如何使用正则表达式匹配按列对Pandas数据进行分组

我有以下数据框:

import pandas as pd
df = pd.DataFrame({'id':['a','b','c','d','e'],
                   'XX_111_S5_R12_001_Mobile_05':[-14,-90,-90,-96,-91],
                   'YY_222_S00_R12_001_1-999_13':[-103,0,-110,-114,-114],
                   'ZZ_111_S00_R12_001_1-999_13':[1,2.3,3,5,6],
})

df.set_index('id',inplace=True)
df

看起来像这样:

Out[6]:
    XX_111_S5_R12_001_Mobile_05  YY_222_S00_R12_001_1-999_13  ZZ_111_S00_R12_001_1-999_13
id
a                           -14                         -103                          1.0
b                           -90                            0                          2.3
c                           -90                         -110                          3.0
d                           -96                         -114                          5.0
e                           -91                         -114                          6.0

我想要做的是根据以下正则表达式对列进行分组:

\w+_\w+_\w+_\d+_([\w\d-]+)_\d+

所以最终它被Mobile和1-999分组.

有什么办法呢.我尝试了这个,但未能将它们分组:

import re
grouped = df.groupby(lambda x: re.search("\w+_\w+_\w+_\d+_([\w\d-]+)_\d+", x).group(), axis=1)
for name, group in grouped:
    print name
    print group

哪个印刷品:

XX_111_S5_R12_001_Mobile_05
YY_222_S00_R12_001_1-999_13
ZZ_111_S00_R12_001_1-999_13

我们想要的是名字打印到:

Mobile
1-999
1-999

并且组打印相应的数据框.

最佳答案 您可以在列上使用
.str.extract,以便为您的groupby使用
extract substrings

# Performing the groupby.
pat = '\w+_\w+_\w+_\d+_([\w\d-]+)_\d+'
grouped = df.groupby(df.columns.str.extract(pat, expand=False), axis=1)

# Showing group information.
for name, group in grouped:
    print name
    print group, '\n'

返回预期的组:

1-999
    YY_222_S00_R12_001_1-999_13  ZZ_111_S00_R12_001_1-999_13
id                                                          
a                          -103                          1.0
b                             0                          2.3
c                          -110                          3.0
d                          -114                          5.0
e                          -114                          6.0 

Mobile
    XX_111_S5_R12_001_Mobile_05
id                             
a                           -14
b                           -90
c                           -90
d                           -96
e                           -91 
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