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Python – Get the Columns Shared by Two Pandas DataFrames using Numpy
To get the columns shared by two DataFrames, use the intersect1d() method. This method is provided by numpy, so you need to import Numpy also with Pandas. Let us first import the required libraries −
import pandas as pd import numpy as np
Create two DataFrames −
# creating dataframe1
dataFrame1 = pd.DataFrame({"Car": ['Bentley', 'Lexus', 'Tesla', 'Mustang', 'Mercedes', 'Jaguar'],"Cubic_Capacity": [2000, 1800, 1500, 2500, 2200, 3000],"Reg_Price": [7000, 1500, 5000, 8000, 9000, 6000],"Units_Sold": [ 100, 110, 150, 80, 200, 90]
})
# creating dataframe2
dataFrame2 = pd.DataFrame({"Car": ['BMW', 'Lexus', 'Tesla', 'Mustang', 'Mercedes', 'Jaguar'],"Units_Sold": [ 100, 110, 150, 80, 200, 90]
})Get common columns using the numpy method intersect1d() −
res = np.intersect1d(dataFrame2.columns, dataFrame1.columns)
Example
Following is the code −
import pandas as pd
import numpy as np
# creating dataframe1
dataFrame1 = pd.DataFrame({"Car": ['Bentley', 'Lexus', 'Tesla', 'Mustang', 'Mercedes', 'Jaguar'],"Cubic_Capacity": [2000, 1800, 1500, 2500, 2200, 3000],"Reg_Price": [7000, 1500, 5000, 8000, 9000, 6000],"Units_Sold": [ 100, 110, 150, 80, 200, 90]
})
print"Dataframe1...\n",dataFrame1
# creating dataframe2
dataFrame2 = pd.DataFrame({"Car": ['BMW', 'Lexus', 'Tesla', 'Mustang', 'Mercedes', 'Jaguar'],"Units_Sold": [ 100, 110, 150, 80, 200, 90]
})
print"Dataframe2...\n",dataFrame2
# get common columns using intersect1d()
res = np.intersect1d(dataFrame2.columns, dataFrame1.columns)
print"\nCommon columns...\n",resOutput
This will produce the following output −
Dataframe1... Car Cubic_Capacity Reg_Price Units_Sold 0 Bentley 2000 7000 100 1 Lexus 1800 1500 110 2 Tesla 1500 5000 150 3 Mustang 2500 8000 80 4 Mercedes 2200 9000 200 5 Jaguar 3000 6000 90 Dataframe2... Car Units_Sold 0 BMW 100 1 Lexus 110 2 Tesla 150 3 Mustang 80 4 Mercedes 200 5 Jaguar 90 Common columns... ['Car' 'Units_Sold']
Updated on: 22-Sep-2021
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