CSV Basics

CSV (Comma-Separated Values) is one of the most common file formats in the world. When you download data from a bank statement, Google Sheets, or a government data portal, it often comes as a .csv file.

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What Does a CSV File Look Like?

Name,Age,City
Rahul,22,Hyderabad
Priya,20,Bangalore
Sai,23,Vizag

Each line is a row. Values within a row are separated by commas. The first row is usually the header.

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Reading CSV Files

Python has a built-in csv module (no installation needed):

import csv

with open("students.csv", "r") as file:
    reader = csv.reader(file)
    
    for row in reader:
        print(row)
# Output:
# ['Name', 'Age', 'City']
# ['Rahul', '22', 'Hyderabad']
# ['Priya', '20', 'Bangalore']
# ['Sai', '23', 'Vizag']

Each row is returned as a list of strings.

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Writing CSV Files

import csv

students = [
    ["Name", "Age", "City"],
    ["Rahul", 22, "Hyderabad"],
    ["Priya", 20, "Bangalore"],
    ["Sai", 23, "Vizag"]
]

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

print("CSV file created!")

Why newline=""?

On Windows, without newline="", Python adds extra blank lines between rows. This parameter prevents that.

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Reading CSV as Dictionaries

For easier access by column name, use DictReader:

import csv

with open("students.csv", "r") as file:
    reader = csv.DictReader(file)
    
    for row in reader:
        print(f"{row['Name']} is from {row['City']}")
# Output:
# Rahul is from Hyderabad
# Priya is from Bangalore
# Sai is from Vizag

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Quick Summary

• CSV Format: Comma-Separated Values for storing tabular datasets.
• csv.reader(file): Reads rows as lists of string values.
• csv.DictReader(file): Reads rows as dictionaries using the header line for keys.
• csv.writer(file) & writerow(): Writes list rows to disk.
• Windows Formatting: Always pass newline='' to open() when writing CSVs on Windows to avoid unwanted blank rows.

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What's Next?

Now that you can work with text and CSV files, let's learn how to process web and AI data in Module 15b: JSON!

Module 15b: JSON

Learn how to serialize, deserialize, and exchange structured JSON data in Python