Fetch Columns Between Two Pandas DataFrames by Intersection in Python

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",res

Output

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')