loop over dictionary of pandas dataframes to find identical columns

Question

I have a dictionary of pandas dataframes that have same column names. I want to loop over this dictionary and return columns with identical names with corresponding dataframe name (dictionary key).

I tried to do the following:

for first_dataframe in dct_dataframes.keys():
    for second_dataframe in dct_dataframes.keys():
        if first_dataframe != second_dataframe:
            for column_first_dataframe in dct_dataframes[first_dataframe]:
                for column_second_dataframe in dct_dataframes[second_dataframe]:
                    if column_first_dataframe == column_second_dataframe:
                        print(column_first_dataframe, dct_dataframes[first_dataframe][column_first_dataframe])
                        print(column_second_dataframe, dct_dataframes[second_dataframe][column_second_dataframe])

However, this does not give me correct output.

What should I correct in my loop and is there a way to to avoid this big loop? Thank you

Answer 1

If I understood your question, assuming your dictionary is something like this:

import pandas as pd
dct_dfs = {'df1': pd.DataFrame({'a':[1,2,3],'b':[4,5,6]}),
           'df2': pd.DataFrame({'a':[7,8,9],'b':[10,11,12]})}

Then, I would proceed like this:

for col in dct_dfs['df1']:
    for df in dct_dfs:
        print(dct_dfs[df][col], '\n', df, '\n\n')

Output:

0    1
1    2
2    3
Name: a, dtype: int64 
 df1 

0    7
1    8
2    9
Name: a, dtype: int64 
 df2 

0    4
1    5
2    6
Name: b, dtype: int64 
 df1 

0    10
1    11
2    12
Name: b, dtype: int64 
 df2