Python Pandas – Find the common rows between two Data Frames

Python Server Side Programming Programming

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

AmitDiwan

Published on 15-Sep-2021 08:56:53

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