CODEWITHSUNDEEP
pythonpandasmerge
HappyPy
HappyPy

Reputation: 10697

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

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 trying to merge the two data frames using the keys from the df1. I think I should use pd.merge for this, but I how can I tell pandas to place the values in the b column of df2 in the a column of df1. This is the output I'm trying to achieve: 

    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

Upvotes: 42

Views: 103046

Answers (3)

Mykola Zotko
Mykola Zotko

Reputation: 17911

You can rename columns and then use functions append or concat:

df2.columns = df1.columns
df1.append(df2, ignore_index=True)
# pd.concat([df1, df2], ignore_index=True)

You can also concatenate both dataframes with vstack from numpy and convert the resulting ndarray to dataframe:

pd.DataFrame(np.vstack([df1, df2]), columns=df1.columns)

Upvotes: 6

scottlittle
scottlittle

Reputation: 20962

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

Upvotes: 27

EdChum
EdChum

Reputation: 394409

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

Upvotes: 57

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