Pandas Python: Concatenate dataframes having same columns

I think there is problem with duplicated columns names in some or all DataFrames.

#simulate error
df1.columns = ['column3','column1','column1']
df2.columns = ['column5','column1','column1']
df3.columns = ['column2','column1','column1']

df_final = pd.concat([df1, df2, df3])

AssertionError: Number of manager items must equal union of block items # manager items: 4, # tot_items: 5

You can find duplicated columns names:

print (df3.columns[df3.columns.duplicated(keep=False)])
Index(['column1', 'column1'], dtype='object')

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Possible solutions is set columns names by list:

df3.columns = ['column1','column2','column3']
print (df3)
  column1 column2 column3
0       m       n       o
1       p       q       r

Or remove duplicated columns with dupe names:

df31 = df3.loc[:, ~df3.columns.duplicated()]
print (df31)
  column2 column1
0       m       n
1       p       q

Then concat or append should working nice.