%matplotlib inline
import geopandas as gpd
import pandas as pd
import numpy as np
import seaborn
import dask.dataframe as dd
from matplotlib import pyplot as plt
bike = dd.read_parquet('/bigdata/citibike.parquet')
bike.head()
trip_duration | start_time | stop_time | start_station_id | start_station_name | start_station_latitude | start_station_longitude | end_station_id | end_station_name | end_station_latitude | end_station_longitude | bike_id | user_type | birth_year | gender | start_taxizone_id | end_taxizone_id | start_ct_id | end_ct_id | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 634 | 2013-07-01 00:00:00 | 2013-07-01 00:10:34 | 164 | E 47 St & 2 Ave | 40.753231 | -73.970322 | 504 | 1 Ave & E 15 St | 40.732220 | -73.981659 | 16950 | Customer | NaN | 0 | 233.0 | 224.0 | 1432.0 | 2158.0 |
1 | 1547 | 2013-07-01 00:00:02 | 2013-07-01 00:25:49 | 388 | W 26 St & 10 Ave | 40.749718 | -74.002953 | 459 | W 20 St & 11 Ave | 40.746746 | -74.007759 | 19816 | Customer | NaN | 0 | 246.0 | 246.0 | 2098.0 | 2098.0 |
2 | 178 | 2013-07-01 00:01:04 | 2013-07-01 00:04:02 | 293 | Lafayette St & E 8 St | 40.730286 | -73.990768 | 237 | E 11 St & 2 Ave | 40.730473 | -73.986725 | 14548 | Subscriber | 1980.0 | 2 | 113.0 | 79.0 | 1472.0 | 861.0 |
3 | 1580 | 2013-07-01 00:01:06 | 2013-07-01 00:27:26 | 531 | Forsyth St & Broome St | 40.718941 | -73.992661 | 499 | Broadway & W 60 St | 40.769154 | -73.981918 | 16063 | Customer | NaN | 0 | 148.0 | 142.0 | 1475.0 | 1346.0 |
4 | 757 | 2013-07-01 00:01:10 | 2013-07-01 00:13:47 | 382 | University Pl & E 14 St | 40.734928 | -73.992004 | 410 | Suffolk St & Stanton St | 40.720665 | -73.985176 | 19213 | Subscriber | 1986.0 | 1 | 113.0 | 148.0 | 969.0 | 929.0 |
zz = bike['trip_duration start_ct_id'.split()].groupby('start_ct_id').count().compute()
zz = zz.sort_index()
zz.index = zz.index.astype(np.int64)
zz.columns = ['biketrip_count',]
bikesmall = bike['start_station_latitude start_station_longitude start_ct_id'.split()]
bike2 = bikesmall[bikesmall.start_ct_id == 9].compute()
bike2
start_station_latitude | start_station_longitude | start_ct_id | |
---|---|---|---|
1676 | 40.720875 | -73.980858 | 9.0 |
2545 | 40.720875 | -73.980858 | 9.0 |
3113 | 40.720875 | -73.980858 | 9.0 |
3329 | 40.720875 | -73.980858 | 9.0 |
3339 | 40.720875 | -73.980858 | 9.0 |
3419 | 40.720875 | -73.980858 | 9.0 |
3711 | 40.720875 | -73.980858 | 9.0 |
3763 | 40.720875 | -73.980858 | 9.0 |
4049 | 40.720875 | -73.980858 | 9.0 |
4243 | 40.720875 | -73.980858 | 9.0 |
4269 | 40.720875 | -73.980858 | 9.0 |
4317 | 40.720875 | -73.980858 | 9.0 |
4360 | 40.720875 | -73.980858 | 9.0 |
4569 | 40.720875 | -73.980858 | 9.0 |
4583 | 40.720875 | -73.980858 | 9.0 |
4586 | 40.720875 | -73.980858 | 9.0 |
4739 | 40.720875 | -73.980858 | 9.0 |
4741 | 40.720875 | -73.980858 | 9.0 |
4841 | 40.720875 | -73.980858 | 9.0 |
5139 | 40.720875 | -73.980858 | 9.0 |
7740 | 40.720875 | -73.980858 | 9.0 |
7900 | 40.720875 | -73.980858 | 9.0 |
8311 | 40.720875 | -73.980858 | 9.0 |
8742 | 40.720875 | -73.980858 | 9.0 |
10987 | 40.720875 | -73.980858 | 9.0 |
12882 | 40.720875 | -73.980858 | 9.0 |
12998 | 40.720875 | -73.980858 | 9.0 |
13134 | 40.720875 | -73.980858 | 9.0 |
13675 | 40.720875 | -73.980858 | 9.0 |
14201 | 40.720875 | -73.980858 | 9.0 |
... | ... | ... | ... |
38192 | 40.720875 | -73.980858 | 9.0 |
38269 | 40.720875 | -73.980858 | 9.0 |
38289 | 40.720875 | -73.980858 | 9.0 |
38290 | 40.720875 | -73.980858 | 9.0 |
38291 | 40.720875 | -73.980858 | 9.0 |
38298 | 40.720875 | -73.980858 | 9.0 |
38498 | 40.720875 | -73.980858 | 9.0 |
38626 | 40.720875 | -73.980858 | 9.0 |
39191 | 40.720875 | -73.980858 | 9.0 |
39680 | 40.720875 | -73.980858 | 9.0 |
39681 | 40.720875 | -73.980858 | 9.0 |
40174 | 40.720875 | -73.980858 | 9.0 |
40248 | 40.720875 | -73.980858 | 9.0 |
41768 | 40.720875 | -73.980858 | 9.0 |
43287 | 40.720875 | -73.980858 | 9.0 |
45198 | 40.720875 | -73.980858 | 9.0 |
45480 | 40.720875 | -73.980858 | 9.0 |
46523 | 40.720875 | -73.980858 | 9.0 |
47132 | 40.720875 | -73.980858 | 9.0 |
47215 | 40.720875 | -73.980858 | 9.0 |
47216 | 40.720875 | -73.980858 | 9.0 |
47264 | 40.720875 | -73.980858 | 9.0 |
47330 | 40.720875 | -73.980858 | 9.0 |
48096 | 40.720875 | -73.980858 | 9.0 |
48097 | 40.720875 | -73.980858 | 9.0 |
48183 | 40.720875 | -73.980858 | 9.0 |
48654 | 40.720875 | -73.980858 | 9.0 |
48706 | 40.720875 | -73.980858 | 9.0 |
48762 | 40.720875 | -73.980858 | 9.0 |
51071 | 40.720875 | -73.980858 | 9.0 |
74799 rows × 3 columns
zz
biketrip_count | |
---|---|
start_ct_id | |
9 | 74799 |
10 | 430761 |
11 | 242609 |
12 | 474650 |
13 | 228317 |
14 | 131138 |
15 | 257177 |
16 | 142856 |
17 | 241261 |
18 | 178008 |
20 | 132012 |
21 | 672318 |
22 | 27447 |
23 | 38145 |
24 | 85521 |
25 | 3139 |
26 | 47407 |
27 | 7187 |
29 | 4636 |
30 | 40977 |
31 | 21306 |
33 | 2023 |
54 | 56658 |
55 | 1103 |
56 | 37623 |
63 | 4940 |
64 | 5573 |
65 | 12196 |
80 | 2734 |
82 | 3622 |
... | ... |
2037 | 473707 |
2040 | 262070 |
2043 | 63137 |
2047 | 19787 |
2048 | 42559 |
2063 | 2997 |
2081 | 23797 |
2082 | 50779 |
2090 | 11260 |
2095 | 511843 |
2098 | 705033 |
2099 | 308199 |
2100 | 496842 |
2101 | 148639 |
2102 | 421357 |
2103 | 215798 |
2104 | 114130 |
2112 | 166862 |
2123 | 17863 |
2124 | 11633 |
2133 | 42592 |
2146 | 135173 |
2148 | 64526 |
2152 | 246529 |
2155 | 100156 |
2156 | 34091 |
2157 | 100684 |
2158 | 436600 |
2163 | 42561 |
2164 | 57101 |
309 rows × 1 columns
ct = gpd.read_file('../shapefiles/nyct2010.shp')
ct
BoroCT2010 | BoroCode | BoroName | CDEligibil | CT2010 | CTLabel | NTACode | NTAName | PUMA | Shape_Area | Shape_Leng | geometry | |
---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 5000900 | 5 | Staten Island | I | 000900 | 9 | SI22 | West New Brighton-New Brighton-St. George | 3903 | 2.497010e+06 | 7729.016729 | POLYGON ((962269.1260375977 173705.5001831055,... |
1 | 5012500 | 5 | Staten Island | I | 012500 | 125 | SI22 | West New Brighton-New Brighton-St. George | 3903 | 4.954936e+06 | 10582.855530 | POLYGON ((951998.5532226562 168438.0043945312,... |
2 | 5013301 | 5 | Staten Island | E | 013301 | 133.01 | SI22 | West New Brighton-New Brighton-St. George | 3903 | 7.217847e+05 | 3428.312676 | POLYGON ((951720.9486083984 170488.4069824219,... |
3 | 5019700 | 5 | Staten Island | I | 019700 | 197 | SI07 | Westerleigh | 3903 | 3.231720e+06 | 9097.697226 | POLYGON ((947819.2308349609 164190.0209960938,... |
4 | 5002002 | 5 | Staten Island | I | 002002 | 20.02 | SI14 | Grasmere-Arrochar-Ft. Wadsworth | 3902 | 8.501224e+06 | 12591.725901 | POLYGON ((966615.2556152344 158662.2927856445,... |
5 | 5006400 | 5 | Staten Island | I | 006400 | 64 | SI14 | Grasmere-Arrochar-Ft. Wadsworth | 3902 | 7.643184e+06 | 12726.360406 | POLYGON ((963023.891784668 158246.7521972656, ... |
6 | 5007400 | 5 | Staten Island | I | 007400 | 74 | SI14 | Grasmere-Arrochar-Ft. Wadsworth | 3902 | 5.788238e+06 | 9902.948475 | POLYGON ((967656.8290405273 155637.1314086914,... |
7 | 5018701 | 5 | Staten Island | I | 018701 | 187.01 | SI07 | Westerleigh | 3903 | 4.267476e+06 | 8626.771269 | POLYGON ((950555.9412231445 161453.658203125, ... |
8 | 1002202 | 1 | Manhattan | I | 002202 | 22.02 | MN28 | Lower East Side | 3809 | 6.039223e+05 | 3817.391631 | POLYGON ((990284.3284301758 201838.3563842773,... |
9 | 1003200 | 1 | Manhattan | I | 003200 | 32 | MN22 | East Village | 3809 | 2.334190e+06 | 6358.386684 | POLYGON ((989819.2963867188 204093.9949951172,... |
10 | 1006800 | 1 | Manhattan | I | 006800 | 68 | MN21 | Gramercy | 3808 | 1.877943e+06 | 5723.883037 | POLYGON ((989553.9097900391 209596.7955932617,... |
11 | 1008900 | 1 | Manhattan | I | 008900 | 89 | MN13 | Hudson Yards-Chelsea-Flatiron-Union Square | 3807 | 1.782279e+06 | 5578.769499 | POLYGON ((984534.7501831055 210565.4451904297,... |
12 | 1009600 | 1 | Manhattan | E | 009600 | 96 | MN17 | Midtown-Midtown South | 3807 | 1.887288e+06 | 5737.356247 | POLYGON ((990440.5057983398 215405.0643920898,... |
13 | 1009800 | 1 | Manhattan | I | 009800 | 98 | MN19 | Turtle Bay-East Midtown | 3808 | 1.906016e+06 | 5534.199811 | POLYGON ((994133.507019043 214848.8975830078, ... |
14 | 1010000 | 1 | Manhattan | I | 010000 | 100 | MN19 | Turtle Bay-East Midtown | 3808 | 1.860938e+06 | 5692.168488 | POLYGON ((993108.3057861328 216013.1307983398,... |
15 | 1010200 | 1 | Manhattan | I | 010200 | 102 | MN17 | Midtown-Midtown South | 3807 | 1.860993e+06 | 5687.802579 | POLYGON ((992216.5391845703 216507.6870117188,... |
16 | 1010400 | 1 | Manhattan | I | 010400 | 104 | MN17 | Midtown-Midtown South | 3807 | 1.864600e+06 | 5693.036118 | POLYGON ((991325.8814086914 217001.6885986328,... |
17 | 1011201 | 1 | Manhattan | I | 011201 | 112.01 | MN17 | Midtown-Midtown South | 3807 | 8.561644e+05 | 3716.146785 | POLYGON ((991725.2440185547 217725.2991943359,... |
18 | 1011202 | 1 | Manhattan | I | 011202 | 112.02 | MN17 | Midtown-Midtown South | 3807 | 8.395258e+05 | 3688.762328 | POLYGON ((992615.8984375 217228.1416015625, 99... |
19 | 1011203 | 1 | Manhattan | I | 011203 | 112.03 | MN19 | Turtle Bay-East Midtown | 3808 | 8.540825e+05 | 3701.173031 | POLYGON ((993507.2319946289 216732.0338134766,... |
20 | 1011300 | 1 | Manhattan | I | 011300 | 113 | MN17 | Midtown-Midtown South | 3807 | 1.890907e+06 | 5699.860641 | POLYGON ((988650.2766113281 214286.4022216797,... |
21 | 1011402 | 1 | Manhattan | I | 011402 | 114.02 | MN40 | Upper East Side-Carnegie Hill | 3805 | 1.063547e+06 | 4125.256100 | POLYGON ((994013.2479858398 217645.299621582, ... |
22 | 1013000 | 1 | Manhattan | I | 013000 | 130 | MN40 | Upper East Side-Carnegie Hill | 3805 | 1.918145e+06 | 5807.972956 | POLYGON ((994920.1096191406 221386.2695922852,... |
23 | 1014000 | 1 | Manhattan | I | 014000 | 140 | MN40 | Upper East Side-Carnegie Hill | 3805 | 1.925984e+06 | 5820.815640 | POLYGON ((996728.3079833984 222545.6896362305,... |
24 | 1014200 | 1 | Manhattan | I | 014200 | 142 | MN40 | Upper East Side-Carnegie Hill | 3805 | 1.927688e+06 | 5821.704944 | POLYGON ((995836.4956054688 223039.7406005859,... |
25 | 1014601 | 1 | Manhattan | I | 014601 | 146.01 | MN32 | Yorkville | 3805 | 7.998799e+05 | 4016.133393 | POLYGON ((998271.5236206055 222317.6588134766,... |
26 | 1014602 | 1 | Manhattan | I | 014602 | 146.02 | MN32 | Yorkville | 3805 | 1.175339e+06 | 4528.695483 | POLYGON ((998660.5087890625 223021.3121948242,... |
27 | 1014801 | 1 | Manhattan | I | 014801 | 148.01 | MN40 | Upper East Side-Carnegie Hill | 3805 | 5.592162e+05 | 3135.951423 | POLYGON ((996994.3508300781 223026.0794067383,... |
28 | 1014802 | 1 | Manhattan | I | 014802 | 148.02 | MN40 | Upper East Side-Carnegie Hill | 3805 | 1.351365e+06 | 4691.029341 | POLYGON ((997637.4860229492 224187.0347900391,... |
29 | 1015300 | 1 | Manhattan | I | 015300 | 153 | MN14 | Lincoln Square | 3806 | 1.872393e+06 | 5674.292342 | POLYGON ((990644.7542114258 221597.942199707, ... |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
2136 | 2021800 | 2 | Bronx | E | 021800 | 218 | BX08 | West Farms-Bronx River | 3709 | 3.460969e+06 | 9122.453686 | POLYGON ((1021107.376037598 243458.9674072266,... |
2137 | 2024000 | 2 | Bronx | E | 024000 | 240 | BX37 | Van Nest-Morris Park-Westchester Square | 3704 | 2.577349e+06 | 7190.177079 | POLYGON ((1021556.863220215 246239.2802124023,... |
2138 | 2006000 | 2 | Bronx | E | 006000 | 60 | BX75 | Crotona Park East | 3705 | 3.413187e+06 | 7818.412089 | POLYGON ((1017867.582641602 245337.3627929688,... |
2139 | 2006200 | 2 | Bronx | E | 006200 | 62 | BX08 | West Farms-Bronx River | 3709 | 2.035611e+06 | 7175.713453 | POLYGON ((1019153.905639648 243875.9155883789,... |
2140 | 3030300 | 3 | Brooklyn | E | 030300 | 303 | BK79 | Ocean Hill | 4007 | 2.690240e+06 | 6898.560842 | POLYGON ((1008188.862182617 185753.8187866211,... |
2141 | 3036501 | 3 | Brooklyn | E | 036501 | 365.01 | BK79 | Ocean Hill | 4007 | 1.369715e+06 | 5483.369156 | POLYGON ((1008957.26940918 185699.4918212891, ... |
2142 | 3079602 | 3 | Brooklyn | E | 079602 | 796.02 | BK60 | Prospect Lefferts Gardens-Wingate | 4011 | 1.453525e+06 | 5043.967955 | POLYGON ((996507.9182128906 176285.0225830078,... |
2143 | 3082000 | 3 | Brooklyn | E | 082000 | 820 | BK60 | Prospect Lefferts Gardens-Wingate | 4011 | 1.599913e+06 | 5582.419306 | POLYGON ((998104.8178100586 178068.6047973633,... |
2144 | 3082200 | 3 | Brooklyn | E | 082200 | 822 | BK60 | Prospect Lefferts Gardens-Wingate | 4011 | 1.827423e+06 | 5792.844437 | POLYGON ((997439.182800293 176336.3872070312, ... |
2145 | 1003400 | 1 | Manhattan | I | 003400 | 34 | MN22 | East Village | 3809 | 1.718946e+06 | 5503.345191 | POLYGON ((990340.0073852539 205029.4624023438,... |
2146 | 3090000 | 3 | Brooklyn | E | 090000 | 900 | BK81 | Brownsville | 4007 | 2.645351e+06 | 6709.231083 | POLYGON ((1007479.828186035 181438.7852172852,... |
2147 | 3000900 | 3 | Brooklyn | I | 000900 | 9 | BK09 | Brooklyn Heights-Cobble Hill | 4004 | 1.737777e+06 | 5883.375467 | POLYGON ((986838.3345947266 192326.7385864258,... |
2148 | 3036100 | 3 | Brooklyn | E | 036100 | 361 | BK79 | Ocean Hill | 4007 | 1.524421e+06 | 6064.700108 | POLYGON ((1007864.663391113 183580.8475952148,... |
2149 | 3078200 | 3 | Brooklyn | E | 078200 | 782 | BK91 | East Flatbush-Farragut | 4010 | 1.811374e+06 | 5948.145346 | POLYGON ((1001592.999633789 171330.1213989258,... |
2150 | 3083000 | 3 | Brooklyn | E | 083000 | 830 | BK91 | East Flatbush-Farragut | 4010 | 2.171915e+06 | 6600.753863 | POLYGON ((1000207.434997559 172073.5809936523,... |
2151 | 1006000 | 1 | Manhattan | I | 006000 | 60 | MN50 | Stuyvesant Town-Cooper Village | 3808 | 1.296018e+06 | 5239.096008 | POLYGON ((991333.3630371094 207173.3526000977,... |
2152 | 3031300 | 3 | Brooklyn | E | 031300 | 313 | BK61 | Crown Heights North | 4006 | 1.832522e+06 | 5465.787220 | POLYGON ((999740.874206543 186352, 999901.1726... |
2153 | 3031500 | 3 | Brooklyn | E | 031500 | 315 | BK61 | Crown Heights North | 4006 | 1.886108e+06 | 5658.750760 | POLYGON ((998973.1525878906 186411.3536376953,... |
2154 | 3019300 | 3 | Brooklyn | E | 019300 | 193 | BK69 | Clinton Hill | 4004 | 2.903179e+06 | 6981.649815 | POLYGON ((995501.4732055664 190827.6047973633,... |
2155 | 3023300 | 3 | Brooklyn | E | 023300 | 233 | BK75 | Bedford | 4003 | 1.849442e+06 | 5438.790291 | POLYGON ((996695.8309936523 190462.5628051758,... |
2156 | 1002800 | 1 | Manhattan | E | 002800 | 28 | MN28 | Lower East Side | 3809 | 1.973562e+06 | 5627.595336 | POLYGON ((991650.9154052734 204299.32421875, 9... |
2157 | 1004400 | 1 | Manhattan | I | 004400 | 44 | MN50 | Stuyvesant Town-Cooper Village | 3808 | 4.277454e+06 | 9684.842507 | (POLYGON ((994681.4056396484 203127.6748046875... |
2158 | 4137700 | 4 | Queens | I | 137700 | 1377 | QN42 | Oakland Gardens | 4104 | 8.038804e+06 | 12085.908028 | POLYGON ((1052563.640808105 209850.8568115234,... |
2159 | 4138502 | 4 | Queens | I | 138502 | 1385.02 | QN99 | park-cemetery-etc-Queens | 4104 | 2.620882e+07 | 48473.195704 | POLYGON ((1054368.627197266 217912.8056030273,... |
2160 | 1028700 | 1 | Manhattan | E | 028700 | 287 | MN35 | Washington Heights North | 3801 | 5.710876e+06 | 12407.587938 | POLYGON ((1003963.362792969 255062.9552001953,... |
2161 | 1029700 | 1 | Manhattan | I | 029700 | 297 | MN99 | park-cemetery-etc-Manhattan | 3801 | 9.961849e+06 | 20553.099113 | (POLYGON ((1004601.953430176 259027.5151977539... |
2162 | 3000100 | 3 | Brooklyn | I | 000100 | 1 | BK09 | Brooklyn Heights-Cobble Hill | 4004 | 2.237282e+06 | 6527.281839 | POLYGON ((986764.3486328125 194584.6243896484,... |
2163 | 3000301 | 3 | Brooklyn | I | 000301 | 3.01 | BK09 | Brooklyn Heights-Cobble Hill | 4004 | 2.142139e+06 | 6466.952122 | POLYGON ((985832.7232055664 193771.6766357422,... |
2164 | 1023300 | 1 | Manhattan | E | 023300 | 233 | MN04 | Hamilton Heights | 3802 | 2.535724e+06 | 7136.778935 | POLYGON ((999389.0635986328 241090.4204101562,... |
2165 | 1023700 | 1 | Manhattan | E | 023700 | 237 | MN04 | Hamilton Heights | 3802 | 2.897558e+06 | 7073.400099 | POLYGON ((1000029.442993164 242245.0491943359,... |
2166 rows × 12 columns
ct = ct.to_crs({'init': 'epsg:4326'})
ct2 = ct.merge(zz, left_index=True, right_index=True, how='left')
ct2.biketrip_count = np.log(ct2.biketrip_count.fillna(1))
sorted(ct2.CTLabel.unique().tolist())
['1', '10', '10.01', '10.02', '100', '1004', '1006', '1008', '1008.01', '1008.02', '101', '1010', '1010.01', '1010.02', '1012', '1014', '1016', '1017', '1018', '102', '1020', '1022', '1024', '1026', '1028', '1029', '103', '1032.01', '1032.02', '1033', '1034', '1039', '104', '1047', '105', '1058.01', '1058.04', '1059', '106', '106.01', '106.02', '107.01', '1070', '1072.01', '1072.02', '1078', '108', '1085', '109', '1093', '1097', '1098', '1099', '11', '110', '1104', '1106', '111', '1110', '1113', '1116', '1118', '112', '112.01', '112.02', '112.03', '1120', '1122', '1123', '1124', '1126', '1128', '1129', '113', '1130', '1132', '1133', '1134', '1139', '114', '114.01', '114.02', '1141', '1142.01', '1142.02', '1144', '1146', '1147', '115', '115.02', '1150', '1151', '1152', '1155', '1156', '1157', '1158', '1159', '116', '1160', '1161', '1162', '1163', '1164', '1166', '1167', '1168', '117', '1170', '1171', '1172.01', '1172.02', '1174', '1175', '1176.01', '1176.02', '1178', '118', '1180', '1181', '1182.01', '1182.02', '1184', '1185', '1186', '1187', '1188', '1189', '119', '1190', '1191', '1192', '1193', '1194', '1195', '1196', '1198', '1199', '12', '120', '1200', '1201', '1202', '1203', '1205', '1207', '1208', '121', '121.01', '121.02', '1210', '1211', '1214', '1215', '122', '1220', '1223', '1227.01', '1227.02', '123', '123.01', '1237', '124', '1241', '1247', '125', '1257', '126', '126.01', '126.02', '1265', '1267', '127', '127.01', '1277', '128', '128.01', '128.04', '128.05', '128.06', '1283', '129', '129.01', '129.02', '1291.02', '1291.03', '1291.04', '13', '130', '1301', '131', '132', '132.01', '132.03', '132.04', '133', '133.01', '133.02', '1333', '1339', '134', '1341', '1347', '135', '136', '1367', '137', '1377', '138', '1385.01', '1385.02', '139', '1399', '14', '14.01', '14.02', '140', '1403', '1409.01', '1409.02', '141', '1417', '142', '142.01', '142.02', '1429', '143', '1435', '144', '144.01', '144.02', '1441', '1447', '145', '1451.01', '1451.02', '1459', '146.01', '146.02', '146.04', '146.05', '146.06', '146.07', '146.08', '1463', '1467', '147', '147.01', '147.02', '1471', '1479', '148', '148.01', '148.02', '1483', '149', '15', '15.01', '15.02', '150', '150.01', '150.02', '1502', '1507.01', '1507.02', '151', '152', '1522', '1529.01', '1529.02', '153', '154', '155', '1551.01', '1551.02', '156', '156.01', '156.02', '156.03', '1567', '157', '1571.01', '1571.02', '1579.01', '1579.02', '1579.03', '158', '158.01', '158.02', '159', '16', '160', '160.01', '160.02', '161', '1617', '162', '1621', '163', '164', '165', '166', '167', '168', '169', '169.01', '17', '170', '170.05', '170.07', '170.08', '170.09', '170.10', '170.11', '170.12', '171', '172', '173', '174', '174.01', '174.02', '175', '176', '177', '177.01', '177.02', '178', '179', '179.01', '179.02', '18', '180', '181', '181.01', '181.02', '182', '183', '183.01', '183.02', '184', '184.01', '184.02', '185', '185.01', '185.02', '186', '187', '187.01', '187.02', '188', '189', '189.01', '189.02', '19', '190', '191', '192', '193', '194', '195', '196', '197', '197.01', '197.02', '198', '199', '2', '2.01', '2.02', '20', '20.01', '20.02', '200', '201', '201.01', '201.02', '202', '203', '204', '205', '205.01', '205.02', '206', '206.01', '207', '207.01', '208', '208.01', '208.03', '208.04', '209', '209.01', '21', '210', '210.01', '210.02', '211', '212', '213', '213.01', '213.02', '213.03', '214', '215', '215.01', '215.02', '216', '216.01', '216.02', '217', '217.03', '218', '219', '22', '22.01', '22.02', '220', '220.01', '220.02', '221', '221.01', '221.02', '222', '223', '223.01', '223.02', '224', '224.01', '224.03', '224.04', '225', '226', '227', '227.01', '227.02', '227.03', '228', '229', '229.01', '229.02', '23', '230', '231', '232', '233', '233.01', '233.02', '234', '235', '235.01', '235.02', '236', '237', '237.02', '237.03', '237.04', '238', '238.01', '238.02', '239', '24', '240', '241', '242', '243', '243.01', '243.02', '244', '244.01', '244.02', '245', '245.01', '245.02', '246', '247', '248', '249', '25', '250', '251', '252', '253', '253.01', '253.02', '254', '255', '256', '257', '258', '259', '259.01', '259.02', '26', '26.01', '26.02', '260', '261', '262', '263', '264', '265', '266', '266.01', '266.02', '267', '267.01', '267.02', '268', '269', '269.01', '269.02', '27', '27.01', '27.02', '270', '271', '272', '273', '273.01', '273.02', '274', '274.01', '274.02', '275', '276', '277', '277.02', '277.04', '277.05', '277.06', '278', '279', '28', '280', '281', '282', '283', '284', '285', '285.01', '285.02', '286', '287', '288', '289', '29', '29.01', '290', '291', '291.02', '291.03', '291.04', '292', '293', '293.01', '293.02', '294', '295', '296', '297', '298', '299', '3', '3.01', '30', '30.01', '30.02', '300', '301', '302', '303', '303.01', '303.02', '304', '305', '306', '307', '307.01', '308', '309', '309.02', '309.03', '309.04', '31', '310', '311', '312', '313', '314', '315', '316', '317', '317.01', '317.02', '317.03', '317.04', '318', '319', '319.01', '319.02', '32', '320', '321', '323', '324', '325', '326', '327', '328', '329', '33', '330', '331', '332.01', '332.02', '333', '334', '334.01', '334.02', '335', '336', '337', '338', '339', '34', '340', '341', '342', '343', '344', '345', '347', '348', '349', '35', '350', '351', '352', '353', '354', '355', '356', '356.01', '356.02', '357', '358', '359', '36', '36.01', '36.02', '360', '360.01', '360.02', '361', '362', '363', '364', '365', '365.01', '365.02', '366', '367', '368', '369', '369.01', '369.02', '37', '370', '371', '372', '373', '374', '374.01', '374.02', '375', '375.04', '376', '377', '378', '379', '38', '380', '381', '382', '383', '383.01', '383.02', '384', '385', '386', '387', '388', '389', '39', '390', '391', '392', '393', '394', '395', '396', '397', '398', '399', '399.01', '399.02', '4', '40', '40.01', '40.02', '400', '401', '402', '403', '403.02', '403.03', '403.04', '404', '405', '405.01', '405.02', '406', '407', '407.01', '407.02', '408', '409', '41', '410', '411', '412', '413', '414', '414.01', '414.02', '415', '416', '417', '418', '419', '42', '420', '421', '422', '423', '424', '425', '426', '427', '428', '429', '429.01', '429.02', '43', '430', '431', '432', '433', '434', '435', '436', '437', '437.01', '437.02', '438', '439', '44', '44.01', '440', '441', '442', '443', '443.01', '443.02', '444', '445', '446', '446.01', '446.02', '447', '448', '449', '449.01', '449.02', '45', '450', '451.01', '451.02', '452', '453', '454', '455', '456', '457', '458', '459', '46', '460', '461', '462', '462.01', '462.02', '463', '464', '465', '466', '467', '468', '469', '47', '470', '471', '472', '473', '474', '475', '476', '477', '478', '479', '48', '480', '481', '482', '483', '484', '485', '486', '488', '489', '49', '490', '491', '492', '493', '493.01', '493.02', '494', '495', '496', '497', '498', '499', '5', '5.01', '5.02', '50', '50.01', '50.02', '500', '501', '502.01', '502.02', '503', '504', '505', '506', '507', '508', '508.01', '508.03', '508.04', '509', '51', '510', '510.01', '510.02', '511', '512', '513', '514', '515', '516', '516.01', '516.02', '517', '518', '519', '52', '52.01', '52.02', '520', '521', '522', '523', '524', '525', '526', '527', '528', '529', '53', '530', '531', '532', '533', '534', '534.01', '535', '536.01', '537', '538', '539', '54', '540', '542', '543', '544', '545', '546', '547', '548', '549', '55', '55.01', '55.02', '550', '551', '552', '553', '554', '555', '556', '557', '558', '559', '56', '56.01', '56.02', '560', '561', '562', '563', '564', '565', '566', '567', '568', '569', '57', '570', '571', '572', '573', '574', '575', '576', '577', '578', '579', '58', '580', '581', '582', '583', '584', '585', '586', '587', '588', '589', '59', '59.02', '590', '591', '592', '593', '594', '594.01', '594.02', '595', '596', '598', '599', '6', '60', '600', '601', '603', '606', '607.01', '608', '61', '610', '610.02', '610.03', '610.04', '612', '613.01', '613.02', '614', '616', '616.01', '616.02', '618', '619', '62', '62.01', '62.02', '620', ...]
The white point should be inside the zone indicated by the red point. Google maps that is a 6 minute difference in location walking, which is quite a lot. Something is very broken about the spatial join.
ct2.plot('biketrip_count', cmap=plt.cm.viridis)
plt.plot([-73.980858,], [40.720875, ] , 'o', color='white')
plt.plot(-73.98370854854818, 40.72555342330404, 'o', color='red')
plt.gcf().set_size_inches(12, 9)
plt.xlim(-74.0, -73.95)
plt.ylim(40.7, 40.75)
(40.7, 40.75)
!ls
citibike_cleaning_nb.ipynb stations.2017.04.20.09.43.json derby.log subway_test_1.ipynb exploratory_bike_station_ids.ipynb subway_test_2.ipynb lowfreq_bike_stations.ipynb Untitled.ipynb sql_test_1.ipynb
zz = bike['trip_duration start_ct_id'.split()].groupby('start_ct_id').count().compute()
print(ct.geometry[9].centroid)
POINT (-73.98370854854818 40.72555342330404)
tz = gpd.read_file('../shapefiles/taxi_zones.shp')
tz.to_crs({'init': 'epsg:4326'})
LocationID | OBJECTID | Shape_Area | Shape_Leng | borough | geometry | zone | |
---|---|---|---|---|---|---|---|
0 | 1 | 1 | 0.000782 | 0.116357 | EWR | POLYGON ((-74.18445299999996 40.6949959999999,... | Newark Airport |
1 | 2 | 2 | 0.004866 | 0.433470 | Queens | (POLYGON ((-73.82337597260663 40.6389870471767... | Jamaica Bay |
2 | 3 | 3 | 0.000314 | 0.084341 | Bronx | POLYGON ((-73.84792614099985 40.87134223399991... | Allerton/Pelham Gardens |
3 | 4 | 4 | 0.000112 | 0.043567 | Manhattan | POLYGON ((-73.97177410965318 40.72582128133705... | Alphabet City |
4 | 5 | 5 | 0.000498 | 0.092146 | Staten Island | POLYGON ((-74.17421738099989 40.56256808599987... | Arden Heights |
5 | 6 | 6 | 0.000606 | 0.150491 | Staten Island | POLYGON ((-74.06367318899999 40.60219816599994... | Arrochar/Fort Wadsworth |
6 | 7 | 7 | 0.000390 | 0.107417 | Queens | POLYGON ((-73.90413637799996 40.76752031699986... | Astoria |
7 | 8 | 8 | 0.000027 | 0.027591 | Queens | POLYGON ((-73.92334041500001 40.77512891199993... | Astoria Park |
8 | 9 | 9 | 0.000338 | 0.099784 | Queens | POLYGON ((-73.78502434699996 40.76103651599986... | Auburndale |
9 | 10 | 10 | 0.000436 | 0.099839 | Queens | POLYGON ((-73.7832662499999 40.68999429299992,... | Baisley Park |
10 | 11 | 11 | 0.000265 | 0.079211 | Brooklyn | POLYGON ((-74.00109809499993 40.60303462599992... | Bath Beach |
11 | 12 | 12 | 0.000042 | 0.036661 | Manhattan | POLYGON ((-74.01565756599994 40.70483308799993... | Battery Park |
12 | 13 | 13 | 0.000149 | 0.050281 | Manhattan | POLYGON ((-74.01244109299991 40.7190576729999,... | Battery Park City |
13 | 14 | 14 | 0.001382 | 0.175214 | Brooklyn | POLYGON ((-74.03407329297129 40.64431393298185... | Bay Ridge |
14 | 15 | 15 | 0.000925 | 0.144336 | Queens | POLYGON ((-73.7774039129087 40.79659824126783,... | Bay Terrace/Fort Totten |
15 | 16 | 16 | 0.000872 | 0.141292 | Queens | POLYGON ((-73.7685730499999 40.77910542899991,... | Bayside |
16 | 17 | 17 | 0.000323 | 0.093523 | Brooklyn | POLYGON ((-73.94306406899986 40.70142443499989... | Bedford |
17 | 18 | 18 | 0.000149 | 0.069800 | Bronx | POLYGON ((-73.88513907699999 40.86638287399992... | Bedford Park |
18 | 19 | 19 | 0.000547 | 0.101825 | Queens | POLYGON ((-73.72339596299987 40.75038907599986... | Bellerose |
19 | 20 | 20 | 0.000135 | 0.051440 | Bronx | POLYGON ((-73.88386792099986 40.8642908889999,... | Belmont |
20 | 21 | 21 | 0.000380 | 0.115974 | Brooklyn | POLYGON ((-73.97418385499991 40.6094635019999,... | Bensonhurst East |
21 | 22 | 22 | 0.000472 | 0.126170 | Brooklyn | POLYGON ((-73.99254973599997 40.62427426799996... | Bensonhurst West |
22 | 23 | 23 | 0.002196 | 0.290556 | Staten Island | POLYGON ((-74.19568609223377 40.63501686464005... | Bloomfield/Emerson Hill |
23 | 24 | 24 | 0.000061 | 0.047000 | Manhattan | POLYGON ((-73.95953658899998 40.7987185259999,... | Bloomingdale |
24 | 25 | 25 | 0.000124 | 0.047146 | Brooklyn | POLYGON ((-73.98155298299992 40.68914616399994... | Boerum Hill |
25 | 26 | 26 | 0.000534 | 0.123548 | Brooklyn | POLYGON ((-73.98331628499983 40.6414786819999,... | Borough Park |
26 | 27 | 27 | 0.001341 | 0.202509 | Queens | POLYGON ((-73.86522555399998 40.57045847199989... | Breezy Point/Fort Tilden/Riis Beach |
27 | 28 | 28 | 0.000291 | 0.097961 | Queens | POLYGON ((-73.79240413399991 40.71619304099993... | Briarwood/Jamaica Hills |
28 | 29 | 29 | 0.000202 | 0.071408 | Brooklyn | POLYGON ((-73.96004798699995 40.58326987199995... | Brighton Beach |
29 | 30 | 30 | 0.000146 | 0.094510 | Queens | POLYGON ((-73.82075892499992 40.61523267899991... | Broad Channel |
... | ... | ... | ... | ... | ... | ... | ... |
233 | 234 | 234 | 0.000073 | 0.036072 | Manhattan | POLYGON ((-73.98996936399989 40.73490456699994... | Union Sq |
234 | 235 | 235 | 0.000213 | 0.076167 | Bronx | POLYGON ((-73.90947862999988 40.86180812899987... | University Heights/Morris Heights |
235 | 236 | 236 | 0.000103 | 0.044252 | Manhattan | POLYGON ((-73.95779380499984 40.77359989699993... | Upper East Side North |
236 | 237 | 237 | 0.000096 | 0.042213 | Manhattan | POLYGON ((-73.9661274729999 40.76217929999991,... | Upper East Side South |
237 | 238 | 238 | 0.000185 | 0.060109 | Manhattan | POLYGON ((-73.96884378999985 40.78596738899994... | Upper West Side North |
238 | 239 | 239 | 0.000205 | 0.063626 | Manhattan | POLYGON ((-73.97501417199996 40.78768560599987... | Upper West Side South |
239 | 240 | 240 | 0.000722 | 0.146070 | Bronx | POLYGON ((-73.87643743099994 40.89687059299995... | Van Cortlandt Park |
240 | 241 | 241 | 0.000255 | 0.068765 | Bronx | POLYGON ((-73.88840157099996 40.88441707499993... | Van Cortlandt Village |
241 | 242 | 242 | 0.000360 | 0.138136 | Bronx | POLYGON ((-73.83593362199987 40.84840635599993... | Van Nest/Morris Park |
242 | 243 | 243 | 0.000438 | 0.094331 | Manhattan | POLYGON ((-73.93156536999994 40.86958215799991... | Washington Heights North |
243 | 244 | 244 | 0.000360 | 0.080569 | Manhattan | POLYGON ((-73.94068822000003 40.85131543299985... | Washington Heights South |
244 | 245 | 245 | 0.000466 | 0.095983 | Staten Island | POLYGON ((-74.09787969199995 40.64035805499988... | West Brighton |
245 | 246 | 246 | 0.000281 | 0.069467 | Manhattan | POLYGON ((-74.00439976203513 40.76267135909888... | West Chelsea/Hudson Yards |
246 | 247 | 247 | 0.000206 | 0.092968 | Bronx | POLYGON ((-73.91222180499983 40.84235659099988... | West Concourse |
247 | 248 | 248 | 0.000150 | 0.056919 | Bronx | POLYGON ((-73.86393748099981 40.84004456599994... | West Farms/Bronx River |
248 | 249 | 249 | 0.000072 | 0.036384 | Manhattan | POLYGON ((-74.00250642399995 40.72901638499997... | West Village |
249 | 250 | 250 | 0.000241 | 0.079626 | Bronx | POLYGON ((-73.8455308949999 40.83917330699989,... | Westchester Village/Unionport |
250 | 251 | 251 | 0.000626 | 0.137711 | Staten Island | POLYGON ((-74.13107460299996 40.63114772899996... | Westerleigh |
251 | 252 | 252 | 0.001025 | 0.158004 | Queens | POLYGON ((-73.82049919995306 40.80101146781907... | Whitestone |
252 | 253 | 253 | 0.000078 | 0.036051 | Queens | POLYGON ((-73.83908354399988 40.76525691299991... | Willets Point |
253 | 254 | 254 | 0.000360 | 0.085886 | Bronx | POLYGON ((-73.85186563799999 40.87905886499989... | Williamsbridge/Olinville |
254 | 255 | 255 | 0.000172 | 0.062384 | Brooklyn | POLYGON ((-73.96176070375392 40.72522879205536... | Williamsburg (North Side) |
255 | 256 | 256 | 0.000169 | 0.067915 | Brooklyn | POLYGON ((-73.95834207500002 40.71330630099992... | Williamsburg (South Side) |
256 | 257 | 257 | 0.000139 | 0.058669 | Brooklyn | POLYGON ((-73.97984261899994 40.66072744099996... | Windsor Terrace |
257 | 258 | 258 | 0.000366 | 0.089013 | Queens | POLYGON ((-73.84504194899991 40.68931894699996... | Woodhaven |
258 | 259 | 259 | 0.000395 | 0.126750 | Bronx | POLYGON ((-73.85107116191899 40.91037152011096... | Woodlawn/Wakefield |
259 | 260 | 260 | 0.000422 | 0.133514 | Queens | POLYGON ((-73.9017537339999 40.76077547499995,... | Woodside |
260 | 261 | 261 | 0.000034 | 0.027120 | Manhattan | POLYGON ((-74.01332610899989 40.7050307879999,... | World Trade Center |
261 | 262 | 262 | 0.000122 | 0.049064 | Manhattan | (POLYGON ((-73.94383256699986 40.7828590889999... | Yorkville East |
262 | 263 | 263 | 0.000066 | 0.037017 | Manhattan | POLYGON ((-73.95218621999996 40.7730198449999,... | Yorkville West |
263 rows × 7 columns
tz.plot()
<matplotlib.axes._subplots.AxesSubplot at 0x7fdb6dc399b0>