Please add force_suffixes to pandas.merge()

Code Sample, a copy-pastable example if possible

import pandas as pd

A = pd.DataFrame({'colname': [1, 2]})

B = pd.DataFrame({'colname': [1, 2]})

C = pd.DataFrame({'colname': [1, 2]})

D = pd.merge(A, B, right_index=True, left_index=True, suffixes=('_A', '_B'))

print(pd.merge(D, B, right_index=True, left_index=True, suffixes=('', '_C'))

>   colname_A  colname_B  colname
> 0          1          1        1
> 1          2          2        2

Problem description

When using pandas.merge() suffixes are only added to the column-names if a column-name appears in both data frames. With more than two data frames that can lead to the above situation. The first merge adds suffixes. When the resulting table is merged with a third table the column-name does not appear twice and the suffix is not added. The suffix then needs to be added manually. This is overhead, especially when larger numbers of data-frames are merged. An option “force_suffixes” would be appreciated that ensures the suffix is added.

Expected Output

>   colname_A  colname_B  colname_C
> 0          1          1        1
> 1          2          2        2

[TheRealPJC]

I agree - this very useful.

[ThomasProctor]

Here’s the kludge I’ve been using to do this. Maybe it will help with a fix. I make no claims to it being remotely well-engineered

def merge_force_suffix(left, right, **kwargs):
    on_col = kwargs['on']
    suffix_tupple = kwargs['suffixes']
    
    def suffix_col(col, suffix):
        if col != on_col:
            return str(col) + suffix
        else:
            return col
            
    left_suffixed = left.rename(columns=lambda x: suffix_col(x, suffix_tupple[0]))
    right_suffixed = right.rename(columns=lambda x: suffix_col(x, suffix_tupple[1]))
    del kwargs['suffixes']
    return pd.merge(left_suffixed, right_suffixed, **kwargs)