Divija89/Tips-predictor-model1
1
1{2 "cells": [3 {4 "cell_type": "code",5 "execution_count": 51,6 "id": "0d7736cd",7 "metadata": {},8 "outputs": [9 {10 "name": "stdout",11 "output_type": "stream",12 "text": [13 "hi\n"14 ]15 }16 ],17 "source": [18 "print(\"hi\")"19 ]20 },21 {22 "cell_type": "code",23 "execution_count": 11,24 "id": "0e468f0f",25 "metadata": {},26 "outputs": [27 {28 "data": {29 "text/plain": [30 "'1.6.1'"31 ]32 },33 "execution_count": 11,34 "metadata": {},35 "output_type": "execute_result"36 }37 ],38 "source": [39 "sklearn.__version__"40 ]41 },42 {43 "cell_type": "code",44 "execution_count": 10,45 "id": "d8e69082",46 "metadata": {},47 "outputs": [],48 "source": [49 "import sklearn"50 ]51 },52 {53 "cell_type": "code",54 "execution_count": null,55 "id": "e47ebe41",56 "metadata": {},57 "outputs": [],58 "source": [59 "import numpy as np\n",60 "import matplotlib.pyplot as plt\n",61 "import seaborn as sns\n",62 "from sklearn.linear_model import LinearRegression\n",63 "from sklearn.preprocessing import OneHotEncoder\n",64 "from sklearn.compose import ColumnTransformer\n",65 "from sklearn.pipeline import Pipeline\n",66 "import joblib\n"67 ]68 },69 {70 "cell_type": "code",71 "execution_count": null,72 "id": "9577088d",73 "metadata": {},74 "outputs": [],75 "source": []76 },77 {78 "cell_type": "code",79 "execution_count": 54,80 "id": "3af38654",81 "metadata": {},82 "outputs": [],83 "source": [84 "df = sns.load_dataset('taxis')"85 ]86 },87 {88 "cell_type": "code",89 "execution_count": 55,90 "id": "b6feea8e",91 "metadata": {},92 "outputs": [93 {94 "data": {95 "text/html": [96 "<div>\n",97 "<style scoped>\n",98 " .dataframe tbody tr th:only-of-type {\n",99 " vertical-align: middle;\n",100 " }\n",101 "\n",102 " .dataframe tbody tr th {\n",103 " vertical-align: top;\n",104 " }\n",105 "\n",106 " .dataframe thead th {\n",107 " text-align: right;\n",108 " }\n",109 "</style>\n",110 "<table border=\"1\" class=\"dataframe\">\n",111 " <thead>\n",112 " <tr style=\"text-align: right;\">\n",113 " <th></th>\n",114 " <th>pickup</th>\n",115 " <th>dropoff</th>\n",116 " <th>passengers</th>\n",117 " <th>distance</th>\n",118 " <th>fare</th>\n",119 " <th>tip</th>\n",120 " <th>tolls</th>\n",121 " <th>total</th>\n",122 " <th>color</th>\n",123 " <th>payment</th>\n",124 " <th>pickup_zone</th>\n",125 " <th>dropoff_zone</th>\n",126 " <th>pickup_borough</th>\n",127 " <th>dropoff_borough</th>\n",128 " </tr>\n",129 " </thead>\n",130 " <tbody>\n",131 " <tr>\n",132 " <th>0</th>\n",133 " <td>2019-03-23 20:21:09</td>\n",134 " <td>2019-03-23 20:27:24</td>\n",135 " <td>1</td>\n",136 " <td>1.60</td>\n",137 " <td>7.0</td>\n",138 " <td>2.15</td>\n",139 " <td>0.0</td>\n",140 " <td>12.95</td>\n",141 " <td>yellow</td>\n",142 " <td>credit card</td>\n",143 " <td>Lenox Hill West</td>\n",144 " <td>UN/Turtle Bay South</td>\n",145 " <td>Manhattan</td>\n",146 " <td>Manhattan</td>\n",147 " </tr>\n",148 " <tr>\n",149 " <th>1</th>\n",150 " <td>2019-03-04 16:11:55</td>\n",151 " <td>2019-03-04 16:19:00</td>\n",152 " <td>1</td>\n",153 " <td>0.79</td>\n",154 " <td>5.0</td>\n",155 " <td>0.00</td>\n",156 " <td>0.0</td>\n",157 " <td>9.30</td>\n",158 " <td>yellow</td>\n",159 " <td>cash</td>\n",160 " <td>Upper West Side South</td>\n",161 " <td>Upper West Side South</td>\n",162 " <td>Manhattan</td>\n",163 " <td>Manhattan</td>\n",164 " </tr>\n",165 " <tr>\n",166 " <th>2</th>\n",167 " <td>2019-03-27 17:53:01</td>\n",168 " <td>2019-03-27 18:00:25</td>\n",169 " <td>1</td>\n",170 " <td>1.37</td>\n",171 " <td>7.5</td>\n",172 " <td>2.36</td>\n",173 " <td>0.0</td>\n",174 " <td>14.16</td>\n",175 " <td>yellow</td>\n",176 " <td>credit card</td>\n",177 " <td>Alphabet City</td>\n",178 " <td>West Village</td>\n",179 " <td>Manhattan</td>\n",180 " <td>Manhattan</td>\n",181 " </tr>\n",182 " <tr>\n",183 " <th>3</th>\n",184 " <td>2019-03-10 01:23:59</td>\n",185 " <td>2019-03-10 01:49:51</td>\n",186 " <td>1</td>\n",187 " <td>7.70</td>\n",188 " <td>27.0</td>\n",189 " <td>6.15</td>\n",190 " <td>0.0</td>\n",191 " <td>36.95</td>\n",192 " <td>yellow</td>\n",193 " <td>credit card</td>\n",194 " <td>Hudson Sq</td>\n",195 " <td>Yorkville West</td>\n",196 " <td>Manhattan</td>\n",197 " <td>Manhattan</td>\n",198 " </tr>\n",199 " <tr>\n",200 " <th>4</th>\n",201 " <td>2019-03-30 13:27:42</td>\n",202 " <td>2019-03-30 13:37:14</td>\n",203 " <td>3</td>\n",204 " <td>2.16</td>\n",205 " <td>9.0</td>\n",206 " <td>1.10</td>\n",207 " <td>0.0</td>\n",208 " <td>13.40</td>\n",209 " <td>yellow</td>\n",210 " <td>credit card</td>\n",211 " <td>Midtown East</td>\n",212 " <td>Yorkville West</td>\n",213 " <td>Manhattan</td>\n",214 " <td>Manhattan</td>\n",215 " </tr>\n",216 " <tr>\n",217 " <th>...</th>\n",218 " <td>...</td>\n",219 " <td>...</td>\n",220 " <td>...</td>\n",221 " <td>...</td>\n",222 " <td>...</td>\n",223 " <td>...</td>\n",224 " <td>...</td>\n",225 " <td>...</td>\n",226 " <td>...</td>\n",227 " <td>...</td>\n",228 " <td>...</td>\n",229 " <td>...</td>\n",230 " <td>...</td>\n",231 " <td>...</td>\n",232 " </tr>\n",233 " <tr>\n",234 " <th>6428</th>\n",235 " <td>2019-03-31 09:51:53</td>\n",236 " <td>2019-03-31 09:55:27</td>\n",237 " <td>1</td>\n",238 " <td>0.75</td>\n",239 " <td>4.5</td>\n",240 " <td>1.06</td>\n",241 " <td>0.0</td>\n",242 " <td>6.36</td>\n",243 " <td>green</td>\n",244 " <td>credit card</td>\n",245 " <td>East Harlem North</td>\n",246 " <td>Central Harlem North</td>\n",247 " <td>Manhattan</td>\n",248 " <td>Manhattan</td>\n",249 " </tr>\n",250 " <tr>\n",251 " <th>6429</th>\n",252 " <td>2019-03-31 17:38:00</td>\n",253 " <td>2019-03-31 18:34:23</td>\n",254 " <td>1</td>\n",255 " <td>18.74</td>\n",256 " <td>58.0</td>\n",257 " <td>0.00</td>\n",258 " <td>0.0</td>\n",259 " <td>58.80</td>\n",260 " <td>green</td>\n",261 " <td>credit card</td>\n",262 " <td>Jamaica</td>\n",263 " <td>East Concourse/Concourse Village</td>\n",264 " <td>Queens</td>\n",265 " <td>Bronx</td>\n",266 " </tr>\n",267 " <tr>\n",268 " <th>6430</th>\n",269 " <td>2019-03-23 22:55:18</td>\n",270 " <td>2019-03-23 23:14:25</td>\n",271 " <td>1</td>\n",272 " <td>4.14</td>\n",273 " <td>16.0</td>\n",274 " <td>0.00</td>\n",275 " <td>0.0</td>\n",276 " <td>17.30</td>\n",277 " <td>green</td>\n",278 " <td>cash</td>\n",279 " <td>Crown Heights North</td>\n",280 " <td>Bushwick North</td>\n",281 " <td>Brooklyn</td>\n",282 " <td>Brooklyn</td>\n",283 " </tr>\n",284 " <tr>\n",285 " <th>6431</th>\n",286 " <td>2019-03-04 10:09:25</td>\n",287 " <td>2019-03-04 10:14:29</td>\n",288 " <td>1</td>\n",289 " <td>1.12</td>\n",290 " <td>6.0</td>\n",291 " <td>0.00</td>\n",292 " <td>0.0</td>\n",293 " <td>6.80</td>\n",294 " <td>green</td>\n",295 " <td>credit card</td>\n",296 " <td>East New York</td>\n",297 " <td>East Flatbush/Remsen Village</td>\n",298 " <td>Brooklyn</td>\n",299 " <td>Brooklyn</td>\n",300 " </tr>\n",301 " <tr>\n",302 " <th>6432</th>\n",303 " <td>2019-03-13 19:31:22</td>\n",304 " <td>2019-03-13 19:48:02</td>\n",305 " <td>1</td>\n",306 " <td>3.85</td>\n",307 " <td>15.0</td>\n",308 " <td>3.36</td>\n",309 " <td>0.0</td>\n",310 " <td>20.16</td>\n",311 " <td>green</td>\n",312 " <td>credit card</td>\n",313 " <td>Boerum Hill</td>\n",314 " <td>Windsor Terrace</td>\n",315 " <td>Brooklyn</td>\n",316 " <td>Brooklyn</td>\n",317 " </tr>\n",318 " </tbody>\n",319 "</table>\n",320 "<p>6433 rows × 14 columns</p>\n",321 "</div>"322 ],323 "text/plain": [324 " pickup dropoff passengers distance fare \\\n",325 "0 2019-03-23 20:21:09 2019-03-23 20:27:24 1 1.60 7.0 \n",326 "1 2019-03-04 16:11:55 2019-03-04 16:19:00 1 0.79 5.0 \n",327 "2 2019-03-27 17:53:01 2019-03-27 18:00:25 1 1.37 7.5 \n",328 "3 2019-03-10 01:23:59 2019-03-10 01:49:51 1 7.70 27.0 \n",329 "4 2019-03-30 13:27:42 2019-03-30 13:37:14 3 2.16 9.0 \n",330 "... ... ... ... ... ... \n",331 "6428 2019-03-31 09:51:53 2019-03-31 09:55:27 1 0.75 4.5 \n",332 "6429 2019-03-31 17:38:00 2019-03-31 18:34:23 1 18.74 58.0 \n",333 "6430 2019-03-23 22:55:18 2019-03-23 23:14:25 1 4.14 16.0 \n",334 "6431 2019-03-04 10:09:25 2019-03-04 10:14:29 1 1.12 6.0 \n",335 "6432 2019-03-13 19:31:22 2019-03-13 19:48:02 1 3.85 15.0 \n",336 "\n",337 " tip tolls total color payment pickup_zone \\\n",338 "0 2.15 0.0 12.95 yellow credit card Lenox Hill West \n",339 "1 0.00 0.0 9.30 yellow cash Upper West Side South \n",340 "2 2.36 0.0 14.16 yellow credit card Alphabet City \n",341 "3 6.15 0.0 36.95 yellow credit card Hudson Sq \n",342 "4 1.10 0.0 13.40 yellow credit card Midtown East \n",343 "... ... ... ... ... ... ... \n",344 "6428 1.06 0.0 6.36 green credit card East Harlem North \n",345 "6429 0.00 0.0 58.80 green credit card Jamaica \n",346 "6430 0.00 0.0 17.30 green cash Crown Heights North \n",347 "6431 0.00 0.0 6.80 green credit card East New York \n",348 "6432 3.36 0.0 20.16 green credit card Boerum Hill \n",349 "\n",350 " dropoff_zone pickup_borough dropoff_borough \n",351 "0 UN/Turtle Bay South Manhattan Manhattan \n",352 "1 Upper West Side South Manhattan Manhattan \n",353 "2 West Village Manhattan Manhattan \n",354 "3 Yorkville West Manhattan Manhattan \n",355 "4 Yorkville West Manhattan Manhattan \n",356 "... ... ... ... \n",357 "6428 Central Harlem North Manhattan Manhattan \n",358 "6429 East Concourse/Concourse Village Queens Bronx \n",359 "6430 Bushwick North Brooklyn Brooklyn \n",360 "6431 East Flatbush/Remsen Village Brooklyn Brooklyn \n",361 "6432 Windsor Terrace Brooklyn Brooklyn \n",362 "\n",363 "[6433 rows x 14 columns]"364 ]365 },366 "execution_count": 55,367 "metadata": {},368 "output_type": "execute_result"369 }370 ],371 "source": [372 "df"373 ]374 },375 {376 "cell_type": "code",377 "execution_count": 56,378 "id": "16f6c080",379 "metadata": {},380 "outputs": [381 {382 "name": "stdout",383 "output_type": "stream",384 "text": [385 "<class 'pandas.core.frame.DataFrame'>\n",386 "RangeIndex: 6433 entries, 0 to 6432\n",387 "Data columns (total 14 columns):\n",388 " # Column Non-Null Count Dtype \n",389 "--- ------ -------------- ----- \n",390 " 0 pickup 6433 non-null datetime64[ns]\n",391 " 1 dropoff 6433 non-null datetime64[ns]\n",392 " 2 passengers 6433 non-null int64 \n",393 " 3 distance 6433 non-null float64 \n",394 " 4 fare 6433 non-null float64 \n",395 " 5 tip 6433 non-null float64 \n",396 " 6 tolls 6433 non-null float64 \n",397 " 7 total 6433 non-null float64 \n",398 " 8 color 6433 non-null object \n",399 " 9 payment 6389 non-null object \n",400 " 10 pickup_zone 6407 non-null object \n",401 " 11 dropoff_zone 6388 non-null object \n",402 " 12 pickup_borough 6407 non-null object \n",403 " 13 dropoff_borough 6388 non-null object \n",404 "dtypes: datetime64[ns](2), float64(5), int64(1), object(6)\n",405 "memory usage: 703.7+ KB\n"406 ]407 }408 ],409 "source": [410 "df.info()"411 ]412 },413 {414 "cell_type": "code",415 "execution_count": 57,416 "id": "ffa6ebc8",417 "metadata": {},418 "outputs": [419 {420 "data": {421 "text/html": [422 "<div>\n",423 "<style scoped>\n",424 " .dataframe tbody tr th:only-of-type {\n",425 " vertical-align: middle;\n",426 " }\n",427 "\n",428 " .dataframe tbody tr th {\n",429 " vertical-align: top;\n",430 " }\n",431 "\n",432 " .dataframe thead th {\n",433 " text-align: right;\n",434 " }\n",435 "</style>\n",436 "<table border=\"1\" class=\"dataframe\">\n",437 " <thead>\n",438 " <tr style=\"text-align: right;\">\n",439 " <th></th>\n",440 " <th>passengers</th>\n",441 " <th>distance</th>\n",442 " <th>fare</th>\n",443 " <th>tip</th>\n",444 " <th>tolls</th>\n",445 " <th>total</th>\n",446 " </tr>\n",447 " </thead>\n",448 " <tbody>\n",449 " <tr>\n",450 " <th>count</th>\n",451 " <td>6433.000000</td>\n",452 " <td>6433.000000</td>\n",453 " <td>6433.000000</td>\n",454 " <td>6433.00000</td>\n",455 " <td>6433.000000</td>\n",456 " <td>6433.000000</td>\n",457 " </tr>\n",458 " <tr>\n",459 " <th>mean</th>\n",460 " <td>1.539251</td>\n",461 " <td>3.024617</td>\n",462 " <td>13.091073</td>\n",463 " <td>1.97922</td>\n",464 " <td>0.325273</td>\n",465 " <td>18.517794</td>\n",466 " </tr>\n",467 " <tr>\n",468 " <th>std</th>\n",469 " <td>1.203768</td>\n",470 " <td>3.827867</td>\n",471 " <td>11.551804</td>\n",472 " <td>2.44856</td>\n",473 " <td>1.415267</td>\n",474 " <td>13.815570</td>\n",475 " </tr>\n",476 " <tr>\n",477 " <th>min</th>\n",478 " <td>0.000000</td>\n",479 " <td>0.000000</td>\n",480 " <td>1.000000</td>\n",481 " <td>0.00000</td>\n",482 " <td>0.000000</td>\n",483 " <td>1.300000</td>\n",484 " </tr>\n",485 " <tr>\n",486 " <th>25%</th>\n",487 " <td>1.000000</td>\n",488 " <td>0.980000</td>\n",489 " <td>6.500000</td>\n",490 " <td>0.00000</td>\n",491 " <td>0.000000</td>\n",492 " <td>10.800000</td>\n",493 " </tr>\n",494 " <tr>\n",495 " <th>50%</th>\n",496 " <td>1.000000</td>\n",497 " <td>1.640000</td>\n",498 " <td>9.500000</td>\n",499 " <td>1.70000</td>\n",500 " <td>0.000000</td>\n",501 " <td>14.160000</td>\n",502 " </tr>\n",503 " <tr>\n",504 " <th>75%</th>\n",505 " <td>2.000000</td>\n",506 " <td>3.210000</td>\n",507 " <td>15.000000</td>\n",508 " <td>2.80000</td>\n",509 " <td>0.000000</td>\n",510 " <td>20.300000</td>\n",511 " </tr>\n",512 " <tr>\n",513 " <th>max</th>\n",514 " <td>6.000000</td>\n",515 " <td>36.700000</td>\n",516 " <td>150.000000</td>\n",517 " <td>33.20000</td>\n",518 " <td>24.020000</td>\n",519 " <td>174.820000</td>\n",520 " </tr>\n",521 " </tbody>\n",522 "</table>\n",523 "</div>"524 ],525 "text/plain": [526 " passengers distance fare tip tolls \\\n",527 "count 6433.000000 6433.000000 6433.000000 6433.00000 6433.000000 \n",528 "mean 1.539251 3.024617 13.091073 1.97922 0.325273 \n",529 "std 1.203768 3.827867 11.551804 2.44856 1.415267 \n",530 "min 0.000000 0.000000 1.000000 0.00000 0.000000 \n",531 "25% 1.000000 0.980000 6.500000 0.00000 0.000000 \n",532 "50% 1.000000 1.640000 9.500000 1.70000 0.000000 \n",533 "75% 2.000000 3.210000 15.000000 2.80000 0.000000 \n",534 "max 6.000000 36.700000 150.000000 33.20000 24.020000 \n",535 "\n",536 " total \n",537 "count 6433.000000 \n",538 "mean 18.517794 \n",539 "std 13.815570 \n",540 "min 1.300000 \n",541 "25% 10.800000 \n",542 "50% 14.160000 \n",543 "75% 20.300000 \n",544 "max 174.820000 "545 ]546 },547 "execution_count": 57,548 "metadata": {},549 "output_type": "execute_result"550 }551 ],552 "source": [553 "df.describe()"554 ]555 },556 {557 "cell_type": "code",558 "execution_count": 58,559 "id": "3745be25",560 "metadata": {},561 "outputs": [562 {563 "data": {564 "text/plain": [565 "pickup 0\n",566 "dropoff 0\n",567 "passengers 0\n",568 "distance 0\n",569 "fare 0\n",570 "tip 0\n",571 "tolls 0\n",572 "total 0\n",573 "color 0\n",574 "payment 44\n",575 "pickup_zone 26\n",576 "dropoff_zone 45\n",577 "pickup_borough 26\n",578 "dropoff_borough 45\n",579 "dtype: int64"580 ]581 },582 "execution_count": 58,583 "metadata": {},584 "output_type": "execute_result"585 }586 ],587 "source": [588 "df.isnull().sum()"589 ]590 },591 {592 "cell_type": "code",593 "execution_count": 59,594 "id": "a742cecb",595 "metadata": {},596 "outputs": [597 {598 "data": {599 "text/plain": [600 "0"601 ]602 },603 "execution_count": 59,604 "metadata": {},605 "output_type": "execute_result"606 }607 ],608 "source": [609 "df.duplicated().sum()"610 ]611 },612 {613 "cell_type": "code",614 "execution_count": 60,615 "id": "09a33fe7",616 "metadata": {},617 "outputs": [618 {619 "data": {620 "text/html": [621 "<div>\n",622 "<style scoped>\n",623 " .dataframe tbody tr th:only-of-type {\n",624 " vertical-align: middle;\n",625 " }\n",626 "\n",627 " .dataframe tbody tr th {\n",628 " vertical-align: top;\n",629 " }\n",630 "\n",631 " .dataframe thead th {\n",632 " text-align: right;\n",633 " }\n",634 "</style>\n",635 "<table border=\"1\" class=\"dataframe\">\n",636 " <thead>\n",637 " <tr style=\"text-align: right;\">\n",638 " <th></th>\n",639 " <th>pickup</th>\n",640 " <th>dropoff</th>\n",641 " <th>passengers</th>\n",642 " <th>distance</th>\n",643 " <th>fare</th>\n",644 " <th>tip</th>\n",645 " <th>tolls</th>\n",646 " <th>total</th>\n",647 " <th>color</th>\n",648 " <th>payment</th>\n",649 " <th>pickup_zone</th>\n",650 " <th>dropoff_zone</th>\n",651 " <th>pickup_borough</th>\n",652 " <th>dropoff_borough</th>\n",653 " </tr>\n",654 " </thead>\n",655 " <tbody>\n",656 " <tr>\n",657 " <th>7</th>\n",658 " <td>2019-03-22 12:47:13</td>\n",659 " <td>2019-03-22 12:58:17</td>\n",660 " <td>0</td>\n",661 " <td>1.4</td>\n",662 " <td>8.5</td>\n",663 " <td>0.0</td>\n",664 " <td>0.00</td>\n",665 " <td>11.80</td>\n",666 " <td>yellow</td>\n",667 " <td>NaN</td>\n",668 " <td>Murray Hill</td>\n",669 " <td>Flatiron</td>\n",670 " <td>Manhattan</td>\n",671 " <td>Manhattan</td>\n",672 " </tr>\n",673 " <tr>\n",674 " <th>445</th>\n",675 " <td>2019-03-19 06:57:14</td>\n",676 " <td>2019-03-19 07:00:08</td>\n",677 " <td>1</td>\n",678 " <td>1.3</td>\n",679 " <td>5.5</td>\n",680 " <td>0.0</td>\n",681 " <td>0.00</td>\n",682 " <td>6.30</td>\n",683 " <td>yellow</td>\n",684 " <td>NaN</td>\n",685 " <td>Boerum Hill</td>\n",686 " <td>Columbia Street</td>\n",687 " <td>Brooklyn</td>\n",688 " <td>Brooklyn</td>\n",689 " </tr>\n",690 " <tr>\n",691 " <th>491</th>\n",692 " <td>2019-03-07 07:11:33</td>\n",693 " <td>2019-03-07 07:11:39</td>\n",694 " <td>1</td>\n",695 " <td>1.6</td>\n",696 " <td>2.5</td>\n",697 " <td>0.0</td>\n",698 " <td>0.00</td>\n",699 " <td>5.80</td>\n",700 " <td>yellow</td>\n",701 " <td>NaN</td>\n",702 " <td>Murray Hill</td>\n",703 " <td>Murray Hill</td>\n",704 " <td>Manhattan</td>\n",705 " <td>Manhattan</td>\n",706 " </tr>\n",707 " <tr>\n",708 " <th>545</th>\n",709 " <td>2019-03-27 11:03:43</td>\n",710 " <td>2019-03-27 11:14:34</td>\n",711 " <td>1</td>\n",712 " <td>4.2</td>\n",713 " <td>15.0</td>\n",714 " <td>0.0</td>\n",715 " <td>0.00</td>\n",716 " <td>15.80</td>\n",717 " <td>yellow</td>\n",718 " <td>NaN</td>\n",719 " <td>LaGuardia Airport</td>\n",720 " <td>Forest Hills</td>\n",721 " <td>Queens</td>\n",722 " <td>Queens</td>\n",723 " </tr>\n",724 " <tr>\n",725 " <th>621</th>\n",726 " <td>2019-03-15 17:16:35</td>\n",727 " <td>2019-03-15 17:25:01</td>\n",728 " <td>1</td>\n",729 " <td>1.3</td>\n",730 " <td>7.5</td>\n",731 " <td>0.0</td>\n",732 " <td>0.00</td>\n",733 " <td>11.80</td>\n",734 " <td>yellow</td>\n",735 " <td>NaN</td>\n",736 " <td>Upper East Side North</td>\n",737 " <td>Upper East Side South</td>\n",738 " <td>Manhattan</td>\n",739 " <td>Manhattan</td>\n",740 " </tr>\n",741 " <tr>\n",742 " <th>770</th>\n",743 " <td>2019-03-02 03:16:59</td>\n",744 " <td>2019-03-02 03:17:06</td>\n",745 " <td>0</td>\n",746 " <td>9.4</td>\n",747 " <td>2.5</td>\n",748 " <td>0.0</td>\n",749 " <td>0.00</td>\n",750 " <td>3.80</td>\n",751 " <td>yellow</td>\n",752 " <td>NaN</td>\n",753 " <td>JFK Airport</td>\n",754 " <td>JFK Airport</td>\n",755 " <td>Queens</td>\n",756 " <td>Queens</td>\n",757 " </tr>\n",758 " <tr>\n",759 " <th>913</th>\n",760 " <td>2019-03-23 11:26:58</td>\n",761 " <td>2019-03-23 11:35:17</td>\n",762 " <td>2</td>\n",763 " <td>1.3</td>\n",764 " <td>7.5</td>\n",765 " <td>0.0</td>\n",766 " <td>0.00</td>\n",767 " <td>10.80</td>\n",768 " <td>yellow</td>\n",769 " <td>NaN</td>\n",770 " <td>Upper East Side South</td>\n",771 " <td>Lincoln Square West</td>\n",772 " <td>Manhattan</td>\n",773 " <td>Manhattan</td>\n",774 " </tr>\n",775 " <tr>\n",776 " <th>953</th>\n",777 " <td>2019-03-08 02:58:37</td>\n",778 " <td>2019-03-08 03:19:27</td>\n",779 " <td>2</td>\n",780 " <td>6.9</td>\n",781 " <td>23.5</td>\n",782 " <td>0.0</td>\n",783 " <td>0.00</td>\n",784 " <td>27.30</td>\n",785 " <td>yellow</td>\n",786 " <td>NaN</td>\n",787 " <td>Garment District</td>\n",788 " <td>Central Harlem North</td>\n",789 " <td>Manhattan</td>\n",790 " <td>Manhattan</td>\n",791 " </tr>\n",792 " <tr>\n",793 " <th>1207</th>\n",794 " <td>2019-03-08 15:41:20</td>\n",795 " <td>2019-03-08 15:41:23</td>\n",796 " <td>1</td>\n",797 " <td>0.0</td>\n",798 " <td>2.5</td>\n",799 " <td>0.0</td>\n",800 " <td>0.00</td>\n",801 " <td>5.80</td>\n",802 " <td>yellow</td>\n",803 " <td>NaN</td>\n",804 " <td>Hudson Sq</td>\n",805 " <td>Hudson Sq</td>\n",806 " <td>Manhattan</td>\n",807 " <td>Manhattan</td>\n",808 " </tr>\n",809 " <tr>\n",810 " <th>1372</th>\n",811 " <td>2019-03-12 09:19:44</td>\n",812 " <td>2019-03-12 09:43:09</td>\n",813 " <td>1</td>\n",814 " <td>1.6</td>\n",815 " <td>14.5</td>\n",816 " <td>0.0</td>\n",817 " <td>0.00</td>\n",818 " <td>17.80</td>\n",819 " <td>yellow</td>\n",820 " <td>NaN</td>\n",821 " <td>Midtown East</td>\n",822 " <td>Garment District</td>\n",823 " <td>Manhattan</td>\n",824 " <td>Manhattan</td>\n",825 " </tr>\n",826 " <tr>\n",827 " <th>1566</th>\n",828 " <td>2019-03-18 02:20:59</td>\n",829 " <td>2019-03-18 02:49:24</td>\n",830 " <td>1</td>\n",831 " <td>6.0</td>\n",832 " <td>23.0</td>\n",833 " <td>0.0</td>\n",834 " <td>0.00</td>\n",835 " <td>26.80</td>\n",836 " <td>yellow</td>\n",837 " <td>NaN</td>\n",838 " <td>TriBeCa/Civic Center</td>\n",839 " <td>Bushwick South</td>\n",840 " <td>Manhattan</td>\n",841 " <td>Brooklyn</td>\n",842 " </tr>\n",843 " <tr>\n",844 " <th>1690</th>\n",845 " <td>2019-03-22 06:24:14</td>\n",846 " <td>2019-03-22 06:24:14</td>\n",847 " <td>1</td>\n",848 " <td>0.0</td>\n",849 " <td>72.0</td>\n",850 " <td>0.0</td>\n",851 " <td>0.00</td>\n",852 " <td>72.00</td>\n",853 " <td>yellow</td>\n",854 " <td>NaN</td>\n",855 " <td>East New York</td>\n",856 " <td>NaN</td>\n",857 " <td>Brooklyn</td>\n",858 " <td>NaN</td>\n",859 " </tr>\n",860 " <tr>\n",861 " <th>1704</th>\n",862 " <td>2019-03-17 04:22:54</td>\n",863 " <td>2019-03-17 04:44:43</td>\n",864 " <td>2</td>\n",865 " <td>4.3</td>\n",866 " <td>17.5</td>\n",867 " <td>0.0</td>\n",868 " <td>0.00</td>\n",869 " <td>21.30</td>\n",870 " <td>yellow</td>\n",871 " <td>NaN</td>\n",872 " <td>Lower East Side</td>\n",873 " <td>Bushwick South</td>\n",874 " <td>Manhattan</td>\n",875 " <td>Brooklyn</td>\n",876 " </tr>\n",877 " <tr>\n",878 " <th>1737</th>\n",879 " <td>2019-03-29 19:43:51</td>\n",880 " <td>2019-03-29 19:52:28</td>\n",881 " <td>1</td>\n",882 " <td>3.7</td>\n",883 " <td>12.0</td>\n",884 " <td>0.0</td>\n",885 " <td>0.00</td>\n",886 " <td>13.80</td>\n",887 " <td>yellow</td>\n",888 " <td>NaN</td>\n",889 " <td>JFK Airport</td>\n",890 " <td>Baisley Park</td>\n",891 " <td>Queens</td>\n",892 " <td>Queens</td>\n",893 " </tr>\n",894 " <tr>\n",895 " <th>1851</th>\n",896 " <td>2019-03-02 19:20:18</td>\n",897 " <td>2019-03-02 19:21:06</td>\n",898 " <td>1</td>\n",899 " <td>0.1</td>\n",900 " <td>2.5</td>\n",901 " <td>0.0</td>\n",902 " <td>0.00</td>\n",903 " <td>5.80</td>\n",904 " <td>yellow</td>\n",905 " <td>NaN</td>\n",906 " <td>Lenox Hill West</td>\n",907 " <td>Upper East Side South</td>\n",908 " <td>Manhattan</td>\n",909 " <td>Manhattan</td>\n",910 " </tr>\n",911 " <tr>\n",912 " <th>1860</th>\n",913 " <td>2019-03-01 11:58:50</td>\n",914 " <td>2019-03-01 12:10:26</td>\n",915 " <td>1</td>\n",916 " <td>0.9</td>\n",917 " <td>8.5</td>\n",918 " <td>0.0</td>\n",919 " <td>0.00</td>\n",920 " <td>11.80</td>\n",921 " <td>yellow</td>\n",922 " <td>NaN</td>\n",923 " <td>Yorkville West</td>\n",924 " <td>Upper East Side North</td>\n",925 " <td>Manhattan</td>\n",926 " <td>Manhattan</td>\n",927 " </tr>\n",928 " <tr>\n",929 " <th>1929</th>\n",930 " <td>2019-03-13 22:35:35</td>\n",931 " <td>2019-03-13 22:35:49</td>\n",932 " <td>1</td>\n",933 " <td>0.0</td>\n",934 " <td>2.5</td>\n",935 " <td>0.0</td>\n",936 " <td>0.00</td>\n",937 " <td>3.80</td>\n",938 " <td>yellow</td>\n",939 " <td>NaN</td>\n",940 " <td>JFK Airport</td>\n",941 " <td>JFK Airport</td>\n",942 " <td>Queens</td>\n",943 " <td>Queens</td>\n",944 " </tr>\n",945 " <tr>\n",946 " <th>1941</th>\n",947 " <td>2019-03-30 16:57:00</td>\n",948 " <td>2019-03-30 17:16:31</td>\n",949 " <td>2</td>\n",950 " <td>2.6</td>\n",951 " <td>14.5</td>\n",952 " <td>0.0</td>\n",953 " <td>0.00</td>\n",954 " <td>17.80</td>\n",955 " <td>yellow</td>\n",956 " <td>NaN</td>\n",957 " <td>Two Bridges/Seward Park</td>\n",958 " <td>Murray Hill</td>\n",959 " <td>Manhattan</td>\n",960 " <td>Manhattan</td>\n",961 " </tr>\n",962 " <tr>\n",963 " <th>2353</th>\n",964 " <td>2019-03-21 10:46:14</td>\n",965 " <td>2019-03-21 11:06:33</td>\n",966 " <td>2</td>\n",967 " <td>2.8</td>\n",968 " <td>14.0</td>\n",969 " <td>0.0</td>\n",970 " <td>0.00</td>\n",971 " <td>17.30</td>\n",972 " <td>yellow</td>\n",973 " <td>NaN</td>\n",974 " <td>Garment District</td>\n",975 " <td>Little Italy/NoLiTa</td>\n",976 " <td>Manhattan</td>\n",977 " <td>Manhattan</td>\n",978 " </tr>\n",979 " <tr>\n",980 " <th>2444</th>\n",981 " <td>2019-03-10 11:06:54</td>\n",982 " <td>2019-03-10 11:16:13</td>\n",983 " <td>1</td>\n",984 " <td>1.4</td>\n",985 " <td>8.0</td>\n",986 " <td>0.0</td>\n",987 " <td>0.00</td>\n",988 " <td>11.30</td>\n",989 " <td>yellow</td>\n",990 " <td>NaN</td>\n",991 " <td>Lincoln Square East</td>\n",992 " <td>Times Sq/Theatre District</td>\n",993 " <td>Manhattan</td>\n",994 " <td>Manhattan</td>\n",995 " </tr>\n",996 " <tr>\n",997 " <th>3109</th>\n",998 " <td>2019-03-01 22:48:59</td>\n",999 " <td>2019-03-01 22:50:37</td>\n",1000 " <td>1</td>\n",1001 " <td>0.0</td>\n",1002 " <td>3.0</td>\n",1003 " <td>0.0</td>\n",1004 " <td>0.00</td>\n",1005 " <td>6.80</td>\n",1006 " <td>yellow</td>\n",1007 " <td>NaN</td>\n",1008 " <td>Times Sq/Theatre District</td>\n",1009 " <td>Times Sq/Theatre District</td>\n",1010 " <td>Manhattan</td>\n",1011 " <td>Manhattan</td>\n",1012 " </tr>\n",1013 " <tr>\n",1014 " <th>3372</th>\n",1015 " <td>2019-03-09 13:48:43</td>\n",1016 " <td>2019-03-09 13:59:10</td>\n",1017 " <td>0</td>\n",1018 " <td>1.3</td>\n",1019 " <td>8.5</td>\n",1020 " <td>0.0</td>\n",1021 " <td>0.00</td>\n",1022 " <td>11.80</td>\n",1023 " <td>yellow</td>\n",1024 " <td>NaN</td>\n",1025 " <td>Upper West Side South</td>\n",1026 " <td>Midtown North</td>\n",1027 " <td>Manhattan</td>\n",1028 " <td>Manhattan</td>\n",1029 " </tr>\n",1030 " <tr>\n",1031 " <th>3793</th>\n",1032 " <td>2019-03-24 06:07:30</td>\n",1033 " <td>2019-03-24 06:12:22</td>\n",1034 " <td>1</td>\n",1035 " <td>1.5</td>\n",1036 " <td>6.5</td>\n",1037 " <td>0.0</td>\n",1038 " <td>0.00</td>\n",1039 " <td>9.80</td>\n",1040 " <td>yellow</td>\n",1041 " <td>NaN</td>\n",1042 " <td>NaN</td>\n",1043 " <td>Midtown East</td>\n",1044 " <td>NaN</td>\n",1045 " <td>Manhattan</td>\n",1046 " </tr>\n",1047 " <tr>\n",1048 " <th>3803</th>\n",1049 " <td>2019-03-28 19:48:00</td>\n",1050 " <td>2019-03-28 20:31:39</td>\n",1051 " <td>1</td>\n",1052 " <td>17.7</td>\n",1053 " <td>52.0</td>\n",1054 " <td>0.0</td>\n",1055 " <td>5.76</td>\n",1056 " <td>65.56</td>\n",1057 " <td>yellow</td>\n",1058 " <td>NaN</td>\n",1059 " <td>JFK Airport</td>\n",1060 " <td>Penn Station/Madison Sq West</td>\n",1061 " <td>Queens</td>\n",1062 " <td>Manhattan</td>\n",1063 " </tr>\n",1064 " <tr>\n",1065 " <th>3983</th>\n",1066 " <td>2019-03-06 21:20:27</td>\n",1067 " <td>2019-03-06 22:15:45</td>\n",1068 " <td>0</td>\n",1069 " <td>9.3</td>\n",1070 " <td>41.5</td>\n",1071 " <td>0.0</td>\n",1072 " <td>5.76</td>\n",1073 " <td>51.06</td>\n",1074 " <td>yellow</td>\n",1075 " <td>NaN</td>\n",1076 " <td>Midtown Center</td>\n",1077 " <td>Forest Hills</td>\n",1078 " <td>Manhattan</td>\n",1079 " <td>Queens</td>\n",1080 " </tr>\n",1081 " <tr>\n",1082 " <th>4230</th>\n",1083 " <td>2019-03-13 15:39:06</td>\n",1084 " <td>2019-03-13 15:50:27</td>\n",1085 " <td>1</td>\n",1086 " <td>1.8</td>\n",1087 " <td>9.5</td>\n",1088 " <td>0.0</td>\n",1089 " <td>0.00</td>\n",1090 " <td>12.80</td>\n",1091 " <td>yellow</td>\n",1092 " <td>NaN</td>\n",1093 " <td>Midtown Center</td>\n",1094 " <td>Union Sq</td>\n",1095 " <td>Manhattan</td>\n",1096 " <td>Manhattan</td>\n",1097 " </tr>\n",1098 " <tr>\n",1099 " <th>4384</th>\n",1100 " <td>2019-03-14 06:58:59</td>\n",1101 " <td>2019-03-14 07:08:24</td>\n",1102 " <td>1</td>\n",1103 " <td>1.8</td>\n",1104 " <td>8.5</td>\n",1105 " <td>0.0</td>\n",1106 " <td>0.00</td>\n",1107 " <td>9.30</td>\n",1108 " <td>yellow</td>\n",1109 " <td>NaN</td>\n",1110 " <td>East Harlem North</td>\n",1111 " <td>Morningside Heights</td>\n",1112 " <td>Manhattan</td>\n",1113 " <td>Manhattan</td>\n",1114 " </tr>\n",1115 " <tr>\n",1116 " <th>4474</th>\n",1117 " <td>2019-03-09 00:20:47</td>\n",1118 " <td>2019-03-09 00:27:37</td>\n",1119 " <td>4</td>\n",1120 " <td>0.7</td>\n",1121 " <td>6.0</td>\n",1122 " <td>0.0</td>\n",1123 " <td>0.00</td>\n",1124 " <td>9.80</td>\n",1125 " <td>yellow</td>\n",1126 " <td>NaN</td>\n",1127 " <td>East Village</td>\n",1128 " <td>Stuy Town/Peter Cooper Village</td>\n",1129 " <td>Manhattan</td>\n",1130 " <td>Manhattan</td>\n",1131 " </tr>\n",1132 " <tr>\n",1133 " <th>4515</th>\n",1134 " <td>2019-03-31 09:42:47</td>\n",1135 " <td>2019-03-31 09:53:15</td>\n",1136 " <td>1</td>\n",1137 " <td>1.9</td>\n",1138 " <td>9.0</td>\n",1139 " <td>0.0</td>\n",1140 " <td>0.00</td>\n",1141 " <td>12.30</td>\n",1142 " <td>yellow</td>\n",1143 " <td>NaN</td>\n",1144 " <td>Garment District</td>\n",1145 " <td>West Chelsea/Hudson Yards</td>\n",1146 " <td>Manhattan</td>\n",1147 " <td>Manhattan</td>\n",1148 " </tr>\n",1149 " <tr>\n",1150 " <th>4562</th>\n",1151 " <td>2019-03-03 23:02:48</td>\n",1152 " <td>2019-03-03 23:02:57</td>\n",1153 " <td>1</td>\n",1154 " <td>0.1</td>\n",1155 " <td>20.0</td>\n",1156 " <td>0.0</td>\n",1157 " <td>0.00</td>\n",1158 " <td>20.80</td>\n",1159 " <td>yellow</td>\n",1160 " <td>NaN</td>\n",1161 " <td>Long Island City/Hunters Point</td>\n",1162 " <td>Long Island City/Hunters Point</td>\n",1163 " <td>Queens</td>\n",1164 " <td>Queens</td>\n",1165 " </tr>\n",1166 " <tr>\n",1167 " <th>4746</th>\n",1168 " <td>2019-03-12 07:06:07</td>\n",1169 " <td>2019-03-12 07:06:21</td>\n",1170 " <td>1</td>\n",1171 " <td>1.3</td>\n",1172 " <td>2.5</td>\n",1173 " <td>0.0</td>\n",1174 " <td>0.00</td>\n",1175 " <td>5.80</td>\n",1176 " <td>yellow</td>\n",1177 " <td>NaN</td>\n",1178 " <td>Meatpacking/West Village West</td>\n",1179 " <td>Meatpacking/West Village West</td>\n",1180 " <td>Manhattan</td>\n",1181 " <td>Manhattan</td>\n",1182 " </tr>\n",1183 " <tr>\n",1184 " <th>4801</th>\n",1185 " <td>2019-03-26 15:30:50</td>\n",1186 " <td>2019-03-26 15:42:59</td>\n",1187 " <td>1</td>\n",1188 " <td>1.2</td>\n",1189 " <td>9.0</td>\n",1190 " <td>0.0</td>\n",1191 " <td>0.00</td>\n",1192 " <td>12.30</td>\n",1193 " <td>yellow</td>\n",1194 " <td>NaN</td>\n",1195 " <td>TriBeCa/Civic Center</td>\n",1196 " <td>Battery Park City</td>\n",1197 " <td>Manhattan</td>\n",1198 " <td>Manhattan</td>\n",1199 " </tr>\n",1200 " <tr>\n",