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