Merging two dataframes with same column names but different number of columns in pandas

Question

I have two pandas dataframes

df1 = DataFrame([[0,123,321],[0,1543,432]], columns=['A', 'B','C']) df2 = DataFrame([[1,124],[1,1544]], columns=['A', 'C'])

I want to merge these so that the new dataframe would look like below

A | B | C 0 123 321 0 1543 432 1 null 124 1 null 1544

I have tried using append and concat but nothing seems to work. Any help would be much appreciated.

adding the code-snippets for your failed attempts with append & concat will help to resolve specific errors — Joshua Baboo
– Joshua Baboo, Commented Apr 19, 2016 at 18:13

Abbas · Accepted Answer · 2016-04-19 18:09:13Z

11

Concatenate the dataframes

import pandas as pd pd.concat([df1,df2], axis=0) A B C 0 0 123 321 1 0 1543 432 0 1 NaN 124 1 1 NaN 1544

answered Apr 19, 2016 at 18:09

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1 Comment

Thanks this does the trick. I am marking this as answer because it also caters to empty dataframes. Append method doesn't work with empty dataframes.

Jaber Haisan · Accepted Answer · 2023-05-12 04:56:19Z

8

from doc-ref ref try: df1.append(df2, ignore_index=True)

 A B C 0 0 123 321 1 0 1543 432 2 1 NaN 124 3 1 NaN 1544

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answered Apr 19, 2016 at 18:08

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