使用正则表达式从 Pandas 列中提取子字符串

Question

I have columns with values like this:

Col1

1/1/100 'BA1
1/1/102Packe
1/1/102 'to_

And need to extract just 1/1/100 (from the first row) and so on (1/1/102...)

I am using:

df['col1'] = df['col1'].str.extract('(\d+)/(\d+)/(\d+)', expand=True)

But I'm getting only 1.

Not sure why this is not working, is there a problem with regex or I need some kind of mapping?

Answer 1

You need to only use a single capturing group:

df['col1'] = df['col1'].str.extract('(\d+/\d+/\d+)', expand=True)
                                     ^           ^

The str.extract method returns the value captured with the first capturing group, and your regex captures the first 1 into that group.

Test:

>>> import pandas as pd
>>> df = pd.DataFrame({"col1":["1/1/100 'BA1", "1/1/102Packe", "1/1/102 'to_"]})
>>> df['col1'].str.extract('(\d+/\d+/\d+)', expand=True)
         0
0  1/1/100
1  1/1/102
2  1/1/102

Answer 2

you can try this also,

df['Col1']=df['Col1'].str.replace('\d+|/','')

Note: Regex is more powerful than .str.replace .

Answer 3

我建议这个正则表达式：

df['col1'].str.extract('\b(\d/?)+', expand=True)