Conecting DataFrame in pandas by column name

Question

I have 3 Data Frames:

first:

Country	col1
Afghanistan	6.4
Albania	7.3

sec:

Country	col2
Afghanistan	610
Algeria	983

last:

Country	col3
Afghanistan	1
Angola	2

And I want to connect them by col "Country" and fill the empty values with np.nan to get:

Country	col1	col2	col3
Afghanistan	6.4	601	1
Albania	7.3	NaN	NaN
Algeria	NaN	983	NaN
Angola	NaN	NaN	2

Does this answer your question? [Python: pandas merge multiple dataframes](https://stackoverflow.com/questions/44327999/python-pandas-merge-multiple-dataframes) — Irfanuddin, Jan 09 '22 at 14:54

Irfanuddin · Answer 1 · 2022-01-09T14:48:51.923

You can use df.merge() with type outer for this.

import pandas as pd
from functools import reduce

#create dataframes
df1= pd.DataFrame([["Afghanistan", 6.4], ["Albania", 7.4]], columns=['Country', 'col1'])
df2= pd.DataFrame([["Afghanistan", 610], ["Algeria", 983]], columns=['Country', 'col2'])
df3= pd.DataFrame([["Afghanistan", 1], ["Angola", 2]], columns=['Country', 'col3'])

#merge them all on Country
df_merged = reduce(lambda  left,right: pd.merge(left,right,on=['Country'],
                                            how='outer'), [df1, df2, df3])

       Country  col1   col2  col3
0  Afghanistan   6.4  610.0   1.0
1      Albania   7.4    NaN   NaN
2      Algeria   NaN  983.0   NaN
3       Angola   NaN    NaN   2.0

Conecting DataFrame in pandas by column name

1 Answers1