CSV Handling

Introduction

CSV (Comma-Separated Values) is one of the simplest and most widely used formats for storing tabular data. Spreadsheets, databases, and data science tools can all export and import CSV files, which makes it an extremely common format to work with in real Python programs.

Python's built-in csv module handles the tricky edge cases of CSV parsing for you — like commas inside quoted values — so you rarely need to split lines manually.

What is a CSV File?

A CSV file stores data as plain text, with each line representing one row and commas separating each column value. The first row is often (but not always) a header row naming each column.

name,age,grade
Alex,16,A
Maya,15,B
Riya,16,A

The csv Module

Python's built-in csv module provides reader and writer objects that handle the details of parsing and formatting CSV rows correctly, including values that contain commas or quotes.

Reading CSV Files

csv.reader() wraps an open file and lets you loop over it row by row. Each row comes back as a plain list of strings.

import csv

with open("students.csv", "r") as file:
    reader = csv.reader(file)
    for row in reader:
        print(row)

['name', 'age', 'grade']
['Alex', '16', 'A']
['Maya', '15', 'B']
['Riya', '16', 'A']

Notice the first row is the header. If you want to skip it, you can call next(reader) once before your loop, or use DictReader as shown further below.

Writing CSV Files

csv.writer() lets you write rows to a file one at a time with writerow(), or all at once with writerows().

import csv

rows = [
    ["name", "age", "grade"],
    ["Alex", 16, "A"],
    ["Maya", 15, "B"],
]

with open("output.csv", "w", newline="") as file:
    writer = csv.writer(file)
    writer.writerows(rows)

print("CSV written successfully")

CSV written successfully

The resulting output.csv file contains three lines of comma-separated values, matching the students.csv format shown earlier.

Why newline='' Matters

On Windows, text files normally translate every \n into \r\n automatically when writing. The csv module already adds its own line endings, so without newline='', you can end up with blank lines between every row.

# Incorrect - may produce extra blank lines on Windows
with open("output.csv", "w") as file:
    writer = csv.writer(file)

# Correct
with open("output.csv", "w", newline="") as file:
    writer = csv.writer(file)

DictReader & DictWriter

Working with plain lists means remembering which index corresponds to which column. DictReader and DictWriter solve this by using the header row as dictionary keys, so you can access columns by name instead of position.

import csv

with open("students.csv", "r") as file:
    reader = csv.DictReader(file)
    for row in reader:
        print(row["name"], "-", row["grade"])

Alex - A
Maya - B
Riya - A

import csv

students = [
    {"name": "Alex", "age": 16, "grade": "A"},
    {"name": "Maya", "age": 15, "grade": "B"},
]

with open("output.csv", "w", newline="") as file:
    fieldnames = ["name", "age", "grade"]
    writer = csv.DictWriter(file, fieldnames=fieldnames)
    writer.writeheader()
    writer.writerows(students)

print("Done")

Done

Practical Example: Summing a Column

A very common real-world task is reading a CSV file and calculating something from one of its columns — like a total, average, or count. DictReader makes this straightforward since values can be accessed by column name.

product,quantity,price
Pen,10,5
Notebook,4,40
Eraser,20,2

import csv

total_revenue = 0

with open("sales.csv", "r") as file:
    reader = csv.DictReader(file)
    for row in reader:
        quantity = int(row["quantity"])
        price = int(row["price"])
        total_revenue += quantity * price

print("Total Revenue:", total_revenue)

Total Revenue: 290

Every value read from a CSV file is a string, even numbers like "10" or "5" — so they must be converted with int() or float() before being used in calculations.

Common Mistakes

Best Practices

Frequently Asked Questions

Key Takeaways

Summary

The csv module gives you everything needed to read and write tabular data files without manually splitting strings on commas, handling the edge cases of quoting and line endings for you.

In this lesson, you learned how to read and write CSV files with csv.reader()/csv.writer(), why newline="" matters on Windows, how DictReader/DictWriter simplify header-based access, and how to calculate a total from a CSV column.