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Create a Pipeline and remove a column from DataFrame - Python Pandas
Use the colDrop() method of pdpipe library to remove a column from Pandas DataFrame. At first, import the required pdpipe and pandas libraries with their respective aliases −
import pdpipe as pdp import pandas as pd
Let us create a DataFrame. Here, we have two columns −
dataFrame = pd.DataFrame(
{
"Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Bentley', 'Jaguar'],"Units": [100, 150, 110, 80, 110, 90]
}
)To remove a column from the DataFrame, use the ColDrop() method. Here, we are removing the “Units” column −
resDF = pdp.ColDrop("Units").apply(dataFrame)
Example
Following is the complete code −
import pdpipe as pdp
import pandas as pd
# Create DataFrame
dataFrame = pd.DataFrame(
{
"Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Bentley', 'Jaguar'],"Units": [100, 150, 110, 80, 110, 90]
}
)
print("DataFrame ...\n",dataFrame)
# removing a row with pdp
dataFrame = pdp.ValDrop(['Jaguar'],'Car').apply(dataFrame)
print("\n DataFrame after removing a row...\n",dataFrame)
# removing a column with pdp
resDF = pdp.ColDrop("Units").apply(dataFrame)
print("\nDataFrame after removing a column...\n",resDF)
Output
This will produce the following output −
DataFrame ... Car Units 0 BMW 100 1 Lexus 150 2 Audi 110 3 Mustang 80 4 Bentley 110 5 Jaguar 90 Displaying after removing a row... Car Units 0 BMW 100 1 Lexus 150 2 Audi 110 3 Mustang 80 4 Bentley 110 Displaying after removing a column... Car 0 BMW 1 Lexus 2 Audi 3 Mustang 4 Bentley
Updated on: 29-Sep-2021
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