How to Combine Multiple CSV Files Using Python for Your Analysis

Prelude to a Data Symphony

In the world of data analysis, we often encounter situations where we need to combine multiple CSV files to perform more comprehensive analysis. This can be a daunting task, especially when dealing with large datasets. Fear not, Python comes to the rescue with its powerful libraries and elegant syntax. In this tutorial, we will explore different methods to combine multiple CSV files using Python for your next analysis project.

Method 1: Using Pandas

Pandas is an indispensable library for data manipulation and analysis in Python. Its flexible DataFrame structure can easily read and merge multiple CSV files into a single DataFrame. Here’s how you can accomplish this task using Pandas:

import pandas as pd
# List all CSV files to be combined
csv_files = ['file1.csv', 'file2.csv', 'file3.csv']
# Read and concatenate the CSV files into a single DataFrame
combined_df = pd.concat([pd.read_csv(file) for file in csv_files], ignore_index=True)
# Save the combined DataFrame to a new CSV file
combined_df.to_csv('combined.csv', index=False)

Method 2: Using Glob and CSV Modules