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tar 讀取





In [1]:



    


import tarfile



    











In [2]:



    


# 檔案名稱格式
filename_format="M06A_{year:04d}{month:02d}{day:02d}.tar.gz".format
xz_filename_format="xz/M06A_{year:04d}{month:02d}{day:02d}.tar.xz".format
csv_format = "M06A/{year:04d}{month:02d}{day:02d}/{hour:02d}/TDCS_M06A_{year:04d}{month:02d}{day:02d}_{hour:02d}0000.csv".format



    











In [3]:



    


# 打開剛才下載的檔案試試
data_config ={"year":2016, "month":12, "day":18}
tar = tarfile.open(filename_format(**data_config), 'r')



    











In [4]:



    


# 如果沒有下載，可以試試看 xz 檔案
#data_dconfig ={"year":2016, "month":11, "day":18}
#tar = tarfile.open(xz_filename_format(**data_config), 'r')



    











In [5]:



    


# 列出內容
tar.list()



    


















    






?rwxrwxrwx nobody/nobody          0 2016-12-19 06:31:22 M06A/20161218/ 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:22 M06A/20161218/19/ 
?rw-r--r-- nobody/nobody   43788302 2016-12-19 06:58:57 M06A/20161218/19/TDCS_M06A_20161218_190000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:21 M06A/20161218/13/ 
?rw-r--r-- nobody/nobody   47797413 2016-12-19 06:58:52 M06A/20161218/13/TDCS_M06A_20161218_130000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:22 M06A/20161218/21/ 
?rw-r--r-- nobody/nobody   34892056 2016-12-19 06:58:58 M06A/20161218/21/TDCS_M06A_20161218_210000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:17 M06A/20161218/00/ 
?rw-r--r-- nobody/nobody   10242555 2016-12-19 06:58:46 M06A/20161218/00/TDCS_M06A_20161218_000000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:20 M06A/20161218/07/ 
?rw-r--r-- nobody/nobody   29010414 2016-12-19 06:58:48 M06A/20161218/07/TDCS_M06A_20161218_070000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:21 M06A/20161218/14/ 
?rw-r--r-- nobody/nobody   56223075 2016-12-19 06:58:53 M06A/20161218/14/TDCS_M06A_20161218_140000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:20 M06A/20161218/10/ 
?rw-r--r-- nobody/nobody   48228393 2016-12-19 06:58:50 M06A/20161218/10/TDCS_M06A_20161218_100000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:22 M06A/20161218/22/ 
?rw-r--r-- nobody/nobody   23328529 2016-12-19 06:58:59 M06A/20161218/22/TDCS_M06A_20161218_220000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:20 M06A/20161218/09/ 
?rw-r--r-- nobody/nobody   44472646 2016-12-19 06:58:49 M06A/20161218/09/TDCS_M06A_20161218_090000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:20 M06A/20161218/03/ 
?rw-r--r-- nobody/nobody    4482391 2016-12-19 06:58:47 M06A/20161218/03/TDCS_M06A_20161218_030000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:20 M06A/20161218/04/ 
?rw-r--r-- nobody/nobody    6234003 2016-12-19 06:58:47 M06A/20161218/04/TDCS_M06A_20161218_040000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:21 M06A/20161218/17/ 
?rw-r--r-- nobody/nobody   51941166 2016-12-19 06:58:55 M06A/20161218/17/TDCS_M06A_20161218_170000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:21 M06A/20161218/15/ 
?rw-r--r-- nobody/nobody   59027318 2016-12-19 06:58:54 M06A/20161218/15/TDCS_M06A_20161218_150000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:20 M06A/20161218/06/ 
?rw-r--r-- nobody/nobody   17867508 2016-12-19 06:58:47 M06A/20161218/06/TDCS_M06A_20161218_060000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:18 M06A/20161218/01/ 
?rw-r--r-- nobody/nobody    6568696 2016-12-19 06:58:46 M06A/20161218/01/TDCS_M06A_20161218_010000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:21 M06A/20161218/12/ 
?rw-r--r-- nobody/nobody   40639579 2016-12-19 06:58:51 M06A/20161218/12/TDCS_M06A_20161218_120000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:21 M06A/20161218/18/ 
?rw-r--r-- nobody/nobody   44388617 2016-12-19 06:58:56 M06A/20161218/18/TDCS_M06A_20161218_180000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:22 M06A/20161218/20/ 
?rw-r--r-- nobody/nobody   41976533 2016-12-19 06:58:57 M06A/20161218/20/TDCS_M06A_20161218_200000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:21 M06A/20161218/16/ 
?rw-r--r-- nobody/nobody   56768259 2016-12-19 06:58:55 M06A/20161218/16/TDCS_M06A_20161218_160000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:20 M06A/20161218/05/ 
?rw-r--r-- nobody/nobody   10337717 2016-12-19 06:58:47 M06A/20161218/05/TDCS_M06A_20161218_050000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:19 M06A/20161218/02/ 
?rw-r--r-- nobody/nobody    4735396 2016-12-19 06:58:46 M06A/20161218/02/TDCS_M06A_20161218_020000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:20 M06A/20161218/08/ 
?rw-r--r-- nobody/nobody   37158659 2016-12-19 06:58:48 M06A/20161218/08/TDCS_M06A_20161218_080000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:20 M06A/20161218/11/ 
?rw-r--r-- nobody/nobody   44919062 2016-12-19 06:58:51 M06A/20161218/11/TDCS_M06A_20161218_110000.csv 
?rwxr-xr-x nobody/nobody          0 2016-12-19 06:31:22 M06A/20161218/23/ 
?rw-r--r-- nobody/nobody   12896245 2016-12-19 06:58:59 M06A/20161218/23/TDCS_M06A_20161218_230000.csv 

















In [6]:



    


# 打開裡面 10 點鐘的資料
csv = tar.extractfile(csv_format(hour=10, **data_config))
# 類似檔案的物件
csv



    


















    
Out[6]:








<ExFileObject name='M06A_20161218.tar.gz'>

















In [7]:



    


# 印出前十行來看看
for i in range(10):
    print(csv.readline().decode())



    


















    






31,2016-12-18 10:00:50,01F1045N,2016-12-18 10:29:01,01F0584N,53.400,Y,2016-12-18 10:00:50+01F1045N; 2016-12-18 10:04:37+01F0979N; 2016-12-18 10:05:58+01F0956N; 2016-12-18 10:07:43+01F0928N; 2016-12-18 10:10:43+01F0880N; 2016-12-18 10:18:38+01F0750N; 2016-12-18 10:27:26+01H0608N; 2016-12-18 10:29:01+01F0584N

31,2016-12-18 10:34:24,01F3525S,2016-12-18 10:46:09,01F3686S,20.200,Y,2016-12-18 10:34:24+01F3525S; 2016-12-18 10:37:13+01F3561S; 2016-12-18 10:39:21+01F3590S; 2016-12-18 10:42:54+01F3640S; 2016-12-18 10:45:26+01F3676S; 2016-12-18 10:46:09+01F3686S

31,2016-12-18 10:57:33,03F3854N,2016-12-18 11:15:23,01F3686S,33.600,Y,2016-12-18 10:57:33+03F3854N; 2016-12-18 11:12:29+01F3640S; 2016-12-18 11:14:45+01F3676S; 2016-12-18 11:15:23+01F3686S

31,2016-12-18 10:05:11,03F0525S,2016-12-18 10:07:39,03F0559S,12.100,Y,2016-12-18 10:05:11+03F0525S; 2016-12-18 10:07:39+03F0559S

31,2016-12-18 10:35:46,01F3185S,2016-12-18 11:05:08,01F3686S,54.100,Y,2016-12-18 10:35:46+01F3185S; 2016-12-18 10:38:12+01F3227S; 2016-12-18 10:39:37+01F3252S; 2016-12-18 10:41:30+01F3286S; 2016-12-18 10:46:13+01F3366S; 2016-12-18 10:47:57+01F3398S; 2016-12-18 10:51:34+01F3460S; 2016-12-18 10:57:54+01F3561S; 2016-12-18 10:59:37+01F3590S; 2016-12-18 11:04:35+01F3676S; 2016-12-18 11:05:08+01F3686S

31,2016-12-18 10:00:35,03F3496N,2016-12-18 10:03:32,03F3445N,16.800,Y,2016-12-18 10:00:35+03F3496N; 2016-12-18 10:03:32+03F3445N

32,2016-12-18 10:00:21,05F0287N,2016-12-18 12:40:50,03F0021N,46.600,Y,2016-12-18 10:00:21+05F0287N; 2016-12-18 12:27:33+05F0055N; 2016-12-18 12:31:28+05F0001N; 2016-12-18 12:32:17+03F0150N; 2016-12-18 12:32:53+03F0140N; 2016-12-18 12:34:24+03F0116N; 2016-12-18 12:38:33+03F0054N; 2016-12-18 12:40:50+03F0021N

31,2016-12-18 10:50:12,01H0271N,2016-12-18 10:55:02,01H0200N,13.300,Y,2016-12-18 10:50:12+01H0271N; 2016-12-18 10:54:30+01H0208N; 2016-12-18 10:55:02+01H0200N

31,2016-12-18 10:09:36,01F0339S,2016-12-18 10:16:15,01H0447S,19.400,Y,2016-12-18 10:09:36+01F0339S; 2016-12-18 10:16:15+01H0447S

32,2016-12-18 10:36:58,01F3696N,2016-12-18 10:43:35,01F3640N,8.000,Y,2016-12-18 10:36:58+01F3696N; 2016-12-18 10:38:24+01F3676N; 2016-12-18 10:43:35+01F3640N

利用 pandas 來處理資料





In [8]:



    


import pandas

csv 欄位依照手冊設定

國道高速公路電子收費交通資料蒐集支援系統(Traffic Data Collection System,TDCS)使用手冊

  • VehicleType： 車種 31(小客車) 、32(小貨車) 、41(大客車) 、42(大貨車) 、5(聯結車)
  • DetectionTime_O：車輛通過本旅次第 1 個偵測站時間
  • GantryID_O： 車輛通過本旅次第 1 個偵測站編號
  • DetectionTime_D： 車輛通過本旅次最後 1 個偵測站時間
  • GantryID_D： 車輛通過本旅次最後 1 個偵測站編號
  • TripLength：本旅次之行駛距離
  • TripEnd：旅次結標記 (Y：旅次正常結束，N：異常)
  • TripInformation： 本旅次經過的各個偵測站之通過時間及偵測站編號




In [9]:



    


# 設定欄位名稱
M06A_fields = ['VehicleType',
               'DetectionTime_O','GantryID_O',
               'DetectionTime_D','GantryID_D ',
               'TripLength', 'TripEnd', 'TripInformation']
# 打開裡面 10 點鐘的資料
csv = tar.extractfile(csv_format(hour=10, **data_config))
# 讀進資料
data = pandas.read_csv(csv, names=M06A_fields)



    











In [10]:



    


data



    


















    
Out[10]:










  
    

      
      VehicleType
      DetectionTime_O
      GantryID_O
      DetectionTime_D
      GantryID_D
      TripLength
      TripEnd
      TripInformation
    

  
  
    

      0
      31
      2016-12-18 10:00:50
      01F1045N
      2016-12-18 10:29:01
      01F0584N
      53.400
      Y
      2016-12-18 10:00:50+01F1045N; 2016-12-18 10:04...
    

    

      1
      31
      2016-12-18 10:34:24
      01F3525S
      2016-12-18 10:46:09
      01F3686S
      20.200
      Y
      2016-12-18 10:34:24+01F3525S; 2016-12-18 10:37...
    

    

      2
      31
      2016-12-18 10:57:33
      03F3854N
      2016-12-18 11:15:23
      01F3686S
      33.600
      Y
      2016-12-18 10:57:33+03F3854N; 2016-12-18 11:12...
    

    

      3
      31
      2016-12-18 10:05:11
      03F0525S
      2016-12-18 10:07:39
      03F0559S
      12.100
      Y
      2016-12-18 10:05:11+03F0525S; 2016-12-18 10:07...
    

    

      4
      31
      2016-12-18 10:35:46
      01F3185S
      2016-12-18 11:05:08
      01F3686S
      54.100
      Y
      2016-12-18 10:35:46+01F3185S; 2016-12-18 10:38...
    

    

      5
      31
      2016-12-18 10:00:35
      03F3496N
      2016-12-18 10:03:32
      03F3445N
      16.800
      Y
      2016-12-18 10:00:35+03F3496N; 2016-12-18 10:03...
    

    

      6
      32
      2016-12-18 10:00:21
      05F0287N
      2016-12-18 12:40:50
      03F0021N
      46.600
      Y
      2016-12-18 10:00:21+05F0287N; 2016-12-18 12:27...
    

    

      7
      31
      2016-12-18 10:50:12
      01H0271N
      2016-12-18 10:55:02
      01H0200N
      13.300
      Y
      2016-12-18 10:50:12+01H0271N; 2016-12-18 10:54...
    

    

      8
      31
      2016-12-18 10:09:36
      01F0339S
      2016-12-18 10:16:15
      01H0447S
      19.400
      Y
      2016-12-18 10:09:36+01F0339S; 2016-12-18 10:16...
    

    

      9
      32
      2016-12-18 10:36:58
      01F3696N
      2016-12-18 10:43:35
      01F3640N
      8.000
      Y
      2016-12-18 10:36:58+01F3696N; 2016-12-18 10:38...
    

    

      10
      31
      2016-12-18 10:59:07
      03F2985N
      2016-12-18 10:59:07
      03F2985N
      3.000
      Y
      2016-12-18 10:59:07+03F2985N
    

    

      11
      32
      2016-12-18 10:18:38
      01F3640N
      2016-12-18 10:44:03
      01F3525N
      18.000
      Y
      2016-12-18 10:18:38+01F3640N; 2016-12-18 10:21...
    

    

      12
      31
      2016-12-18 10:19:12
      01F3460N
      2016-12-18 10:19:12
      01F3460N
      7.100
      Y
      2016-12-18 10:19:12+01F3460N
    

    

      13
      31
      2016-12-18 10:07:39
      03F2261S
      2016-12-18 11:20:08
      01F3019S
      118.805
      Y
      2016-12-18 10:07:39+03F2261S; 2016-12-18 10:10...
    

    

      14
      31
      2016-12-18 10:25:34
      01F0099S
      2016-12-18 10:38:24
      01H0305S
      26.220
      Y
      2016-12-18 10:25:34+01F0099S; 2016-12-18 10:29...
    

    

      15
      31
      2016-12-18 10:26:33
      01F0750S
      2016-12-18 11:01:52
      01F1292S
      62.300
      Y
      2016-12-18 10:26:33+01F0750S; 2016-12-18 10:34...
    

    

      16
      32
      2016-12-18 10:32:41
      01F0099N
      2016-12-18 10:32:41
      01F0099N
      3.700
      Y
      2016-12-18 10:32:41+01F0099N
    

    

      17
      31
      2016-12-18 10:32:55
      05F0438N
      2016-12-18 10:49:58
      05F0287N
      32.000
      Y
      2016-12-18 10:32:55+05F0438N; 2016-12-18 10:41...
    

    

      18
      31
      2016-12-18 10:57:03
      03F2125N
      2016-12-18 12:55:52
      01F0293N
      182.900
      Y
      2016-12-18 10:57:03+03F2125N; 2016-12-18 10:58...
    

    

      19
      31
      2016-12-18 10:15:57
      01F2089N
      2016-12-18 10:27:00
      01F1906N
      21.600
      Y
      2016-12-18 10:15:57+01F2089N; 2016-12-18 10:20...
    

    

      20
      31
      2016-12-18 10:52:17
      03F1992N
      2016-12-18 10:59:48
      01F2011S
      20.200
      Y
      2016-12-18 10:52:17+03F1992N; 2016-12-18 10:56...
    

    

      21
      31
      2016-12-18 10:47:22
      05F0438N
      2016-12-18 11:35:25
      05F0055N
      42.700
      Y
      2016-12-18 10:47:22+05F0438N; 2016-12-18 10:55...
    

    

      22
      42
      2016-12-18 10:44:36
      01F2322S
      2016-12-18 11:50:23
      01F2714S
      52.800
      Y
      2016-12-18 10:44:36+01F2322S; 2016-12-18 10:49...
    

    

      23
      31
      2016-12-18 10:54:52
      01F0413N
      2016-12-18 11:07:08
      01F0233N
      18.300
      Y
      2016-12-18 10:54:52+01F0413N; 2016-12-18 10:57...
    

    

      24
      31
      2016-12-18 10:03:25
      01F3590S
      2016-12-18 10:08:36
      01F3686S
      13.400
      Y
      2016-12-18 10:03:25+01F3590S; 2016-12-18 10:06...
    

    

      25
      31
      2016-12-18 10:00:23
      01F3696N
      2016-12-18 10:00:23
      01F3696N
      3.000
      Y
      2016-12-18 10:00:23+01F3696N
    

    

      26
      31
      2016-12-18 10:32:18
      01F1292N
      2016-12-18 11:31:45
      01F0293N
      105.700
      Y
      2016-12-18 10:32:18+01F1292N; 2016-12-18 10:41...
    

    

      27
      32
      2016-12-18 10:32:47
      01F3185N
      2016-12-18 10:32:47
      01F3185N
      4.100
      Y
      2016-12-18 10:32:47+01F3185N
    

    

      28
      31
      2016-12-18 10:59:35
      03F4021N
      2016-12-18 11:05:05
      03F3916N
      15.700
      Y
      2016-12-18 10:59:35+03F4021N; 2016-12-18 11:05...
    

    

      29
      31
      2016-12-18 10:17:37
      03F4259N
      2016-12-18 10:42:59
      01F3696N
      39.450
      Y
      2016-12-18 10:17:37+03F4259N; 2016-12-18 10:19...
    

    

      ...
      ...
      ...
      ...
      ...
      ...
      ...
      ...
      ...
    

    

      211217
      31
      2016-12-18 10:02:20
      01F0633S
      2016-12-18 10:04:57
      01F0681S
      6.800
      Y
      2016-12-18 10:02:20+01F0633S; 2016-12-18 10:04...
    

    

      211218
      31
      2016-12-18 10:31:03
      03F3392S
      2016-12-18 10:31:03
      03F3392S
      5.300
      Y
      2016-12-18 10:31:03+03F3392S
    

    

      211219
      31
      2016-12-18 10:23:12
      01F2011N
      2016-12-18 10:35:42
      01F1802N
      29.100
      Y
      2016-12-18 10:23:12+01F2011N; 2016-12-18 10:26...
    

    

      211220
      31
      2016-12-18 10:31:45
      01F2483N
      2016-12-18 10:31:45
      01F2483N
      6.500
      Y
      2016-12-18 10:31:45+01F2483N
    

    

      211221
      31
      2016-12-18 10:59:49
      01F3590N
      2016-12-18 11:44:26
      01F3019N
      62.830
      Y
      2016-12-18 10:59:49+01F3590N; 2016-12-18 11:01...
    

    

      211222
      31
      2016-12-18 10:08:06
      01F0155N
      2016-12-18 10:14:58
      01F0061N
      11.800
      Y
      2016-12-18 10:08:06+01F0155N; 2016-12-18 10:08...
    

    

      211223
      31
      2016-12-18 10:27:46
      01F1664S
      2016-12-18 10:32:03
      01F1725S
      8.700
      Y
      2016-12-18 10:27:46+01F1664S; 2016-12-18 10:32...
    

    

      211224
      32
      2016-12-18 10:34:22
      01F2322N
      2016-12-18 11:07:19
      03F1860N
      57.200
      Y
      2016-12-18 10:34:22+01F2322N; 2016-12-18 10:39...
    

    

      211225
      31
      2016-12-18 10:44:07
      01F1839S
      2016-12-18 11:10:42
      01F2249S
      54.600
      Y
      2016-12-18 10:44:07+01F1839S; 2016-12-18 10:48...
    

    

      211226
      31
      2016-12-18 10:34:31
      01F1774N
      2016-12-18 12:37:58
      01F0213N
      161.800
      Y
      2016-12-18 10:34:31+01F1774N; 2016-12-18 10:39...
    

    

      211227
      31
      2016-12-18 10:13:50
      03F0447S
      2016-12-18 10:21:26
      03F0559S
      19.700
      Y
      2016-12-18 10:13:50+03F0447S; 2016-12-18 10:19...
    

    

      211228
      31
      2016-12-18 10:15:02
      03F0338N
      2016-12-18 10:32:39
      05F0055S
      34.300
      Y
      2016-12-18 10:15:02+03F0338N; 2016-12-18 10:17...
    

    

      211229
      31
      2016-12-18 10:03:44
      03F2194N
      2016-12-18 10:07:36
      03F2125N
      11.200
      Y
      2016-12-18 10:03:44+03F2194N; 2016-12-18 10:07...
    

    

      211230
      31
      2016-12-18 10:50:27
      01F0509N
      2016-12-18 11:07:20
      01F0256N
      27.400
      Y
      2016-12-18 10:50:27+01F0509N; 2016-12-18 10:53...
    

    

      211231
      31
      2016-12-18 10:40:34
      01F0155S
      2016-12-18 10:46:52
      01F0248S
      9.900
      Y
      2016-12-18 10:40:34+01F0155S; 2016-12-18 10:42...
    

    

      211232
      31
      2016-12-18 10:42:09
      01F3286N
      2016-12-18 11:20:08
      01F2827N
      57.800
      Y
      2016-12-18 10:42:09+01F3286N; 2016-12-18 10:44...
    

    

      211233
      31
      2016-12-18 10:04:45
      01F2011S
      2016-12-18 10:45:49
      01F2674S
      72.000
      Y
      2016-12-18 10:04:45+01F2011S; 2016-12-18 10:09...
    

    

      211234
      31
      2016-12-18 10:54:48
      03F0087S
      2016-12-18 11:10:55
      03F0337S
      33.500
      Y
      2016-12-18 10:54:48+03F0087S; 2016-12-18 10:56...
    

    

      211235
      31
      2016-12-18 10:07:06
      01F0376N
      2016-12-18 10:15:07
      01F0256N
      16.400
      Y
      2016-12-18 10:07:06+01F0376N; 2016-12-18 10:09...
    

    

      211236
      31
      2016-12-18 10:28:48
      01F3083S
      2016-12-18 10:59:01
      01F3590S
      58.700
      Y
      2016-12-18 10:28:48+01F3083S; 2016-12-18 10:31...
    

    

      211237
      41
      2016-12-18 10:11:58
      03F0337S
      2016-12-18 10:19:36
      03F0447S
      19.500
      Y
      2016-12-18 10:11:58+03F0337S; 2016-12-18 10:15...
    

    

      211238
      31
      2016-12-18 10:57:09
      01F0061N
      2016-12-18 10:57:09
      01F0061N
      1.800
      Y
      2016-12-18 10:57:09+01F0061N
    

    

      211239
      31
      2016-12-18 10:19:51
      03F1651S
      2016-12-18 10:52:50
      03F2129S
      49.800
      Y
      2016-12-18 10:19:51+03F1651S; 2016-12-18 10:23...
    

    

      211240
      31
      2016-12-18 10:58:58
      01F3366S
      2016-12-18 11:17:58
      01F3686S
      38.900
      Y
      2016-12-18 10:58:58+01F3366S; 2016-12-18 11:00...
    

    

      211241
      31
      2016-12-18 10:16:37
      01F2156N
      2016-12-18 10:25:06
      01F2011N
      21.700
      Y
      2016-12-18 10:16:37+01F2156N; 2016-12-18 10:20...
    

    

      211242
      31
      2016-12-18 10:49:57
      03F0648N
      2016-12-18 10:49:57
      03F0648N
      5.600
      Y
      2016-12-18 10:49:57+03F0648N
    

    

      211243
      31
      2016-12-18 10:31:51
      01F0376N
      2016-12-18 10:40:41
      01F0256N
      16.400
      Y
      2016-12-18 10:31:51+01F0376N; 2016-12-18 10:34...
    

    

      211244
      31
      2016-12-18 10:31:30
      03F0846N
      2016-12-18 10:31:30
      03F0846N
      11.000
      Y
      2016-12-18 10:31:30+03F0846N
    

    

      211245
      31
      2016-12-18 10:38:09
      03F3854S
      2016-12-18 10:38:09
      03F3854S
      8.600
      Y
      2016-12-18 10:38:09+03F3854S
    

    

      211246
      31
      2016-12-18 10:44:36
      01F0633S
      2016-12-18 10:44:36
      01F0633S
      2.600
      Y
      2016-12-18 10:44:36+01F0633S
    

  



211247 rows × 8 columns



















In [11]:



    


# 先檢查一下有沒有異常的資料
data[data.TripEnd == 'N'].shape



    


















    
Out[11]:








(0, 8)

















In [12]:



    


# 先去除異常資料
data = data[data.TripEnd == 'Y']



    











In [13]:



    


# 然後乾脆刪掉 TripEnd 這欄
del data['TripEnd']
# 也可以用 data.drop('TripEnd', axis=1, inplace=True)

查看一下內容





In [14]:



    


# 前 5 筆
# 或 data.iloc[:5]
data.head(5)



    


















    
Out[14]:










  
    

      
      VehicleType
      DetectionTime_O
      GantryID_O
      DetectionTime_D
      GantryID_D
      TripLength
      TripInformation
    

  
  
    

      0
      31
      2016-12-18 10:00:50
      01F1045N
      2016-12-18 10:29:01
      01F0584N
      53.4
      2016-12-18 10:00:50+01F1045N; 2016-12-18 10:04...
    

    

      1
      31
      2016-12-18 10:34:24
      01F3525S
      2016-12-18 10:46:09
      01F3686S
      20.2
      2016-12-18 10:34:24+01F3525S; 2016-12-18 10:37...
    

    

      2
      31
      2016-12-18 10:57:33
      03F3854N
      2016-12-18 11:15:23
      01F3686S
      33.6
      2016-12-18 10:57:33+03F3854N; 2016-12-18 11:12...
    

    

      3
      31
      2016-12-18 10:05:11
      03F0525S
      2016-12-18 10:07:39
      03F0559S
      12.1
      2016-12-18 10:05:11+03F0525S; 2016-12-18 10:07...
    

    

      4
      31
      2016-12-18 10:35:46
      01F3185S
      2016-12-18 11:05:08
      01F3686S
      54.1
      2016-12-18 10:35:46+01F3185S; 2016-12-18 10:38...
    

  




















In [15]:



    


# 第  12 筆
data.iloc[11]



    


















    
Out[15]:








VehicleType                                                       32
DetectionTime_O                                  2016-12-18 10:18:38
GantryID_O                                                  01F3640N
DetectionTime_D                                  2016-12-18 10:44:03
GantryID_D                                                  01F3525N
TripLength                                                        18
TripInformation    2016-12-18 10:18:38+01F3640N; 2016-12-18 10:21...
Name: 11, dtype: object

















In [20]:



    


# 對我們來說，其實重要的只有 TripInformation 和 VehicleType
# 先只注意這兩項
data = data[['VehicleType', "TripInformation"]]
data.head(5)



    


















    
Out[20]:










  
    

      
      VehicleType
      TripInformation
    

  
  
    

      0
      31
      2016-12-18 10:00:50+01F1045N; 2016-12-18 10:04...
    

    

      1
      31
      2016-12-18 10:34:24+01F3525S; 2016-12-18 10:37...
    

    

      2
      31
      2016-12-18 10:57:33+03F3854N; 2016-12-18 11:12...
    

    

      3
      31
      2016-12-18 10:05:11+03F0525S; 2016-12-18 10:07...
    

    

      4
      31
      2016-12-18 10:35:46+01F3185S; 2016-12-18 10:38...
    

  




















In [23]:



    


# 查看看小貨車資料
data.query('VehicleType==32')



    


















    
Out[23]:










  
    

      
      VehicleType
      TripInformation
    

  
  
    

      6
      32
      2016-12-18 10:00:21+05F0287N; 2016-12-18 12:27...
    

    

      9
      32
      2016-12-18 10:36:58+01F3696N; 2016-12-18 10:38...
    

    

      11
      32
      2016-12-18 10:18:38+01F3640N; 2016-12-18 10:21...
    

    

      16
      32
      2016-12-18 10:32:41+01F0099N
    

    

      27
      32
      2016-12-18 10:32:47+01F3185N
    

    

      35
      32
      2016-12-18 10:47:00+01F3286N
    

    

      41
      32
      2016-12-18 10:33:12+03F0337S; 2016-12-18 10:37...
    

    

      51
      32
      2016-12-18 10:19:00+03A0041N
    

    

      73
      32
      2016-12-18 10:08:37+05F0528N; 2016-12-18 10:15...
    

    

      82
      32
      2016-12-18 10:21:55+01F0467N
    

    

      102
      32
      2016-12-18 10:18:46+03F2194N; 2016-12-18 10:21...
    

    

      113
      32
      2016-12-18 10:45:24+03A0015S; 2016-12-18 10:47...
    

    

      132
      32
      2016-12-18 10:57:22+01F0061S; 2016-12-18 10:59...
    

    

      135
      32
      2016-12-18 10:30:40+03F1215S; 2016-12-18 10:32...
    

    

      138
      32
      2016-12-18 10:27:27+03A0015S
    

    

      139
      32
      2016-12-18 10:41:46+01F0532N; 2016-12-18 10:45...
    

    

      142
      32
      2016-12-18 10:10:06+01F2930S; 2016-12-18 10:15...
    

    

      148
      32
      2016-12-18 10:31:12+03F0525S
    

    

      151
      32
      2016-12-18 10:37:33+01F3696N; 2016-12-18 10:38...
    

    

      153
      32
      2016-12-18 10:44:38+01F0339S; 2016-12-18 10:51...
    

    

      178
      32
      2016-12-18 10:56:22+03F0116N; 2016-12-18 10:59...
    

    

      189
      32
      2016-12-18 10:54:31+03F1633N; 2016-12-18 11:03...
    

    

      191
      32
      2016-12-18 10:20:16+01F0681N; 2016-12-18 10:21...
    

    

      192
      32
      2016-12-18 10:54:01+03F0006S; 2016-12-18 10:59...
    

    

      198
      32
      2016-12-18 10:03:22+01F0681N; 2016-12-18 10:04...
    

    

      217
      32
      2016-12-18 10:07:19+01F2866N; 2016-12-18 10:09...
    

    

      240
      32
      2016-12-18 10:06:14+01F3686S
    

    

      252
      32
      2016-12-18 10:58:26+01F0681N; 2016-12-18 10:59...
    

    

      260
      32
      2016-12-18 10:56:35+01F2425S; 2016-12-18 11:00...
    

    

      266
      32
      2016-12-18 10:27:24+03F0394S; 2016-12-18 10:31...
    

    

      ...
      ...
      ...
    

    

      211001
      32
      2016-12-18 10:46:54+01F1774N; 2016-12-18 10:51...
    

    

      211010
      32
      2016-12-18 10:30:57+03F2129S
    

    

      211013
      32
      2016-12-18 10:59:17+01H0579N; 2016-12-18 11:06...
    

    

      211016
      32
      2016-12-18 10:44:40+03F4232N; 2016-12-18 10:48...
    

    

      211020
      32
      2016-12-18 10:58:05+01F1664S; 2016-12-18 11:01...
    

    

      211043
      32
      2016-12-18 10:09:03+03F3854S; 2016-12-18 10:12...
    

    

      211045
      32
      2016-12-18 10:48:59+01F3676S; 2016-12-18 10:49...
    

    

      211048
      32
      2016-12-18 10:58:02+03F2231N; 2016-12-18 11:00...
    

    

      211051
      32
      2016-12-18 10:49:30+03F3854N; 2016-12-18 10:55...
    

    

      211052
      32
      2016-12-18 10:32:05+01F2249N; 2016-12-18 10:36...
    

    

      211056
      32
      2016-12-18 10:44:46+01F0467N
    

    

      211063
      32
      2016-12-18 10:07:49+01H0206S; 2016-12-18 10:13...
    

    

      211087
      32
      2016-12-18 10:32:47+03F0525S
    

    

      211094
      32
      2016-12-18 10:38:25+03F0559S
    

    

      211102
      32
      2016-12-18 10:13:04+01F0557N; 2016-12-18 10:14...
    

    

      211111
      32
      2016-12-18 10:58:47+01F0633S; 2016-12-18 11:00...
    

    

      211122
      32
      2016-12-18 10:17:19+01F3696N; 2016-12-18 10:18...
    

    

      211132
      32
      2016-12-18 10:09:31+05F0287N; 2016-12-18 10:35...
    

    

      211146
      32
      2016-12-18 10:05:20+01F0233N; 2016-12-18 10:06...
    

    

      211147
      32
      2016-12-18 10:27:44+01F3366S
    

    

      211150
      32
      2016-12-18 10:29:16+03F2614N; 2016-12-18 10:33...
    

    

      211176
      32
      2016-12-18 10:57:04+01F3696N; 2016-12-18 10:58...
    

    

      211177
      32
      2016-12-18 10:13:31+01F0376N; 2016-12-18 10:15...
    

    

      211178
      32
      2016-12-18 10:14:28+03F0116N; 2016-12-18 10:18...
    

    

      211189
      32
      2016-12-18 10:02:20+03F1944S; 2016-12-18 10:04...
    

    

      211195
      32
      2016-12-18 10:02:16+03F0158S; 2016-12-18 10:05...
    

    

      211201
      32
      2016-12-18 10:06:08+01F0339S
    

    

      211202
      32
      2016-12-18 10:33:47+03F3588N
    

    

      211215
      32
      2016-12-18 10:12:06+01F3460S; 2016-12-18 10:16...
    

    

      211224
      32
      2016-12-18 10:34:22+01F2322N; 2016-12-18 10:39...
    

  



33815 rows × 2 columns



















In [25]:



    


# 或者查看看小客車資料
data[data.VehicleType==31]



    


















    
Out[25]:










  
    

      
      VehicleType
      TripInformation
    

  
  
    

      0
      31
      2016-12-18 10:00:50+01F1045N; 2016-12-18 10:04...
    

    

      1
      31
      2016-12-18 10:34:24+01F3525S; 2016-12-18 10:37...
    

    

      2
      31
      2016-12-18 10:57:33+03F3854N; 2016-12-18 11:12...
    

    

      3
      31
      2016-12-18 10:05:11+03F0525S; 2016-12-18 10:07...
    

    

      4
      31
      2016-12-18 10:35:46+01F3185S; 2016-12-18 10:38...
    

    

      5
      31
      2016-12-18 10:00:35+03F3496N; 2016-12-18 10:03...
    

    

      7
      31
      2016-12-18 10:50:12+01H0271N; 2016-12-18 10:54...
    

    

      8
      31
      2016-12-18 10:09:36+01F0339S; 2016-12-18 10:16...
    

    

      10
      31
      2016-12-18 10:59:07+03F2985N
    

    

      12
      31
      2016-12-18 10:19:12+01F3460N
    

    

      13
      31
      2016-12-18 10:07:39+03F2261S; 2016-12-18 10:10...
    

    

      14
      31
      2016-12-18 10:25:34+01F0099S; 2016-12-18 10:29...
    

    

      15
      31
      2016-12-18 10:26:33+01F0750S; 2016-12-18 10:34...
    

    

      17
      31
      2016-12-18 10:32:55+05F0438N; 2016-12-18 10:41...
    

    

      18
      31
      2016-12-18 10:57:03+03F2125N; 2016-12-18 10:58...
    

    

      19
      31
      2016-12-18 10:15:57+01F2089N; 2016-12-18 10:20...
    

    

      20
      31
      2016-12-18 10:52:17+03F1992N; 2016-12-18 10:56...
    

    

      21
      31
      2016-12-18 10:47:22+05F0438N; 2016-12-18 10:55...
    

    

      23
      31
      2016-12-18 10:54:52+01F0413N; 2016-12-18 10:57...
    

    

      24
      31
      2016-12-18 10:03:25+01F3590S; 2016-12-18 10:06...
    

    

      25
      31
      2016-12-18 10:00:23+01F3696N
    

    

      26
      31
      2016-12-18 10:32:18+01F1292N; 2016-12-18 10:41...
    

    

      28
      31
      2016-12-18 10:59:35+03F4021N; 2016-12-18 11:05...
    

    

      29
      31
      2016-12-18 10:17:37+03F4259N; 2016-12-18 10:19...
    

    

      30
      31
      2016-12-18 10:08:44+01F0248S; 2016-12-18 10:09...
    

    

      31
      31
      2016-12-18 10:01:20+01H0206S; 2016-12-18 10:07...
    

    

      32
      31
      2016-12-18 10:16:13+01H0271N
    

    

      33
      31
      2016-12-18 10:56:15+01H0305S; 2016-12-18 10:58...
    

    

      34
      31
      2016-12-18 10:35:09+03F1332S; 2016-12-18 10:38...
    

    

      36
      31
      2016-12-18 10:22:44+01H0305S; 2016-12-18 10:25...
    

    

      ...
      ...
      ...
    

    

      211214
      31
      2016-12-18 10:30:44+01F3019N; 2016-12-18 10:36...
    

    

      211216
      31
      2016-12-18 10:57:20+03F0447S; 2016-12-18 11:03...
    

    

      211217
      31
      2016-12-18 10:02:20+01F0633S; 2016-12-18 10:04...
    

    

      211218
      31
      2016-12-18 10:31:03+03F3392S
    

    

      211219
      31
      2016-12-18 10:23:12+01F2011N; 2016-12-18 10:26...
    

    

      211220
      31
      2016-12-18 10:31:45+01F2483N
    

    

      211221
      31
      2016-12-18 10:59:49+01F3590N; 2016-12-18 11:01...
    

    

      211222
      31
      2016-12-18 10:08:06+01F0155N; 2016-12-18 10:08...
    

    

      211223
      31
      2016-12-18 10:27:46+01F1664S; 2016-12-18 10:32...
    

    

      211225
      31
      2016-12-18 10:44:07+01F1839S; 2016-12-18 10:48...
    

    

      211226
      31
      2016-12-18 10:34:31+01F1774N; 2016-12-18 10:39...
    

    

      211227
      31
      2016-12-18 10:13:50+03F0447S; 2016-12-18 10:19...
    

    

      211228
      31
      2016-12-18 10:15:02+03F0338N; 2016-12-18 10:17...
    

    

      211229
      31
      2016-12-18 10:03:44+03F2194N; 2016-12-18 10:07...
    

    

      211230
      31
      2016-12-18 10:50:27+01F0509N; 2016-12-18 10:53...
    

    

      211231
      31
      2016-12-18 10:40:34+01F0155S; 2016-12-18 10:42...
    

    

      211232
      31
      2016-12-18 10:42:09+01F3286N; 2016-12-18 10:44...
    

    

      211233
      31
      2016-12-18 10:04:45+01F2011S; 2016-12-18 10:09...
    

    

      211234
      31
      2016-12-18 10:54:48+03F0087S; 2016-12-18 10:56...
    

    

      211235
      31
      2016-12-18 10:07:06+01F0376N; 2016-12-18 10:09...
    

    

      211236
      31
      2016-12-18 10:28:48+01F3083S; 2016-12-18 10:31...
    

    

      211238
      31
      2016-12-18 10:57:09+01F0061N
    

    

      211239
      31
      2016-12-18 10:19:51+03F1651S; 2016-12-18 10:23...
    

    

      211240
      31
      2016-12-18 10:58:58+01F3366S; 2016-12-18 11:00...
    

    

      211241
      31
      2016-12-18 10:16:37+01F2156N; 2016-12-18 10:20...
    

    

      211242
      31
      2016-12-18 10:49:57+03F0648N
    

    

      211243
      31
      2016-12-18 10:31:51+01F0376N; 2016-12-18 10:34...
    

    

      211244
      31
      2016-12-18 10:31:30+03F0846N
    

    

      211245
      31
      2016-12-18 10:38:09+03F3854S
    

    

      211246
      31
      2016-12-18 10:44:36+01F0633S
    

  



168197 rows × 2 columns

Content source: tjwei/HackNTU_Data_2017

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