How to convert CSV to Parquet in Python using Pandas

📘 Introduction

In modern data workflows, Parquet is a popular columnar storage format for efficient data storage and faster analytics. Converting CSV to Parquet in Python is straightforward using Pandas and PyArrow. In this tutorial, we will walk you through the complete process: from creating a sample CSV file, reading it into a Pandas DataFrame, converting it to Parquet, and finally verifying the conversion.

✅ Prerequisites

Before you begin, make sure you have:

🐍☑️ Installed Python
🌐☑️ Created and activated a virtual environment (venv)

📦1️⃣ Install Libraries

Install the following Python packages using pip:

pip install pandas
pip install pyarrow

📁2️⃣ Create Sample CSV file

First, create a sample CSV file called student.csv within your project folder:

project-folder/
└── student.csv

Add the following content to the .csv file:

id,name,major
s1,Lara Fitzgerald,Data Analytics
s2,Mike Meyer,Data Engineering
s3,Eliza Gomez,Data Science
s4,Travis Robinson,Data Analytics
s5,Jackie Brown,Data Engineering
s6,Caleb Pearson,Data Science
s7,Ava Johansson,Data Science
s8,Nathan Williams,Data Engineering
s9,Cooper Harris,Data Analytics
s10,Murphy Fraser,Data Science

🐍3️⃣ Create Python script

In the same folder as the CSV file, create a Python file (.py) or Jupyter notebook (.ipynb):

project-folder/
├── convert_csv_to_parquet.ipynb
└── student.csv

📥4️⃣ Import Libraries

Open your Python file and start by importing the required Python modules:

import pandas as pd

⬆️5️⃣ Read CSV File

Read the CSV file into a Pandas DataFrame.