Cannot remove spaces or trim spaces from column pandas

Question

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

Answer 1

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