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Intersection of two dataframe in Pandas - Python

Last Updated : 26 Jul, 2020
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Intersection of Two data frames in Pandas can be easily calculated by using the pre-defined function merge(). This function takes both the data frames as argument and returns the intersection between them. Syntax:
pd.merge(df1, df2, how)
Example 1: Python3 1==
import pandas as pd

# Creating Data frames
df1 = {'A': [1, 2, 3, 4],
         'B': ['abc', 'def', 'efg', 'ghi']} 
df2 = {'A': [1, 2, 3, 4 ],
         'B': ['Geeks', 'For', 'efg', 'ghi'],
         'C':['Nikhil', 'Rishabh', 'Rahul', 'Shubham']} 
         
d1 = pd.DataFrame(df1)
d2 = pd.DataFrame(df2) 

# Calling merge() function
int_df = pd.merge(d1, d2, how ='inner', on =['A', 'B'])
print(int_df)
Output:
   A    B        C
0  3  efg    Rahul
1  4  ghi  Shubham
Example 2: Python3 1==
import pandas as pd

# Creating Data frames
df1 = {'A': [1, 2, 3, 4],
         'B': ['Geeks', 'For', 'efg', 'ghi']} 
df2 = {'A': [1, 2, 3, 4 ],
         'B': ['Geeks', 'For', 'abc', 'cde'],
         'C':['Nikhil', 'Rishabh', 'Rahul', 'Shubham']} 
         
d1 = pd.DataFrame(df1)
d2 = pd.DataFrame(df2) 

# Calling merge() function
int_df = pd.merge(d1, d2, how='inner', on=['A', 'B'])
print(int_df)
Output:
   A      B        C
0  1  Geeks   Nikhil
1  2    For  Rishabh

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