Replace a part of string in Pandas Data Column, replace doesn't work

Question

I have been trying to clean my data column by taking a part of the text out. Unfortunately cannot get my head around it.

I tried using the .replace method in pandas series, but that did not seem to have worked

df['Salary Estimate'].str.replace(' (Glassdoor est.)', '',regex=True)


0       $53K-$91K (Glassdoor est.)
1      $63K-$112K (Glassdoor est.)
2       $80K-$90K (Glassdoor est.)
3       $56K-$97K (Glassdoor est.)
4      $86K-$143K (Glassdoor est.)
                  ...             
922                             -1
925                             -1
928    $59K-$125K (Glassdoor est.)
945    $80K-$142K (Glassdoor est.)
948    $62K-$113K (Glassdoor est.)
Name: Salary Estimate, Length: 600, dtype: object

What I expected was

0       $53K-$91K
1      $63K-$112K
2       $80K-$90K
3       $56K-$97K
4      $86K-$143K
                  ...             
922                             -1
925                             -1
928    $59K-$125K
945    $80K-$142K
948    $62K-$113K
Name: Salary Estimate, Length: 600, dtype: object`

Answer 1

If you enable regex, you have to escape regex symbol like (, ) or .:

import re

>>> df['Salary Estimate'].str.replace(re.escape(r' (Glassdoor est.)'), '',regex=True)
0     $53K-$91K
1    $63K-$112K
2     $80K-$90K
3     $56K-$97K
4    $86K-$143K
Name: Salary Estimate, dtype: object

# Or without import re module
>>> df['Salary Estimate'].str.replace(r' \(Glassdoor est\.\)', '',regex=True)
0     $53K-$91K
1    $63K-$112K
2     $80K-$90K
3     $56K-$97K
4    $86K-$143K
Name: Salary Estimate, dtype: object

You can also extract numbers:

>>> df['Salary Estimate'].str.extract(r'\$(?P<min>\d+)K-\$(?P<max>\d+)K')
  min  max
0  53   91
1  63  112
2  80   90
3  56   97
4  86  143