Effortlessly Manipulate CSV and Excel Files with Python: A Practical Tutorial

Simplify Your Workflow Using Built-in Libraries

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Working with delimited text files, particularly comma-separated values (CSV), is commonplace in many industries. Fortunately, Python offers robust tools for reading, writing, and manipulating both CSV and Microsoft Excel files effortlessly. Let’s dive into csv and openpyxl libraries, exploring how to utilize them effectively via practical code samples.

Reading and Writing CSV Files

The csv module provides extensive functionality for managing CSV files. To read from one, open it using a csv.reader instance wrapped around a file handler:

import csv

with open('sample.csv', mode='r') as file:
    reader = csv.reader(file)
    
    # Skip header row
    next(reader)

    for row in reader:
        print(row)

# Output: ['Alice', 'Sales', 'NY', '1000']
#         ['Bob', 'Marketing', 'LA', '2000']
#         ['Charlie', 'IT', 'SF', '3000']

Writing to a new CSV file requires creating a csv.writer instance tied to a writable file handler:

headers = ['Name', 'Department', 'City', 'Salary']
rows = [['David', 'HR', 'CHI', '1500'], ['Eva', 'Finance', 'ATL', '2500']]

with open('new_sample.csv'…