---
product_id: 255203344
title: "O'Reilly Python for Data Analysis, 2e"
price: "€ 150.01"
currency: EUR
in_stock: false
reviews_count: 3
url: https://www.desertcart.nl/products/255203344-oreilly-python-for-data-analysis-2e
store_origin: NL
region: Netherlands
---

# Optimized for real-world data prep Comprehensive Python mastery Expert data analysis with pandas O'Reilly Python for Data Analysis, 2e

**Price:** € 150.01
**Availability:** ❌ Out of Stock

## Summary

> 🐍 Elevate your data game with the ultimate Python analysis bible!

## Quick Answers

- **What is this?** O'Reilly Python for Data Analysis, 2e
- **How much does it cost?** € 150.01 with free shipping
- **Is it available?** Currently out of stock
- **Where can I buy it?** [www.desertcart.nl](https://www.desertcart.nl/products/255203344-oreilly-python-for-data-analysis-2e)

## Best For

- Customers looking for quality international products

## Why This Product

- Free international shipping included
- Worldwide delivery with tracking
- 15-day hassle-free returns

## Key Features

- • **Real-World Examples Included:** Learn through practical, straightforward examples that mirror professional data challenges.
- • **Master Python for Data Analysis:** Unlock the full power of Python with clear, concise guidance from the creator of pandas.
- • **Prepares You for Machine Learning:** Seamlessly transition your data workflows to scikit-learn and TensorFlow with expert tips.
- • **Pandas Expertise at Your Fingertips:** Dive deep into the industry-standard library for data manipulation and transformation.
- • **Trusted by Thousands of Professionals:** Join a community of 1,500+ reviewers who rate it 4.6 stars for its clarity and depth.

## Overview

O'Reilly's Python for Data Analysis, 2nd Edition by Wes McKinney is the definitive guide to mastering Python's data tools, especially pandas. Authored by the creator of pandas, this book offers clear, practical examples to help professionals efficiently manipulate, analyze, and prepare data for advanced machine learning workflows. Highly rated and widely trusted, it’s a must-have resource for data analysts and aspiring data scientists.

## Description

O'Reilly Python for Data Analysis, 2e : McKinney, Wes: desertcart.ae: Books

Review: Best pandas reference book - This is the best reference I use for dealing with python, numpy and mainly pandas. Must have for anyone learning or using pandas. The author (who actually wrote pandas)style is into the point, clear and with simple examples that demonstrate the usage in real world. Also this book has all the info to help you prepare data for sci-kit learn and tf .
Review: Must have - Great book, covers all the basics for data analysis in python

## Features

- Python for Data Analysis
- Wes McKinney
- 978-1491957660
- 1491957662
- Data Analysis

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #308,566 in Books ( See Top 100 in Books ) #526 in Web Programming #650 in Databases & Big Data #878 in Computer Programming Languages |
| Customer Reviews | 4.6 out of 5 stars 1,564 Reviews |

## Images

![O'Reilly Python for Data Analysis, 2e - Image 1](https://m.media-amazon.com/images/I/912I2EtdCbL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Best pandas reference book
*by T***R on 18 December 2019*

This is the best reference I use for dealing with python, numpy and mainly pandas. Must have for anyone learning or using pandas. The author (who actually wrote pandas)style is into the point, clear and with simple examples that demonstrate the usage in real world. Also this book has all the info to help you prepare data for sci-kit learn and tf .

### ⭐⭐⭐⭐⭐ Must have
*by K***A on 31 August 2021*

Great book, covers all the basics for data analysis in python

### ⭐ Print quality, black&white , bad charts
*by M***D on 21 May 2022*

Original book is printed in colors this one came black and white less color interaction in jupter notebook code. Also all charts are in black and white!

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*Product available on Desertcart Netherlands*
*Store origin: NL*
*Last updated: 2026-03-03*