How do you design a function to perform specific transformations on a pandas dataframe?

Question

Anonymous · Accepted Answer

import pandas as pd

def manipulate_dataframe(df, sales_threshold=1000):
    """
    Manipulate a pandas DataFrame:
    - Filters rows with sales greater than sales_threshold
    - Adds a new column 'tax' as 10% of 'sales'
    - Renames the 'sales' column to 'total_sales'
    - Sorts the DataFrame by 'total_sales' in descending order
    
    Parameters:
    df (pd.DataFrame): Input DataFrame with at least a 'sales' column
    sales_threshold (float): Minimum sales value to filter rows
    
    Returns:
    pd.DataFrame: Modified DataFrame
    """
    # Filter rows
    filtered_df = df[df['sales'] > sales_threshold].copy()
    
    # Add 'tax' column
    filtered_df['tax'] = filtered_df['sales'] * 0.10
    
    # Rename 'sales' column
    filtered_df.rename(columns={'sales': 'total_sales'}, inplace=True)
    
    # Sort by 'total_sales'
    sorted_df = filtered_df.sort_values(by='total_sales', ascending=False)
    
    return sorted_df

How do you design a function to perform specific transformations on a pandas dataframe?

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