How to Read a CSV File in Python

Reading CSV files is one of the most common data import tasks in Python. Here are the main methods to accomplish this.

Method 1: Using pandas (Recommended)

The easiest way to read a CSV file is with pandas:

import pandas as pd

# Read a CSV file
df = pd.read_csv('data.csv')

# View the first few rows
print(df.head())

Common Options

# Specify a different delimiter
df = pd.read_csv('data.csv', sep=';')

# Skip header rows
df = pd.read_csv('data.csv', skiprows=2)

# Use specific columns
df = pd.read_csv('data.csv', usecols=['name', 'age'])

# Handle missing values
df = pd.read_csv('data.csv', na_values=['NA', 'N/A', ''])

Method 2: Using the csv Module

For simpler needs, use Python’s built-in csv module:

import csv

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

Reading as Dictionaries

import csv

with open('data.csv', 'r') as file:
    reader = csv.DictReader(file)
    for row in reader:
        print(row['name'], row['age'])

Summary

• Use pandas.read_csv() for data analysis workflows
• Use the csv module for simple file processing
• Both methods handle large files efficiently