Python Pandas – Find the common rows between two Data Frames

To find the common rows between two DataFrames, use the merge() method. Let us first create DataFrame1 with two columns −

dataFrame1 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Tesla', 'Bentley', 'Jaguar'], "Units": [100, 150, 110, 80, 110, 90] } )

Create DataFrame2 with two columns −

dataFrame2 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Bentley', 'Jaguar'], "Units": [100, 250, 150, 80, 130, 90] } )

To find the common rows −

dataFrame1.merge(dataFrame2, how = 'inner' ,indicator=False) 

Example

Following is the code −

import pandas as pd # Create DataFrame1 dataFrame1 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Tesla', 'Bentley', 'Jaguar'], "Units": [100, 150, 110, 80, 110, 90] } ) print"DataFrame1 ...\n",dataFrame1 # Create DataFrame2 dataFrame2 = pd.DataFrame( { "Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Bentley', 'Jaguar'], "Units": [100, 250, 150, 80, 130, 90] } ) print"\nDataFrame2 ...\n",dataFrame2 # check for equality print"\nAre both the DataFrames equal? ",dataFrame1.equals(dataFrame2) # finding common rows between two DataFrames resData = dataFrame1.merge(dataFrame2, how = 'inner' ,indicator=False) print"\nCommon rows between two DataFrames...\n",resData

Output

This will produce the following output −

DataFrame1 ...        Car   Units 0      BMW    100 1    Lexus    150 2     Audi    110 3    Tesla     80 4  Bentley    110 5   Jaguar     90 DataFrame2 ...        Car   Units 0      BMW    100 1    Lexus    250 2     Audi    150 3  Mustang     80 4  Bentley    130 5   Jaguar     90 Are both the DataFrames equal? False Common rows between two DataFrames...     Car Units 0     BMW 100 1  Jaguar 90