如何在熊猫数据框中用另一列拆分一列

时间:2019-07-11 08:56:27

标签: python pandas dataframe split data-cleaning

我正在清理pandas数据框中的数据,我想将一列拆分为另一列。

我想按“ eNBID”列拆分“ id”列,但不知道如何拆分

import pandas as pd

id_list = ['4600375067649','4600375077246','460037495681','460037495694']
eNBID_list = ['750676','750772','749568','749569']
df=pd.DataFrame({'id':id_list,'eNBID':eNBID_list})

df.head()

id                  eNBID
4600375067649       750676
4600375077246       750772
460037495681        749568
460037495694        749569

What I want:

df.head()

id                     eNBID
460-03-750676-49       750676
460-03-750772-46       750772
460-03-749568-1        749568
460-03-749569-4        749569

#column 'eNBID' is the third part of column 'id', the item length in column 'eNBID' is 6 or 7.

2 个答案:

答案 0 :(得分:1)

考虑46003对于所有ID均保持不变

df['id'] = df.apply(lambda x: '-'.join([i[:3]+'-'+i[3:] if '460' in i else i for i in list(re.findall('(\w*)'+'('+x.eNBID+')'+'(\w*)',x.id)[0])]), axis=1)

输出

                 id   eNBID
0  460-03-750676-49  750676
1  460-03-750772-46  750772
2   460-03-749568-1  749568
3   460-03-749569-4  749569

答案 1 :(得分:0)

在第3、5、11位之后考虑“-”:

df['id'] = df['id'].apply(lambda s: s[:3] + '-' + s[3:5] + '-' + s[5:11] + '-' + s[11:])