Pandas Join() | Mastering in Python Pandas Library
Pandas Join() Method in Python
import pandas as pd
df1 = pd.DataFrame({'A': [1,2,3],
'B': [10,20,30]})
df2 = pd.DataFrame({'C': [4,5,6],
'D': [40,50,60]})
display(df1, df2)
Output >>>
A B
0 1 10
1 2 20
2 3 30
C D
0 4 40
1 5 50
2 6 60
df1.join(df2)
Output >>>
A B C D
0 1 10 4 40
1 2 20 5 50
2 3 30 6 60
df2.join(df1)
Output >>>
C D A B
0 4 40 1 10
1 5 50 2 20
2 6 60 3 30
df1 = pd.DataFrame({'A': [1,2,3],
'B': [10,20,30]},
index = ['a','b','c'])
df2 = pd.DataFrame({'C': [4,5,6],
'D': [40,50,60]},
index = ['a','b','c'])
display(df1, df2)
Output >>>
A B
a 1 10
b 2 20
c 3 30
C D
a 4 40
b 5 50
c 6 60
df1.join(df2)
Output >>>
A B C D
a 1 10 4 40
b 2 20 5 50
c 3 30 6 60
df1 = pd.DataFrame({'A': [1,2,3],
'B': [10,20,30]},
index = ['a','b','c'])
df2 = pd.DataFrame({'C': [4,5],
'D': [40,50]},
index = ['a','b'])
display(df1, df2)
Output >>>
A B
a 1 10
b 2 20
c 3 30
C D
a 4 40
b 5 50
df1.join(df2)
Output >>>
A B C D
a 1 10 4.0 40.0
b 2 20 5.0 50.0
c 3 30 NaN NaN
df1.join(df2, how = 'right')
Output >>>
A B C D
a 1 10 4 40
b 2 20 5 50
df1.join(df2, how = 'inner')
Output >>>
A B C D
a 1 10 4 40
b 2 20 5 50
df1.join(df2, how = 'outer')
Output >>>
A B C D
a 1 10 4.0 40.0
b 2 20 5.0 50.0
c 3 30 NaN NaN
df1 = pd.DataFrame({'A': [1,2,3],
'B': [10,20,30]})
df2 = pd.DataFrame({'A': [4,5,6],
'D': [40,50,60]})
display(df1, df2)
Output >>>
A B
0 1 10
1 2 20
2 3 30
A D
0 4 40
1 5 50
2 6 60
df1.join(df2, lsuffix = '_1')
Output >>>
A_1 B A D
a 1 10 4.0 40.0
b 2 20 5.0 50.0
c 3 30 NaN NaN
df1.join(df2, rsuffix = '_1')
Output >>>
A B A_1 D
a 1 10 4.0 40.0
b 2 20 5.0 50.0
c 3 30 NaN NaN