Cannot remove spaces or trim spaces from column pandas-CodePudding

I'm stuck in simple task. I have a test dataframe with spaces in it. In order to remove them I did following:

df_unique['final'] = df_unique['final'].astype("string")
df_unique['final'] = df_unique['final'].str.strip()
df_unique['final'] = df_unique['final'].str.replace(' ', '')

But still:

df_unique = 

final
 123 123
 123 123 123
 12345 123

df_unique.info() show the column as String.

I think it is not working for DOUBLE spaces numbers. Idk maybe this information will help you

CodePudding user response：

Considering that the dataframe is called df and looks like the following

         final
0      123 123
1  123 123 123
2    12345 123

Assuming that the goal is to create a new column, let's call it new, and store the values of the column final, but without the spaces, one can create a custom lambda function using re as follows

import re

df['new'] = df['final'].apply(lambda x: re.sub(r'\s', '', x))

[Out]:
         final        new
0      123 123     123123
1  123 123 123  123123123
2    12345 123   12345123

If one wants to update the column final, then do the following

df['final'] = df['final'].apply(lambda x: re.sub(r'\s', '', x))

[Out]:
  
       final
0     123123
1  123123123
2   12345123

Another option for this last use case would be using pandas.Series.str.replace as

df['final'] = df['final'].str.replace(r'\s', '', regex=True)

[Out]:

       final
0     123123
1  123123123
2   12345123

Note:

One needs to pass regex=True, else one will get

FutureWarning: The default value of regex will change from True to False in a future version