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In [63]:

    
import numpy as np 
import pandas as pd

# plots
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline

trip= pd.read_csv('trip.csv')
#wed= pd.read_csv('weather.csv')



In [15]:

    
trip.sample(2)
#trip.dtypes









    Out[15]:






  
    
      
      id
      duration
      start_date
      start_station_name
      start_station_id
      end_date
      end_station_name
      end_station_id
      bike_id
      subscription_type
      zip_code
    
  
  
    
      178891
      384502
      1347
      7/29/2014 8:50
      Mountain View Caltrain Station
      28
      7/29/2014 9:13
      San Antonio Shopping Center
      31
      146
      Subscriber
      94133
    
    
      11479
      20196
      902
      9/13/2013 11:59
      South Van Ness at Market
      66
      9/13/2013 12:14
      Commercial at Montgomery
      45
      202
      Subscriber
      94115



In [4]:

    
#Cantidad de viajes por bike
trip = trip['duration'].sum()
trip









    Out[4]:





742280971



In [53]:

    
# Number of duration per bike -  consultar*
#trip.groupby('duration').sum()['bike_id'].plot(figsize=(14,4));
trip.groupby('bike_id').sum()['duration'].plot(figsize=(14,4));
#trip3 = trip[trip['bike_id'] == 34]
#trip3



In [2]:

    
# Top five bikes durations - falta ver como lo puedo graficar. Grafico anterior*
trip.sort_values('duration',ascending=False).head(5)









    Out[2]:






  
    
      
      id
      duration
      start_date
      start_station_name
      start_station_id
      end_date
      end_station_name
      end_station_id
      bike_id
      subscription_type
      zip_code
    
  
  
    
      573566
      568474
      17270400
      12/6/2014 21:59
      South Van Ness at Market
      66
      6/24/2015 20:18
      2nd at Folsom
      62
      535
      Customer
      95531
    
    
      382718
      825850
      2137000
      6/28/2015 21:50
      Market at Sansome
      77
      7/23/2015 15:27
      Yerba Buena Center of the Arts (3rd @ Howard)
      68
      466
      Customer
      97213
    
    
      440339
      750192
      1852590
      5/2/2015 6:17
      San Antonio Shopping Center
      31
      5/23/2015 16:53
      Castro Street and El Camino Real
      32
      680
      Subscriber
      94024
    
    
      371066
      841176
      1133540
      7/10/2015 10:35
      University and Emerson
      35
      7/23/2015 13:27
      University and Emerson
      35
      262
      Customer
      94306
    
    
      80510
      111309
      722236
      11/30/2013 13:29
      University and Emerson
      35
      12/8/2013 22:06
      University and Emerson
      35
      247
      Customer
      94301



In [5]:

    
# Top five bikes less durations 
#trip.sort_index('duration',ascending=False).head(5)


#Are trip getting longer or shorter?
# susbcripciones length by time, are subscriptions getting longer or shorter ? 
trip.groupby('subscription_type').mean().loc[:,'duration'].plot(linewidth=2,figsize=(12,8));



In [16]:

    
trip.loc[trip.duration>722236,["id","bike_id", "duration"]].sort_values(by="duration",ascending=False).head(10)



In [17]:

    
trip.loc[trip.duration<722236,["id","bike_id", "duration"]].sort_values(by="duration",ascending=False).head(10)



In [9]:

    
# Histogram of ratings*
trip['duration'].hist(figsize=(16,8));



In [10]:

    
# Histogram of durations
#trip = trip['duration'].value_counts()
trip.hist(figsize=(12,8),bins=20,);



In [33]:

    
# Histogram of bikes
trip = trip['bike_id'].value_counts()
trip = trip[trip > 5000]
#trip.plot(kind='bar',rot=90,figsize=(12,8));



In [ ]:

    
#stat= pd.read_csv('status.csv', low_memory=False)
#stat.head(3)
stat= pd.read_csv('status.csv', iterator=True, chunksize=500)  # gives TextFileReader, which is iterable with chunks of 1000 rows.
df = pd.concat(stat, ignore_index=True)  # df is DataFrame. If errors, do `list(tp)` instead of `tp`
df.sample(3)



In [30]:

    
#CON SIOMA
#rated_movies = pd.merge(movies,ratings, left_on='movieId', right_on='movieId', how='inner')
#rated_movies.sample(2)

#Cantidad de viajes por dia con el mismo startdate
#test = trip.groupby(['start_date'])['id'].count()
#test.head()

tw = pd.merge(trip,wed, left_on='start_date', right_on='date', how='outer')
tw.head()
#tw.sample(2)









    Out[30]:






  
    
      
      id
      duration
      start_date
      start_station_name
      start_station_id
      end_date
      end_station_name
      end_station_id
      bike_id
      subscription_type
      ...
      mean_visibility_miles
      min_visibility_miles
      max_wind_Speed_mph
      mean_wind_speed_mph
      max_gust_speed_mph
      precipitation_inches
      cloud_cover
      events
      wind_dir_degrees
      zip_code_y
    
  
  
    
      0
      4576.0
      63.0
      8/29/2013 14:13
      South Van Ness at Market
      66.0
      8/29/2013 14:14
      South Van Ness at Market
      66.0
      520.0
      Subscriber
      ...
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
    
    
      1
      4578.0
      4521.0
      8/29/2013 14:13
      San Francisco City Hall
      58.0
      8/29/2013 15:29
      Townsend at 7th
      65.0
      623.0
      Customer
      ...
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
    
    
      2
      4577.0
      4524.0
      8/29/2013 14:13
      San Francisco City Hall
      58.0
      8/29/2013 15:28
      Townsend at 7th
      65.0
      632.0
      Customer
      ...
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
    
    
      3
      4607.0
      70.0
      8/29/2013 14:42
      San Jose City Hall
      10.0
      8/29/2013 14:43
      San Jose City Hall
      10.0
      661.0
      Subscriber
      ...
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
    
    
      4
      4130.0
      71.0
      8/29/2013 10:16
      Mountain View City Hall
      27.0
      8/29/2013 10:17
      Mountain View City Hall
      27.0
      48.0
      Subscriber
      ...
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
    
  

5 rows × 35 columns



In [77]:

    
# Top five bikes start_date - falta ver como lo puedo graficar. Grafico anterior*
#ver como puedo hacer los de menor salida 
trip.sort_values('start_date',ascending=False).head(5)









    Out[77]:






  
    
      
      id
      duration
      start_date
      start_station_name
      start_station_id
      end_date
      end_station_name
      end_station_id
      bike_id
      subscription_type
      zip_code
    
  
  
    
      661658
      444343
      483
      9/9/2014 9:59
      Yerba Buena Center of the Arts (3rd @ Howard)
      68
      9/9/2014 10:07
      Market at 10th
      67
      593
      Subscriber
      94107
    
    
      661659
      444342
      228
      9/9/2014 9:59
      Townsend at 7th
      65
      9/9/2014 10:02
      San Francisco Caltrain (Townsend at 4th)
      70
      411
      Subscriber
      94107
    
    
      661660
      444341
      630
      9/9/2014 9:55
      Harry Bridges Plaza (Ferry Building)
      50
      9/9/2014 10:05
      2nd at South Park
      64
      394
      Subscriber
      94706
    
    
      661661
      444340
      513
      9/9/2014 9:54
      Harry Bridges Plaza (Ferry Building)
      50
      9/9/2014 10:02
      Market at 4th
      76
      590
      Customer
      94133
    
    
      661664
      444337
      561
      9/9/2014 9:53
      Harry Bridges Plaza (Ferry Building)
      50
      9/9/2014 10:02
      2nd at Townsend
      61
      393
      Subscriber
      94960



In [5]:

    
# Number of trip by station_id
#trip['start_station_name'].value_counts()[0:19].plot(kind='bar',figsize=(14,4));
#TopOstations = trip['start_station_name'].value_counts()[0:29].index.tolist()
#Dataframe[column].value_counts().index.tolist()
#['apple', 'sausage', 'banana', 'cheese']
trip.sort_index(by='duration', ascending=[False])









    



/home/dai/anaconda2/lib/python2.7/site-packages/ipykernel/__main__.py:6: FutureWarning: by argument to sort_index is deprecated, pls use .sort_values(by=...)






    Out[5]:






  
    
      
      id
      duration
      start_date
      start_station_name
      start_station_id
      end_date
      end_station_name
      end_station_id
      bike_id
      subscription_type
      zip_code
    
  
  
    
      573566
      568474
      17270400
      12/6/2014 21:59
      South Van Ness at Market
      66
      6/24/2015 20:18
      2nd at Folsom
      62
      535
      Customer
      95531
    
    
      382718
      825850
      2137000
      6/28/2015 21:50
      Market at Sansome
      77
      7/23/2015 15:27
      Yerba Buena Center of the Arts (3rd @ Howard)
      68
      466
      Customer
      97213
    
    
      440339
      750192
      1852590
      5/2/2015 6:17
      San Antonio Shopping Center
      31
      5/23/2015 16:53
      Castro Street and El Camino Real
      32
      680
      Subscriber
      94024
    
    
      371066
      841176
      1133540
      7/10/2015 10:35
      University and Emerson
      35
      7/23/2015 13:27
      University and Emerson
      35
      262
      Customer
      94306
    
    
      80510
      111309
      722236
      11/30/2013 13:29
      University and Emerson
      35
      12/8/2013 22:06
      University and Emerson
      35
      247
      Customer
      94301
    
    
      606063
      522337
      720454
      10/30/2014 8:29
      Redwood City Caltrain Station
      22
      11/7/2014 15:36
      Stanford in Redwood City
      25
      692
      Customer
      94010
    
    
      223016
      323594
      716480
      6/13/2014 16:57
      Harry Bridges Plaza (Ferry Building)
      50
      6/21/2014 23:59
      Civic Center BART (7th at Market)
      72
      633
      Subscriber
      94131
    
    
      195379
      361321
      715339
      7/13/2014 5:50
      Arena Green / SAP Center
      14
      7/21/2014 12:32
      Adobe on Almaden
      5
      251
      Customer
      nil
    
    
      421839
      774999
      688899
      5/20/2015 15:27
      Palo Alto Caltrain Station
      34
      5/28/2015 14:49
      California Ave Caltrain Station
      36
      230
      Customer
      nil
    
    
      524521
      635260
      655939
      2/8/2015 3:05
      San Jose Civic Center
      3
      2/15/2015 17:17
      SJSU 4th at San Carlos
      12
      132
      Customer
      89451
    
    
      287337
      237942
      644771
      4/6/2014 3:37
      South Van Ness at Market
      66
      4/13/2014 14:44
      Clay at Battery
      41
      369
      Customer
      94014
    
    
      93400
      129504
      619322
      12/18/2013 9:16
      San Jose Diridon Caltrain Station
      2
      12/25/2013 13:18
      SJSU 4th at San Carlos
      12
      653
      Subscriber
      94041
    
    
      443792
      745640
      611240
      4/29/2015 9:41
      University and Emerson
      35
      5/6/2015 11:28
      San Antonio Shopping Center
      31
      196
      Customer
      81
    
    
      524518
      635263
      602338
      2/8/2015 3:09
      San Jose Civic Center
      3
      2/15/2015 2:28
      San Jose Civic Center
      3
      9
      Customer
      89451
    
    
      20535
      32121
      597517
      9/23/2013 18:24
      California Ave Caltrain Station
      36
      9/30/2013 16:23
      Palo Alto Caltrain Station
      34
      168
      Customer
      95051
    
    
      418295
      779645
      594550
      5/24/2015 13:33
      San Pedro Square
      6
      5/31/2015 10:42
      San Pedro Square
      6
      39
      Customer
      95118
    
    
      119830
      166010
      586356
      1/25/2014 20:00
      San Antonio Caltrain Station
      29
      2/1/2014 14:53
      San Antonio Caltrain Station
      29
      693
      Customer
      94303
    
    
      152689
      421286
      560792
      8/23/2014 9:48
      Rengstorff Avenue / California Street
      33
      8/29/2014 21:35
      Mountain View Caltrain Station
      28
      90
      Customer
      94040
    
    
      393058
      812544
      552697
      6/18/2015 10:45
      Mountain View Caltrain Station
      28
      6/24/2015 20:17
      Palo Alto Caltrain Station
      34
      70
      Customer
      90024
    
    
      505391
      661326
      531240
      2/27/2015 15:45
      San Jose Diridon Caltrain Station
      2
      3/5/2015 19:19
      SJSU 4th at San Carlos
      12
      662
      Customer
      95112
    
    
      252081
      284683
      517856
      5/14/2014 21:14
      Castro Street and El Camino Real
      32
      5/20/2014 21:05
      San Antonio Shopping Center
      31
      670
      Customer
      94040
    
    
      517402
      644642
      505483
      2/14/2015 17:30
      San Pedro Square
      6
      2/20/2015 13:54
      San Pedro Square
      6
      22
      Customer
      95136
    
    
      379557
      830135
      502617
      7/1/2015 14:12
      Redwood City Medical Center
      26
      7/7/2015 9:49
      Redwood City Caltrain Station
      22
      15
      Customer
      nil
    
    
      640982
      473196
      489435
      9/28/2014 18:21
      Japantown
      9
      10/4/2014 10:19
      Japantown
      9
      685
      Customer
      95116
    
    
      155325
      417776
      464952
      8/21/2014 6:16
      Market at 4th
      76
      8/26/2014 15:26
      Davis at Jackson
      42
      466
      Customer
      94102
    
    
      619315
      504411
      457110
      10/17/2014 18:49
      Market at 10th
      67
      10/23/2014 1:47
      Market at 10th
      67
      415
      Customer
      94582
    
    
      43549
      62246
      429384
      10/17/2013 16:06
      Davis at Jackson
      42
      10/22/2013 15:23
      Powell Street BART
      39
      465
      Customer
      43113
    
    
      287336
      237943
      411846
      4/6/2014 3:38
      South Van Ness at Market
      66
      4/10/2014 22:02
      Civic Center BART (7th at Market)
      72
      634
      Customer
      94014
    
    
      574968
      566582
      410157
      12/4/2014 21:55
      Harry Bridges Plaza (Ferry Building)
      50
      12/9/2014 15:51
      2nd at Folsom
      62
      572
      Customer
      nil
    
    
      531427
      626177
      405271
      1/30/2015 21:25
      Japantown
      9
      2/4/2015 14:00
      Paseo de San Antonio
      7
      117
      Customer
      95112
    
    
      ...
      ...
      ...
      ...
      ...
      ...
      ...
      ...
      ...
      ...
      ...
      ...
    
    
      2887
      8576
      60
      9/2/2013 9:40
      Harry Bridges Plaza (Ferry Building)
      50
      9/2/2013 9:41
      Harry Bridges Plaza (Ferry Building)
      50
      354
      Subscriber
      94102
    
    
      616421
      508274
      60
      10/21/2014 11:57
      San Francisco Caltrain 2 (330 Townsend)
      69
      10/21/2014 11:58
      San Francisco Caltrain 2 (330 Townsend)
      69
      578
      Subscriber
      94107
    
    
      88852
      122928
      60
      12/12/2013 9:18
      Powell at Post (Union Square)
      71
      12/12/2013 9:19
      Powell at Post (Union Square)
      71
      614
      Subscriber
      94103
    
    
      406816
      794867
      60
      6/4/2015 19:13
      Steuart at Market
      74
      6/4/2015 19:14
      Steuart at Market
      74
      461
      Subscriber
      94103
    
    
      92925
      128828
      60
      12/17/2013 17:28
      Steuart at Market
      74
      12/17/2013 17:29
      Steuart at Market
      74
      409
      Subscriber
      94105
    
    
      511423
      652693
      60
      2/21/2015 12:45
      Powell Street BART
      39
      2/21/2015 12:46
      Powell Street BART
      39
      532
      Customer
      92111
    
    
      510302
      654272
      60
      2/23/2015 14:12
      Beale at Market
      56
      2/23/2015 14:13
      Beale at Market
      56
      672
      Subscriber
      94402
    
    
      98183
      136099
      60
      12/26/2013 15:55
      2nd at South Park
      64
      12/26/2013 15:56
      2nd at South Park
      64
      423
      Subscriber
      94107
    
    
      509279
      655741
      60
      2/24/2015 9:18
      2nd at Townsend
      61
      2/24/2015 9:19
      2nd at Townsend
      61
      498
      Subscriber
      94403
    
    
      252114
      284638
      60
      5/14/2014 20:11
      Market at 10th
      67
      5/14/2014 20:12
      Market at 10th
      67
      372
      Subscriber
      94107
    
    
      456799
      728496
      60
      4/16/2015 13:39
      Embarcadero at Sansome
      60
      4/16/2015 13:40
      Embarcadero at Sansome
      60
      496
      Subscriber
      94521
    
    
      213972
      335844
      60
      6/23/2014 17:31
      Powell Street BART
      39
      6/23/2014 17:32
      Powell Street BART
      39
      407
      Subscriber
      94102
    
    
      556034
      592699
      60
      1/6/2015 11:38
      South Van Ness at Market
      66
      1/6/2015 11:39
      Market at 10th
      67
      621
      Subscriber
      94123
    
    
      531011
      626726
      60
      2/1/2015 8:02
      San Francisco Caltrain 2 (330 Townsend)
      69
      2/1/2015 8:03
      San Francisco Caltrain 2 (330 Townsend)
      69
      452
      Subscriber
      94107
    
    
      55127
      77650
      60
      10/30/2013 18:22
      Harry Bridges Plaza (Ferry Building)
      50
      10/30/2013 18:23
      Harry Bridges Plaza (Ferry Building)
      50
      416
      Subscriber
      94110
    
    
      181744
      380584
      60
      7/25/2014 17:30
      Castro Street and El Camino Real
      32
      7/25/2014 17:31
      Castro Street and El Camino Real
      32
      155
      Subscriber
      94133
    
    
      115725
      160479
      60
      1/21/2014 13:01
      2nd at Townsend
      61
      1/21/2014 13:02
      2nd at Townsend
      61
      320
      Subscriber
      94115
    
    
      547555
      603851
      60
      1/14/2015 12:37
      Golden Gate at Polk
      59
      1/14/2015 12:38
      Golden Gate at Polk
      59
      548
      Subscriber
      94109
    
    
      345157
      874889
      60
      8/4/2015 9:57
      San Francisco Caltrain 2 (330 Townsend)
      69
      8/4/2015 9:58
      San Francisco Caltrain 2 (330 Townsend)
      69
      374
      Subscriber
      94107
    
    
      666342
      438041
      60
      9/4/2014 10:53
      Civic Center BART (7th at Market)
      72
      9/4/2014 10:54
      Civic Center BART (7th at Market)
      72
      291
      Subscriber
      94117
    
    
      40000
      57581
      60
      10/14/2013 14:47
      Clay at Battery
      41
      10/14/2013 14:48
      Clay at Battery
      41
      368
      Subscriber
      94158
    
    
      597389
      534343
      60
      11/7/2014 9:45
      Temporary Transbay Terminal (Howard at Beale)
      55
      11/7/2014 9:46
      Temporary Transbay Terminal (Howard at Beale)
      55
      300
      Subscriber
      94107
    
    
      542394
      611456
      60
      1/20/2015 17:46
      Embarcadero at Folsom
      51
      1/20/2015 17:47
      Embarcadero at Folsom
      51
      471
      Subscriber
      95032
    
    
      194364
      362788
      60
      7/14/2014 14:09
      Powell Street BART
      39
      7/14/2014 14:10
      Powell Street BART
      39
      372
      Subscriber
      94102
    
    
      633879
      483333
      60
      10/4/2014 19:21
      Yerba Buena Center of the Arts (3rd @ Howard)
      68
      10/4/2014 19:22
      Yerba Buena Center of the Arts (3rd @ Howard)
      68
      560
      Customer
      nil
    
    
      10457
      18792
      60
      9/12/2013 10:09
      Civic Center BART (7th at Market)
      72
      9/12/2013 10:10
      Civic Center BART (7th at Market)
      72
      632
      Subscriber
      94103
    
    
      326026
      900176
      60
      8/21/2015 13:24
      Temporary Transbay Terminal (Howard at Beale)
      55
      8/21/2015 13:25
      Temporary Transbay Terminal (Howard at Beale)
      55
      522
      Subscriber
      94109
    
    
      450401
      736948
      60
      4/22/2015 17:47
      Embarcadero at Folsom
      51
      4/22/2015 17:48
      Embarcadero at Folsom
      51
      585
      Subscriber
      94103
    
    
      72159
      100171
      60
      11/18/2013 15:01
      Temporary Transbay Terminal (Howard at Beale)
      55
      11/18/2013 15:02
      Temporary Transbay Terminal (Howard at Beale)
      55
      469
      Subscriber
      94158
    
    
      2925
      8651
      60
      9/2/2013 10:50
      San Francisco Caltrain 2 (330 Townsend)
      69
      9/2/2013 10:51
      San Francisco Caltrain 2 (330 Townsend)
      69
      544
      Subscriber
      94107
    
  

669959 rows × 11 columns



In [15]:

    
#Cargo los datos nuevamente pero parseando las duraciones
trip2 = pd.read_csv('trip.csv', parse_dates=['duration'])
#Observacion de los tipos de datos
trip2.tail(3)









    Out[15]:






  
    
      
      id
      duration
      start_date
      start_station_name
      start_station_id
      end_date
      end_station_name
      end_station_id
      bike_id
      subscription_type
      zip_code
    
  
  
    
      669956
      432949
      538
      9/1/2014 0:05
      South Van Ness at Market
      66
      9/1/2014 0:14
      5th at Howard
      57
      466
      Customer
      32
    
    
      669957
      432948
      568
      9/1/2014 0:05
      South Van Ness at Market
      66
      9/1/2014 0:15
      5th at Howard
      57
      461
      Customer
      32
    
    
      669958
      432947
      569
      9/1/2014 0:05
      South Van Ness at Market
      66
      9/1/2014 0:15
      5th at Howard
      57
      318
      Customer
      32



In [20]:

    
#podemos los primeros valores 
trip.head(3)









    Out[20]:






  
    
      
      id
      duration
      start_date
      start_station_name
      start_station_id
      end_date
      end_station_name
      end_station_id
      bike_id
      subscription_type
      zip_code
    
  
  
    
      0
      4576
      63
      8/29/2013 14:13
      South Van Ness at Market
      66
      8/29/2013 14:14
      South Van Ness at Market
      66
      520
      Subscriber
      94127
    
    
      1
      4607
      70
      8/29/2013 14:42
      San Jose City Hall
      10
      8/29/2013 14:43
      San Jose City Hall
      10
      661
      Subscriber
      95138
    
    
      2
      4130
      71
      8/29/2013 10:16
      Mountain View City Hall
      27
      8/29/2013 10:17
      Mountain View City Hall
      27
      48
      Subscriber
      97214



In [22]:

    
#y los ultimos
trip.tail(5)









    Out[22]:






  
    
      
      id
      duration
      start_date
      start_station_name
      start_station_id
      end_date
      end_station_name
      end_station_id
      bike_id
      subscription_type
      zip_code
    
  
  
    
      669954
      432951
      619
      9/1/2014 4:21
      Powell Street BART
      39
      9/1/2014 4:32
      Townsend at 7th
      65
      335
      Subscriber
      94118
    
    
      669955
      432950
      6712
      9/1/2014 3:16
      Harry Bridges Plaza (Ferry Building)
      50
      9/1/2014 5:08
      San Francisco Caltrain (Townsend at 4th)
      70
      259
      Customer
      44100
    
    
      669956
      432949
      538
      9/1/2014 0:05
      South Van Ness at Market
      66
      9/1/2014 0:14
      5th at Howard
      57
      466
      Customer
      32
    
    
      669957
      432948
      568
      9/1/2014 0:05
      South Van Ness at Market
      66
      9/1/2014 0:15
      5th at Howard
      57
      461
      Customer
      32
    
    
      669958
      432947
      569
      9/1/2014 0:05
      South Van Ness at Market
      66
      9/1/2014 0:15
      5th at Howard
      57
      318
      Customer
      32



In [23]:

    
trip['start_station_name'][:3] #realizamos una proyeccion









    Out[23]:





0    63
1    70
2    71
Name: duration, dtype: int64



In [78]:

    
duration_station = trip['duration'].value_counts()
%matplotlib notebook
# top 20
duration_station[:5].plot('bar');



In [79]:

    
fig = plt.figure(figsize=(10,4));

trip['subscription_type'].value_counts().plot('bar');



In [75]:

    
#Que estacion de Origen tiene las mayor cantidad¶
trip['start_station_name'].value_counts()[:10].plot('bar');



In [69]:

    
trip['start_station_name'].value_counts()[:20].plot('bar');



In [73]:

    
trip['start_station_name'].value_counts()[10:].plot('bar');



In [ ]:



In [ ]:

	id	duration	start_date	start_station_name	start_station_id	end_date	end_station_name	end_station_id	bike_id	subscription_type	zip_code
178891	384502	1347	7/29/2014 8:50	Mountain View Caltrain Station	28	7/29/2014 9:13	San Antonio Shopping Center	31	146	Subscriber	94133
11479	20196	902	9/13/2013 11:59	South Van Ness at Market	66	9/13/2013 12:14	Commercial at Montgomery	45	202	Subscriber	94115

	id	duration	start_date	start_station_name	start_station_id	end_date	end_station_name	end_station_id	bike_id	subscription_type	zip_code
573566	568474	17270400	12/6/2014 21:59	South Van Ness at Market	66	6/24/2015 20:18	2nd at Folsom	62	535	Customer	95531
382718	825850	2137000	6/28/2015 21:50	Market at Sansome	77	7/23/2015 15:27	Yerba Buena Center of the Arts (3rd @ Howard)	68	466	Customer	97213
440339	750192	1852590	5/2/2015 6:17	San Antonio Shopping Center	31	5/23/2015 16:53	Castro Street and El Camino Real	32	680	Subscriber	94024
371066	841176	1133540	7/10/2015 10:35	University and Emerson	35	7/23/2015 13:27	University and Emerson	35	262	Customer	94306
80510	111309	722236	11/30/2013 13:29	University and Emerson	35	12/8/2013 22:06	University and Emerson	35	247	Customer	94301

	id	bike_id	duration
606063	522337	692	720454
223016	323594	633	716480
195379	361321	251	715339
421839	774999	230	688899
524521	635260	132	655939
287337	237942	369	644771
93400	129504	653	619322
443792	745640	196	611240
524518	635263	9	602338
20535	32121	168	597517

	id	duration	start_date	start_station_name	start_station_id	end_date	end_station_name	end_station_id	bike_id	subscription_type	...	mean_visibility_miles	min_visibility_miles	max_wind_Speed_mph	mean_wind_speed_mph	max_gust_speed_mph	precipitation_inches	cloud_cover	events	wind_dir_degrees	zip_code_y
0	4576.0	63.0	8/29/2013 14:13	South Van Ness at Market	66.0	8/29/2013 14:14	South Van Ness at Market	66.0	520.0	Subscriber	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1	4578.0	4521.0	8/29/2013 14:13	San Francisco City Hall	58.0	8/29/2013 15:29	Townsend at 7th	65.0	623.0	Customer	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2	4577.0	4524.0	8/29/2013 14:13	San Francisco City Hall	58.0	8/29/2013 15:28	Townsend at 7th	65.0	632.0	Customer	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
3	4607.0	70.0	8/29/2013 14:42	San Jose City Hall	10.0	8/29/2013 14:43	San Jose City Hall	10.0	661.0	Subscriber	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
4	4130.0	71.0	8/29/2013 10:16	Mountain View City Hall	27.0	8/29/2013 10:17	Mountain View City Hall	27.0	48.0	Subscriber	...	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

	id	duration	start_date	start_station_name	start_station_id	end_date	end_station_name	end_station_id	bike_id	subscription_type	zip_code
661658	444343	483	9/9/2014 9:59	Yerba Buena Center of the Arts (3rd @ Howard)	68	9/9/2014 10:07	Market at 10th	67	593	Subscriber	94107
661659	444342	228	9/9/2014 9:59	Townsend at 7th	65	9/9/2014 10:02	San Francisco Caltrain (Townsend at 4th)	70	411	Subscriber	94107
661660	444341	630	9/9/2014 9:55	Harry Bridges Plaza (Ferry Building)	50	9/9/2014 10:05	2nd at South Park	64	394	Subscriber	94706
661661	444340	513	9/9/2014 9:54	Harry Bridges Plaza (Ferry Building)	50	9/9/2014 10:02	Market at 4th	76	590	Customer	94133
661664	444337	561	9/9/2014 9:53	Harry Bridges Plaza (Ferry Building)	50	9/9/2014 10:02	2nd at Townsend	61	393	Subscriber	94960

	id	duration	start_date	start_station_name	start_station_id	end_date	end_station_name	end_station_id	bike_id	subscription_type	zip_code
669956	432949	538	9/1/2014 0:05	South Van Ness at Market	66	9/1/2014 0:14	5th at Howard	57	466	Customer	32
669957	432948	568	9/1/2014 0:05	South Van Ness at Market	66	9/1/2014 0:15	5th at Howard	57	461	Customer	32
669958	432947	569	9/1/2014 0:05	South Van Ness at Market	66	9/1/2014 0:15	5th at Howard	57	318	Customer	32

	id	duration	start_date	start_station_name	start_station_id	end_date	end_station_name	end_station_id	bike_id	subscription_type	zip_code
0	4576	63	8/29/2013 14:13	South Van Ness at Market	66	8/29/2013 14:14	South Van Ness at Market	66	520	Subscriber	94127
1	4607	70	8/29/2013 14:42	San Jose City Hall	10	8/29/2013 14:43	San Jose City Hall	10	661	Subscriber	95138
2	4130	71	8/29/2013 10:16	Mountain View City Hall	27	8/29/2013 10:17	Mountain View City Hall	27	48	Subscriber	97214

	id	duration	start_date	start_station_name	start_station_id	end_date	end_station_name	end_station_id	bike_id	subscription_type	zip_code
669954	432951	619	9/1/2014 4:21	Powell Street BART	39	9/1/2014 4:32	Townsend at 7th	65	335	Subscriber	94118
669955	432950	6712	9/1/2014 3:16	Harry Bridges Plaza (Ferry Building)	50	9/1/2014 5:08	San Francisco Caltrain (Townsend at 4th)	70	259	Customer	44100
669956	432949	538	9/1/2014 0:05	South Van Ness at Market	66	9/1/2014 0:14	5th at Howard	57	466	Customer	32
669957	432948	568	9/1/2014 0:05	South Van Ness at Market	66	9/1/2014 0:15	5th at Howard	57	461	Customer	32
669958	432947	569	9/1/2014 0:05	South Van Ness at Market	66	9/1/2014 0:15	5th at Howard	57	318	Customer	32