You have an input CSV file in a source location. Read the file, drop an existing column, and add a new derived column that increases the salary by three times. Provide a code snippet.

Using pandas makes this task straightforward. The code reads the CSV, drops the unwanted column, creates a new column by multiplying the salary by 3, and writes the result back.

import pandas as pd

source = "/path/to/source/data.csv"
output = "/path/to/target/data_processed.csv"

# Read CSV
df = pd.read_csv(source)

# Drop a column named 'old_column'
df = df.drop(columns=['old_column'])

# Add derived column 'salary_increased'
df['salary_increased'] = df['salary'] * 3

# Write back to CSV
df.to_csv(output, index=False)

Complexity is O(n) where n is the number of rows, as pandas processes the entire DataFrame in memory. If the file is large, consider using the csv module or chunked processing. This snippet assumes the salary column exists and contains numeric values.