如何分割数字和文字

Question

I have a dataset like this

data = pd.DataFrame({ 'a' : [5, 5, '2 bad']})

I want to convert this to

{ 'a.digits' : [5, 5, 2], 'a.text' : [nan, nan, 'bad']}

I can get 'a.digits' as bellow

data['a.digits'] = data['a'].replace('[^0-9]', '', regex = True) 
5    2
2    1
Name: a, dtype: int64

When i do

data['a'] = data['a'].replace('[^\D]', '', regex = True)

or

data['a'] = data['a'].replace('[^a-zA-Z]', '', regex = True)

i get

5      2
bad    1
Name: a, dtype: int64

What's wrong? How to remove digits?

Answer 1

Something like this would suffice?

In [8]: import numpy as np

In [9]: import re

In [10]: data['a.digits'] = data['a'].apply(lambda x: int(re.sub(r'[\D]', '', str(x))))

In [12]: data['a.text'] = data['a'].apply(lambda x: re.sub(r'[\d]', '', str(x)))

In [13]: data.replace('', np.nan, regex=True)
Out[13]: 
       a a.digits a.text
0      5        5    NaN
1      5        5    NaN
2  2 bad        2    bad

Answer 2

假设在2和Bad之间有一个空格，您可以这样做：

data['Text'] = data['a'].str.split(' ').str[1]