701996,TSLA 546 | 42,2020-05-29,161.75,TSLA 547 | 43,2020-06-01,171.600006,TSLA 548 | 44,2020-06-02,178.940002,TSLA 549 | 45,2020-06-03,177.62399299999998,TSLA 550 | 46,2020-06-04,177.975998,TSLA 551 | 47,2020-06-05,175.567993,TSLA 552 | 48,2020-06-08,183.800003,TSLA 553 | 49,2020-06-09,188.001999,TSLA 554 | 50,2020-06-10,198.37600700000002,TSLA 555 | 51,2020-06-11,198.03999299999998,TSLA 556 | 52,2020-06-12,196.0,TSLA 557 | 53,2020-06-15,183.557999,TSLA 558 | 54,2020-06-16,202.369995,TSLA 559 | 55,2020-06-17,197.542007,TSLA 560 | 56,2020-06-18,200.600006,TSLA 561 | 57,2020-06-19,202.556,TSLA 562 | 58,2020-06-22,199.990005,TSLA 563 | 59,2020-06-23,199.776001,TSLA 564 | 60,2020-06-24,198.82200600000002,TSLA 565 | 61,2020-06-25,190.854004,TSLA 566 | 62,2020-06-26,198.955994,TSLA 567 | 63,2020-06-29,193.80200200000002,TSLA 568 | 64,2020-06-30,201.300003,TSLA 569 | 65,2020-07-01,216.600006,TSLA 570 | 66,2020-07-02,244.29600499999998,TSLA 571 | 67,2020-07-06,255.33799700000003,TSLA 572 | 68,2020-07-07,281.00201400000003,TSLA 573 | 69,2020-07-08,281.0,TSLA 574 | 70,2020-07-09,279.39801,TSLA 575 | 71,2020-07-10,279.200012,TSLA 576 | 72,2020-07-13,331.799988,TSLA 577 | 73,2020-07-14,311.200012,TSLA 578 | 74,2020-07-15,308.600006,TSLA 579 | 75,2020-07-16,295.432007,TSLA 580 | 76,2020-07-17,302.690002,TSLA 581 | 77,2020-07-20,303.802002,TSLA 582 | 78,2020-07-21,327.985992,TSLA 583 | 79,2020-07-22,319.799988,TSLA 584 | 80,2020-07-23,335.790009,TSLA 585 | 81,2020-07-24,283.201996,TSLA 586 | 82,2020-07-27,287.0,TSLA 587 | 83,2020-07-28,300.799988,TSLA 588 | 84,2020-07-29,300.200012,TSLA 589 | 85,2020-07-30,297.600006,TSLA 590 | 86,2020-07-31,303.0,TSLA 591 | 87,2020-08-03,289.839996,TSLA 592 | 88,2020-08-04,299.00201400000003,TSLA 593 | 89,2020-08-05,298.597992,TSLA 594 | 90,2020-08-06,298.16598500000003,TSLA 595 | 91,2020-08-07,299.90799,TSLA 596 | 92,2020-08-10,289.600006,TSLA 597 | 93,2020-08-11,279.200012,TSLA 598 | 94,2020-08-12,294.0,TSLA 599 | 95,2020-08-13,322.200012,TSLA 600 | 96,2020-08-14,332.99798599999997,TSLA 601 | 97,2020-08-17,335.399994,TSLA 602 | 98,2020-08-18,379.798004,TSLA 603 | 99,2020-08-19,373.0,TSLA 604 | 100,2020-08-20,372.135986,TSLA 605 | 101,2020-08-21,408.951996,TSLA 606 | 102,2020-08-24,425.256012,TSLA 607 | 103,2020-08-25,394.977997,TSLA 608 | 104,2020-08-26,412.0,TSLA 609 | 105,2020-08-27,436.09200999999996,TSLA 610 | 106,2020-08-28,459.02398700000003,TSLA 611 | 107,2020-08-31,444.60998499999994,TSLA 612 | 108,2020-09-01,502.14001500000006,TSLA 613 | 109,2020-09-02,478.98999000000003,TSLA 614 | 110,2020-09-03,407.230011,TSLA 615 | 111,2020-09-04,402.809998,TSLA 616 | 112,2020-09-08,356.0,TSLA 617 | 113,2020-09-09,356.600006,TSLA 618 | 114,2020-09-10,386.209991,TSLA 619 | 115,2020-09-11,381.940002,TSLA 620 | 116,2020-09-14,380.950012,TSLA 621 | 117,2020-09-15,436.55999800000006,TSLA 622 | 118,2020-09-16,439.869995,TSLA 623 | 119,2020-09-17,415.600006,TSLA 624 | 120,2020-09-18,447.94000199999994,TSLA 625 | 121,2020-09-21,453.130005,TSLA 626 | 122,2020-09-22,429.60000599999995,TSLA 627 | 123,2020-09-23,405.160004,TSLA 628 | 124,2020-09-24,363.799988,TSLA 629 | 125,2020-09-25,393.47000099999997,TSLA 630 | 126,2020-09-28,424.619995,TSLA 631 | 127,2020-09-29,416.0,TSLA 632 | 128,2020-09-30,421.32000700000003,TSLA 633 | 129,2020-10-01,440.76000999999997,TSLA 634 | 130,2020-10-02,421.39001500000006,TSLA 635 | 131,2020-10-05,423.35000599999995,TSLA 636 | 132,2020-10-06,423.790009,TSLA 637 | 133,2020-10-07,419.869995,TSLA 638 | 134,2020-10-08,438.44000199999994,TSLA 639 | 135,2020-10-09,430.130005,TSLA 640 | 136,2020-10-12,442.0,TSLA 641 | 137,2020-10-13,443.35000599999995,TSLA 642 | 138,2020-10-14,449.77999900000003,TSLA 643 | 139,2020-10-15,450.30999800000006,TSLA 644 | 140,2020-10-16,454.44000199999994,TSLA 645 | 141,2020-10-19,446.23999000000003,TSLA 646 | 142,2020-10-20,431.75,TSLA 647 | 143,2020-10-21,422.700012,TSLA 648 | 144,2020-10-22,441.920013,TSLA 649 | 145,2020-10-23,421.839996,TSLA 650 | 146,2020-10-26,411.630005,TSLA 651 | 147,2020-10-27,423.76000999999997,TSLA 652 | 148,2020-10-28,416.480011,TSLA 653 | 149,2020-10-29,409.959991,TSLA 654 | 150,2020-10-30,406.899994,TSLA 655 | 151,2020-11-02,394.0,TSLA 656 | 152,2020-11-03,409.730011,TSLA 657 | 153,2020-11-04,430.619995,TSLA 658 | 154,2020-11-05,428.299988,TSLA 659 | 155,2020-11-06,436.10000599999995,TSLA 660 | 156,2020-11-09,439.5,TSLA 661 | 157,2020-11-10,420.089996,TSLA 662 | 158,2020-11-11,416.450012,TSLA 663 | 159,2020-11-12,415.049988,TSLA 664 | 160,2020-11-13,410.850006,TSLA 665 | 161,2020-11-16,408.929993,TSLA 666 | 162,2020-11-17,460.170013,TSLA 667 | 163,2020-11-18,448.35000599999995,TSLA 668 | 164,2020-11-19,492.0,TSLA 669 | 165,2020-11-20,497.98999000000003,TSLA 670 | 166,2020-11-23,503.5,TSLA 671 | 167,2020-11-24,540.400024,TSLA 672 | 168,2020-11-25,550.0599980000001,TSLA 673 | 169,2020-11-27,581.159973,TSLA 674 | 170,2020-11-30,602.210022,TSLA 675 | 171,2020-12-01,597.590027,TSLA 676 | 172,2020-12-02,556.4400019999999,TSLA 677 | 173,2020-12-03,590.02002,TSLA 678 | 174,2020-12-04,591.01001,TSLA 679 | 175,2020-12-07,604.919983,TSLA 680 | 176,2020-12-08,625.51001,TSLA 681 | 177,2020-12-09,653.6900019999999,TSLA 682 | 178,2020-12-10,574.369995,TSLA 683 | 179,2020-12-11,615.01001,TSLA 684 | 180,2020-12-14,619.0,TSLA 685 | 181,2020-12-15,643.280029,TSLA 686 | 182,2020-12-16,628.22998,TSLA 687 | 183,2020-12-17,628.1900019999999,TSLA 688 | 184,2020-12-18,668.900024,TSLA 689 | 185,2020-12-21,666.23999,TSLA 690 | 186,2020-12-22,648.0,TSLA 691 | 187,2020-12-23,632.200012,TSLA 692 | 188,2020-12-24,642.98999,TSLA 693 | 189,2020-12-28,674.51001,TSLA 694 | 190,2020-12-29,661.0,TSLA 695 | 191,2020-12-30,672.0,TSLA 696 | 192,2020-12-31,699.98999,TSLA 697 | 193,2021-01-04,719.460022,TSLA 698 | 194,2021-01-05,723.659973,TSLA 699 | 195,2021-01-06,758.48999,TSLA 700 | 196,2021-01-07,777.630005,TSLA 701 | 197,2021-01-08,856.0,TSLA 702 | 198,2021-01-11,849.400024,TSLA 703 | 199,2021-01-12,831.0,TSLA 704 | 200,2021-01-13,852.76001,TSLA 705 | 201,2021-01-14,843.3900150000001,TSLA 706 | 202,2021-01-15,852.0,TSLA 707 | 203,2021-01-19,837.799988,TSLA 708 | 204,2021-01-20,858.73999,TSLA 709 | 205,2021-01-21,855.0,TSLA 710 | 206,2021-01-22,834.3099980000001,TSLA 711 | 207,2021-01-25,855.0,TSLA 712 | 208,2021-01-26,891.3800050000001,TSLA 713 | 209,2021-01-27,870.349976,TSLA 714 | 210,2021-01-28,820.0,TSLA 715 | 211,2021-01-29,830.0,TSLA 716 | 212,2021-02-01,814.289978,TSLA 717 | 213,2021-02-02,844.679993,TSLA 718 | 214,2021-02-03,877.0200199999999,TSLA 719 | 215,2021-02-04,855.0,TSLA 720 | 216,2021-02-05,845.0,TSLA 721 | 217,2021-02-08,869.669983,TSLA 722 | 218,2021-02-09,855.1199949999999,TSLA 723 | 219,2021-02-10,843.6400150000001,TSLA 724 | 220,2021-02-11,812.4400019999999,TSLA 725 | 221,2021-02-12,801.26001,TSLA 726 | 222,2021-02-16,818.0,TSLA 727 | 223,2021-02-17,779.090027,TSLA 728 | 224,2021-02-18,780.900024,TSLA 729 | 225,2021-02-19,795.0,TSLA 730 | 226,2021-02-22,762.6400150000001,TSLA 731 | 227,2021-02-23,662.130005,TSLA 732 | 228,2021-02-24,711.849976,TSLA 733 | 229,2021-02-25,726.150024,TSLA 734 | 230,2021-02-26,700.0,TSLA 735 | 231,2021-03-01,690.1099849999999,TSLA 736 | 232,2021-03-02,718.280029,TSLA 737 | 233,2021-03-03,687.98999,TSLA 738 | 234,2021-03-04,655.799988,TSLA 739 | 235,2021-03-05,626.0599980000001,TSLA 740 | 236,2021-03-08,600.549988,TSLA 741 | 237,2021-03-09,608.179993,TSLA 742 | 238,2021-03-10,700.299988,TSLA 743 | 239,2021-03-11,699.400024,TSLA 744 | 240,2021-03-12,670.0,TSLA 745 | 241,2021-03-15,694.090027,TSLA 746 | 242,2021-03-16,703.349976,TSLA 747 | 243,2021-03-17,656.869995,TSLA 748 | 244,2021-03-18,684.289978,TSLA 749 | 245,2021-03-19,646.599976,TSLA 750 | 246,2021-03-22,684.590027,TSLA 751 | 247,2021-03-23,675.77002,TSLA 752 | 248,2021-03-24,667.909973,TSLA 753 | 249,2021-03-25,613.0,TSLA 754 | 250,2021-03-26,641.869995,TSLA 755 | -------------------------------------------------------------------------------- /toronto-weather.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/datagy/mediumdata/11aeaf83ccc61f970caff2fb8943df1f611be789/toronto-weather.xlsx 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