Concatenate dataframe with some columns equals and some columns different-CodePudding

I am trying to concatenate two Dataframes but an error occurs systematically and I don't know how to correct it.

I saw an example of what I want to do on the Pandas documentation :

However, I am trying to do the same on my two dataframe :

df1 :

df2 :

Some columns are similar but some of them are different. I used reset_index(drop=True) in order to avoid this problem even if the index of each dataframe are different.

I am trying to do this : pd.concat([df1, df2], ignore_index=True, sort=False) but I have this error :

Can somebody have an idea of how I could solve this error ? Thanks in advance for your time !

CodePudding user response：

Reset the indices by hand, transpose the dataframes, do an outer join, then transpose them back.

import pandas as pd

df1 = pd.DataFrame({'A': [1,2,3,4,5], 'B':[2,3,4,5,6], 'C':[-9,-2,-1,8,0]})
df2 = pd.DataFrame({'A': [4,5], 'B':[2,6], 'D':[9,0]})

df1.index = range(df1.shape[0])
df2.index = range(df1.shape[0], df1.shape[0] df2.shape[0])

result = df1.T.join(df2.T, how='outer').T
result

     A    B    C    D
0  1.0  2.0 -9.0  NaN
1  2.0  3.0 -2.0  NaN
2  3.0  4.0 -1.0  NaN
3  4.0  5.0  8.0  NaN
4  5.0  6.0  0.0  NaN
5  4.0  2.0  NaN  9.0
6  5.0  6.0  NaN  0.0