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Python - Add a prefix to column names in a Pandas DataFrame
To add a prefix to all the column names, use the add_prefix() method. At first, import the required Pandas library −
import pandas as pd
Create a DataFrame with 4 columns −
dataFrame = pd.DataFrame({"Car": ['BMW', 'Lexus', 'Tesla', 'Mustang', 'Mercedes', 'Jaguar'],"Cubic_Capacity": [2000, 1800, 1500, 2500, 2200, 3000],"Reg_Price": [7000, 1500, 5000, 8000, 9000, 6000],"Units_Sold": [ 100, 120, 150, 110, 200, 250]
})Add a prefix to _column to every column using add_prefix() −
dataFrame.add_prefix('column_')
Example
Following is the code −
import pandas as pd
# creating dataframe
dataFrame = pd.DataFrame({"Car": ['BMW', 'Lexus', 'Tesla', 'Mustang', 'Mercedes', 'Jaguar'],"Cubic_Capacity": [2000, 1800, 1500, 2500, 2200, 3000],"Reg_Price": [7000, 1500, 5000, 8000, 9000, 6000],"Units_Sold": [ 100, 120, 150, 110, 200, 250]
})
print"DataFrame ...\n",dataFrame
print"\nUpdated DataFrame...\n",dataFrame.add_prefix('column_')Output
This will produce the following output −
DataFrame ... Car Cubic_Capacity Reg_Price Units_Sold 0 BMW 2000 7000 100 1 Lexus 1800 1500 120 2 Tesla 1500 5000 150 3 Mustang 2500 8000 110 4 Mercedes 2200 9000 200 5 Jaguar 3000 6000 250 Updated DataFrame... column_Car column_Cubic_Capacity column_Reg_Price column_Units_Sold 0 BMW 2000 7000 100 1 Lexus 1800 1500 120 2 Tesla 1500 5000 150 3 Mustang 2500 8000 110 4 Mercedes 2200 9000 200 5 Jaguar 3000 6000 250
Updated on: 21-Sep-2021
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