how to concat two data frames with different column names in pandas? - python

Question

df1 = pd.DataFrame({\'a\':[1,2,3],\'x\':[4,5,6],\'y\':[7,8,9]})
df2 = pd.DataFrame({\'b\':[10,11,12],\'x\':[13,14,15],\'y\':[16,17,18]})

I\'m tryin

Answer 1

Use numpy to concatenate the dataframes, so you don't have to rename all of the columns (or explicitly ignore indexes). np.concatenate also works on an arbitrary number of dataframes.

df = pd.DataFrame( np.concatenate( (df1.values, df2.values), axis=0 ) )
df.columns = [ 'a', 'x', 'y' ]
df

Answer 2

Just use concat and rename the column for df2 so it aligns:

In [92]:
pd.concat([df1,df2.rename(columns={'b':'a'})], ignore_index=True)

Out[92]:
    a   x   y
0   1   4   7
1   2   5   8
2   3   6   9
3  10  13  16
4  11  14  17
5  12  15  18

similarly you can use merge but you'd need to rename the column as above:

In [103]:
df1.merge(df2.rename(columns={'b':'a'}),how='outer')

Out[103]:
    a   x   y
0   1   4   7
1   2   5   8
2   3   6   9
3  10  13  16
4  11  14  17
5  12  15  18