检查数据，如果数据无效，请返回或打印这些记录

Question

嗨，我有一个没有标题的数据文件，并且其中有14个字段，我正在使用提取方法根据模式检查其中的几个字段。我正在按列检查数据。它确实验证数据没有问题，但是唯一的问题是它返回true / false。如果数据与模式不匹配，我想打印整行，或打印格式不正确的值。我不确定如何实现。

下面是我到目前为止尝试过的代码

import pandas as pd
import re
try:
    df = pd.read_csv("E:\data.txt", delimiter='\t', dtype=str, header=None)
    x= len(df.index)
    print(x)
except Exception as e:
    print (e)
try:
    df[0]= df[0].str.match('(\d\d\d\d-\d\d-\d\d)')
except Exception as e:
    print (e)

try:
    df[1]= df[1].str.match('(\d\d:\d\d:\d\d)')
except Exception as e:
    print (e)

try:        
    df[2]= df[2].str.match('(\d\d.\d\d\d\d*)')
except Exception as e:
    print (e)

try:   
    df[3]= df[3].str.match('-(\d\d.\d\d\d\d*)')
except Exception as e:
    print (e)

try:   
    df[5]= df[5].str.match('(\d\d*)')
except Exception as e:
    print (e)

try:   
    df[6]= df[6].str.match('(\d\d.\d\d\d\d*)')
except Exception as e:
    print (e)

try:   
    df[7]= df[7].str.match('(\d\d.\d\d\d\d*)')
except Exception as e:
    print (e)
print(df)

try:   
    df[13]= df[13].str.match('(\d\d*)')
except Exception as e:
    print (e)
print(df)

下面是样本数据集：

018-01-01   00:04:43    43.71678    -79.44384   Tow 53  43.75544    -79.43828   C100    1   WL28    CCG P2  00:16:29
2018-01-01  00:09:10    43.78304    -79.23663   Lockout 30  43.79497    -79.23394   C2  4   WL5 CCG     00:10:05
2018-01-01  00:15:49    43.24116    -79.85282   Lockout 134 43.39425    -79.98044   H23 9   F109    CCG     00:48:16
2018-01-01  00:16:47    43.76756    -79.41196   Flatbed Tow 435 43.77409    -79.49313   C23 10  FB88    CCG     00:18:19
2018-01-01  00:18:53    43.26671    -79.96222   Tow 172 43.2412 -79.85274   H23 11  F109    CCG     02:42:04
2018-01-01  00:22:59    43.8088942  -79.2698542 No service  35  43.78196    -79.2351    C2  50001   WL5 CLUB_AUTO       00:23:04
2018-01-01  00:25:39    43.57866    -79.63927   Tow 304 43.59991    -79.67094   C950    14  F157    CCG     02:46:21
2018-01-01  00:26:27    43.72097    -79.47553   Lockout 152 43.81375    -79.36767   C950    15  F124    CCG P2  00:50:35
2018-01-01  00:26:56    43.785702   -79.729198  Jump Start/Battery Test 55  43.68537    -79.80871   C28 50003   FB6 CCG     00:52:26
2018-01-01  00:28:08    43.79901    -79.42031   Flatbed Tow 67  43.94571    -79.44134   C950    50004   F124    CLUB_AUTO       00:35:10
2018-01-01  00:33:26    43.67615    -79.7707    Tow 84  0   0   C28 19  FB6 CCG P2  00:54:30
2018-01-01  00:41:30    44.07323    -79.48489   Tow 9   44.06664    -79.42858   C512    22  FB1 CCG     00:42:50
2018-01-01  00:43:36    43.62484    -79.55517   Tow 43  43.68514    -79.59623   C16 23  WL1 CCG P5  00:53:31
2018-01-01  00:43:40    43.7088 -79.39456   Flat tire, with Spare   64  43.70485    -79.29617   A18 24  LS1 CCG     00:47:33
2018-01-01  00:47:24    43.87896    -79.49169   Tow 96  43.81937    -79.56436   C950    26  F157    CCG     01:12:33
2018-01-01  00:48:17    44.90311    -79.43861   Winch/Extrication   87  0   0   R130    27  SHOP    CCG P2  00:58:46
2018-01-01  00:48:38    0   0   Flat tire, with Spare   72  43.22824    -79.77316   G30 50006   WL1 RAP_RSO RP  00:54:38
2018-01-01  00:51:39    44.26556    -78.35797   No service  55  44.25686    -78.28151   P151    30  FB3 CCG     00:54:11
2018-01-01  00:52:36    43.68888    -79.32561   Tow 272 43.7969 -79.42919   C950    31  F117    CCG     04:04:21
2018-01-01  00:53:08    43.68968    -79.74152   No service  132 43.69461    -79.71206   C28 32  FB6 CCG     02:30:03
2018-01-01  00:55:14    44.2455058  -76.9499712 Tow 49  44.28096    -76.56847   K112M   50007   MD2 CLUB_AUTO       00:57:35
2018-01-01  00:57:00    46.31401    -83.94554   Winch/Extrication   189 46.52989    -84.37611   R829    36  FB2 CCG     01:11:20
2018-01-01  00:58:23    43.444523   -80.497246  No service  59  43.48807    -80.5573    G23 50008   F105    CCG     01:10:51
2018-01-01  00:59:31    42.26581    -82.4183    Tow 84

Answer 1

IIUC，也许您可​​以尝试这样的事情：

dd = {1:'(\d\d:\d\d:\d\d)'
     ,2:'(\d\d.\d{4,})'
     ,3:'-(\d\d.\d{4,})'
     ,5:'(\d\d*)'}

for i, j in dd.items():
    print(f'Checking column {i}')
    print(df[~df[i].astype(str).str.match(j)])