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Python - Fetch columns between two Pandas DataFrames by Intersection
To fetch columns between two DataFrames by Intersection, use the intersection() method. Let us 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],
})
# creating dataframe2
dataFrame2 = pd.DataFrame({"Car": ['BMW', 'Lexus', 'Tesla', 'Mustang', 'Mercedes', 'Jaguar'],"Units_Sold": [ 100, 110, 150, 80, 200, 90]
})Fetch common columns −
dataFrame2.columns.intersection(dataFrame1.columns)
Example
Following is the complete code −
import pandas as pd
# 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],
})
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
# getting common columns using intersection()
res = dataFrame2.columns.intersection(dataFrame1.columns)
print"\nCommon columns...\n",resOutput
This will produce the following output −
Dataframe1... Car Cubic_Capacity Reg_Price 0 Bentley 2000 7000 1 Lexus 1800 1500 2 Tesla 1500 5000 3 Mustang 2500 8000 4 Mercedes 2200 9000 5 Jaguar 3000 6000 Dataframe2... Car Units_Sold 0 BMW 100 1 Lexus 110 2 Tesla 150 3 Mustang 80 4 Mercedes 200 5 Jaguar 90 Common columns... Index([u'Car'], dtype='object')
Updated on: 21-Sep-2021
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