I've got two dataframes i would like to join, however, the dont contain exactly the same rows.
I've got this in the dataframe1
test1 1 test2 3 test5 4 test6 5 test7 6 And this in dataframe2
test1 4 test3 5 test4 6 test5 3 test6 3 What I would like to achieve is the following
col1 col2 test1 1 4 test2 3 test3 5 test4 6 test5 4 3 test6 5 3 test7 6 or
col1 col2 test1 1 4 test2 3 0 test3 0 5 test4 0 6 test5 4 3 test6 5 3 test7 6 0 Use pd.merge with how='outer':
In [1539]: df1 Out[1539]: col val 0 test1 1 1 test2 3 2 test5 4 3 test6 5 4 test7 6 In [1540]: df2 Out[1540]: col val 0 test1 4 1 test3 5 2 test4 6 3 test5 3 4 test6 3 In [1541]: df1.merge(df2, on='col', how='outer') Out[1541]: col val_x val_y 0 test1 1.0 4.0 1 test2 3.0 NaN 2 test5 4.0 3.0 3 test6 5.0 3.0 4 test7 6.0 NaN 5 test3 NaN 5.0 6 test4 NaN 6.0 In [1542]: df1.merge(df2, on='col', how='outer').fillna(0) Out[1542]: col val_x val_y 0 test1 1.0 4.0 1 test2 3.0 0.0 2 test5 4.0 3.0 3 test6 5.0 3.0 4 test7 6.0 0.0 5 test3 0.0 5.0 6 test4 0.0 6.0 
Use merge, which is inner join by default:
pd.merge(dataframe1, dataframe2, left_index=True, right_index=True) Or join, which is left join by default:
dataframe1.join(dataframe2) Or concat, which is outer join by default:
pd.concat([dataframe1, dataframe2], axis=1)