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Reading and Writing CSV Files in Python

Last Updated : 15 Jul, 2025

CSV (Comma Separated Values) format is one of the most widely used formats for storing and exchanging structured data between different applications, including databases and spreadsheets. CSV files store tabular data, where each data field is separated by a delimiter, typically a comma. Python provides built-in support for handling CSV files through the csv module, making it easy to read, write and manipulate CSV data efficiently.

However, we first need to import the module using:

import csv

To read a CSV file, Python provides the csv.reader class, which reads data in a structured format. The first step involves opening the CSV file using the open() function in read mode ('r'). The csv.reader() function then reads the file, returning an iterable reader object.

Example CSV File: Giants.csv

csv.reader(csvfile, dialect='excel', **fmtparams)

• csvfile: The file object containing CSV data.
• dialect: Defines a set of parameters to control CSV reading (default is 'excel').
• **fmtparams: Additional formatting parameters like delimiter, quotechar, etc.

Example:

import csv

# Opening the CSV file
with open('Giants.csv', mode='r') as file:
    # Reading the CSV file
    csvFile = csv.reader(file)
    
    # Skipping the header (uncomment if needed)
    # next(csvFile)  

    # Displaying the contents of the CSV file
    for line in csvFile:
        print(line)

Output

['Steve', 13, 'A']
['John', 14, 'F']
['Nancy', 14, 'C']
['Ravi', 13, 'B']

Explanation: The csv module reads Giants.csv using csv.reader(file), iterating row by row. The with statement ensures proper file closure. Each row is returned as a list of column values. Use next(csvFile) to skip the header.

Python provides the csv.writer class to write data to a CSV file. It converts user data into delimited strings before writing them to a file. While opening the file, using newline='' prevents unnecessary newlines when writing.

csv.writer(csvfile, dialect='excel', **fmtparams)

• csvfile: The file object where CSV data will be written.
• dialect: Defines a set of parameters to control CSV writing (default is 'excel').
• **fmtparams: Additional formatting options such as delimiter, quotechar,etc.

writerow(fields)

writerows(rows)

Example:

import csv

# Field names
f = ['Name', 'Branch', 'Year', 'CGPA']

# Data rows of CSV file
r = [
    ['Nikhil', 'COE', '2', '9.0'],
    ['Sanchit', 'COE', '2', '9.1'],
    ['Aditya', 'IT', '2', '9.3'],
    ['Sagar', 'SE', '1', '9.5'],
    ['Prateek', 'MCE', '3', '7.8'],
    ['Sahil', 'EP', '2', '9.1']
]

# Name of the CSV file
fn = "university_records.csv"

# Writing to CSV file
with open(fn, 'w', newline='') as csvfile:
    # Creating a CSV writer object
    csvwriter = csv.writer(csvfile)
    
    # Writing the field names
    csvwriter.writerow(f)
    
    # Writing the data rows
    csvwriter.writerows(r)

Output: A file named university_records.csv will be created containing the following data.

Explanation: This example shows how to write a list of dictionaries to a CSV file using csv.DictWriter. Each dictionary is a student record, with fieldnames as column headers. The file is opened in write mode ('w'), writeheader() writes headers and writerows(d) writes records.

The csv.DictWriter class allows writing a dictionary to a CSV file. It maps dictionary keys to field names.

csv.DictWriter(csvfile, fieldnames, restval='', extrasaction='raise', dialect='excel', *args, **kwds)

• csvfile: The file object where CSV data will be written.
• fieldnames: A list of column headers that correspond to dictionary keys.
• restval: Default value for missing dictionary keys.
• extrasaction: Defines how to handle extra keys ('raise' or 'ignore').
• dialect: Defines a set of parameters to control CSV writing (default is 'excel').

• writeheader(): Writes column headers using the field names.
• writerows(mydict): Writes multiple dictionary rows.

Example: A file named university_records.csv will be created containing the following data.

import csv

# Data rows as dictionary objects
d = [
    {'name': 'Nikhil', 'branch': 'COE', 'year': '2', 'cgpa': '9.0'},
    {'name': 'Sanchit', 'branch': 'COE', 'year': '2', 'cgpa': '9.1'},
    {'name': 'Aditya', 'branch': 'IT', 'year': '2', 'cgpa': '9.3'},
    {'name': 'Sagar', 'branch': 'SE', 'year': '1', 'cgpa': '9.5'},
    {'name': 'Prateek', 'branch': 'MCE', 'year': '3', 'cgpa': '7.8'},
    {'name': 'Sahil', 'branch': 'EP', 'year': '2', 'cgpa': '9.1'}
]

# Field names
f = ['Name', 'Branch', 'Year', 'CGPA']

# Name of the CSV file
fn = "university_records.csv"

# Writing to CSV file
with open(fn, 'w', newline='') as csvfile:
    # Creating a CSV DictWriter object
    writer = csv.DictWriter(csvfile, fieldnames=f)
    
    # Writing headers (field names)
    writer.writeheader()
    
    # Writing data rows
    writer.writerows(d)

Output

Explanation: This example demonstrates writing a list of student records to a CSV file using csv.DictWriter. The file is opened in write mode ('w'), fieldnames define column headers, writeheader() writes them and writerows(d) adds records. Keys must match fieldnames to ensure alignment.

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