Intersection of two dataframe in Pandas – Python
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:
import pandas as pd # Creating Data framesdf1 = {'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() functionint_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:
import pandas as pd # Creating Data framesdf1 = {'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() functionint_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
