--- product_id: 462261723 title: "Python for Data Analysis 3e: Data Wrangling with pandas, NumPy, and Jupyter" price: "€ 109.88" currency: EUR in_stock: true reviews_count: 8 url: https://www.desertcart.be/products/462261723-python-for-data-analysis-3e-data-wrangling-with-pandas-numpy store_origin: BE region: Belgium --- # Python-powered data mastery Hands-on Jupyter notebook workflow Comprehensive pandas & NumPy coverage Python for Data Analysis 3e: Data Wrangling with pandas, NumPy, and Jupyter **Price:** € 109.88 **Availability:** ✅ In Stock ## Summary > 📈 Elevate your data game with the ultimate Python toolkit! ## Quick Answers - **What is this?** Python for Data Analysis 3e: Data Wrangling with pandas, NumPy, and Jupyter - **How much does it cost?** € 109.88 with free shipping - **Is it available?** Yes, in stock and ready to ship - **Where can I buy it?** [www.desertcart.be](https://www.desertcart.be/products/462261723-python-for-data-analysis-3e-data-wrangling-with-pandas-numpy) ## 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 That Stick:** Explore end-to-end projects on diverse datasets, from movie stats to baby names, to solidify your skills and impress peers. - • **From Beginner to Data Scientist:** No prior Python knowledge needed—start with fundamentals and quickly advance to real-world data analysis and modeling. - • **Master Data Wrangling Like a Pro:** Unlock the full potential of pandas for cleaning, transforming, and analyzing complex datasets with ease. - • **Trusted by Thousands of Data Enthusiasts:** Join a community of 496+ reviewers who rate this book 4.6/5 stars for clarity, depth, and practical value. - • **Seamless Integration with Python Ecosystem:** Leverage NumPy’s blazing-fast vectorized operations and Jupyter’s interactive notebooks for efficient, reproducible workflows. ## Overview Python for Data Analysis 3e by Wes McKinney is the definitive guide to mastering data wrangling using pandas, NumPy, and Jupyter notebooks. Perfect for professionals and aspiring data scientists, it covers everything from Python basics to advanced data manipulation and modeling, supported by practical examples and a strong community endorsement. ## Description Buy Python for Data Analysis 3e: Data Wrangling with pandas, NumPy, and Jupyter 3 by Mckinney, Wes (ISBN: 9781098104030) from desertcart's Book Store. Everyday low prices and free delivery on eligible orders. Review: Great book - Great book. Definitely would recommend. Review: Excellent - This book is very thorough and written very clearly. I bought it to assist my learning about DS/ML/AI. As Wes says in the book, the vast majority of the work in this area is data "wrangling", or getting the data into a form suitable for analysis. This book is very comprehensive and covers every aspect of the process. It starts with some introductions to Python, IPython and Jupyter. It doesn't really assume any Python knowledge, but I knew and worked with Python already and would describe it as a "whistle-stop tour". IPython is a more interactive (and dare I say, better) Python shell/interpreter which is great for exploring / testing stuff out. Jupyter is simply a web-based tool which can use IPython and has a slightly different workflow based on "cells" which can be executed. After that, there is a brief section on NumPy, and it highlights the key ideas: vectorised operations with multi-dimensional arrays. That is, to create the result of summing the elements of two arrays, a and b, you can simply write a + b. This makes for quick and convenient batch operations on data with no for loops in sight. These arrays offer a compact and highly efficient way to work with data, and they the "lingua franca" of the Python data world. The bulk of what follows is on pandas, which makes working with numpy even easier and is a heavyweight tool for loading data from a variety of formats (and storing it), cleaning it, processing it, aggregating, joining, visualising (with help from matplotlib) - everything you could want really. pandas is amazing software, and like most great software projects, it has the right abstractions (like the DataFrame), integrates seamlessly with a lot of other data libraries, and starts to feels intuitive after a while. There is also a lot of information on working with time data, and a brief chapter on building models. My favourite part was probably the end-to-end data analysis examples where Wes explores datasets from movies to baby names. Seeing the whole process there was great. The appendices are well worth reading, if not skimming, since there are more NumPy and IPython tricks. Could this book be improved in any way? Yes, I think a lot of reads a bit like a reference. Some more "real-world" examples would have been better in a lot of cases - but you do see those in the data analysis chapter. Also, the reason for using simpler examples was probably to demonstrate the point more clearly and independent of other chapters. Overall though, this gets a strong recommendation from me if you want to get more into data and machine learning. Thanks to Wes McKinney, we not only have pandas, but this book to navigate it. ## Features - New Store Stock ## Technical Specifications | Specification | Value | |---------------|-------| | Best Sellers Rank | 42,937 in Books ( See Top 100 in Books ) 9 in Data Mining (Books) 13 in Database Applications 33 in Introduction to Programming | | Customer Reviews | 4.6 out of 5 stars 496 Reviews | ## Images ![Python for Data Analysis 3e: Data Wrangling with pandas, NumPy, and Jupyter - Image 1](https://m.media-amazon.com/images/I/91QBEYSpnLL.jpg) ## Customer Reviews ### ⭐⭐⭐⭐⭐ Great book *by A***Y on 25 March 2026* Great book. Definitely would recommend. ### ⭐⭐⭐⭐⭐ Excellent *by H***. on 15 August 2023* This book is very thorough and written very clearly. I bought it to assist my learning about DS/ML/AI. As Wes says in the book, the vast majority of the work in this area is data "wrangling", or getting the data into a form suitable for analysis. This book is very comprehensive and covers every aspect of the process. It starts with some introductions to Python, IPython and Jupyter. It doesn't really assume any Python knowledge, but I knew and worked with Python already and would describe it as a "whistle-stop tour". IPython is a more interactive (and dare I say, better) Python shell/interpreter which is great for exploring / testing stuff out. Jupyter is simply a web-based tool which can use IPython and has a slightly different workflow based on "cells" which can be executed. After that, there is a brief section on NumPy, and it highlights the key ideas: vectorised operations with multi-dimensional arrays. That is, to create the result of summing the elements of two arrays, a and b, you can simply write a + b. This makes for quick and convenient batch operations on data with no for loops in sight. These arrays offer a compact and highly efficient way to work with data, and they the "lingua franca" of the Python data world. The bulk of what follows is on pandas, which makes working with numpy even easier and is a heavyweight tool for loading data from a variety of formats (and storing it), cleaning it, processing it, aggregating, joining, visualising (with help from matplotlib) - everything you could want really. pandas is amazing software, and like most great software projects, it has the right abstractions (like the DataFrame), integrates seamlessly with a lot of other data libraries, and starts to feels intuitive after a while. There is also a lot of information on working with time data, and a brief chapter on building models. My favourite part was probably the end-to-end data analysis examples where Wes explores datasets from movies to baby names. Seeing the whole process there was great. The appendices are well worth reading, if not skimming, since there are more NumPy and IPython tricks. Could this book be improved in any way? Yes, I think a lot of reads a bit like a reference. Some more "real-world" examples would have been better in a lot of cases - but you do see those in the data analysis chapter. Also, the reason for using simpler examples was probably to demonstrate the point more clearly and independent of other chapters. Overall though, this gets a strong recommendation from me if you want to get more into data and machine learning. Thanks to Wes McKinney, we not only have pandas, but this book to navigate it. ### ⭐⭐⭐⭐⭐ Improving python knowledge. *by N***O on 15 December 2025* Helpful book to start studying/ relearning python. ## Frequently Bought Together - Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter - Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python - Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems --- ## Why Shop on Desertcart? - 🛒 **Trusted by 1.3+ Million Shoppers** — Serving international shoppers since 2016 - 🌍 **Shop Globally** — Access 737+ million products across 21 categories - 💰 **No Hidden Fees** — All customs, duties, and taxes included in the price - 🔄 **15-Day Free Returns** — Hassle-free returns (30 days for PRO members) - 🔒 **Secure Payments** — Trusted payment options with buyer protection - ⭐ **TrustPilot Rated 4.5/5** — Based on 8,000+ happy customer reviews **Shop now:** [https://www.desertcart.be/products/462261723-python-for-data-analysis-3e-data-wrangling-with-pandas-numpy](https://www.desertcart.be/products/462261723-python-for-data-analysis-3e-data-wrangling-with-pandas-numpy) --- *Product available on Desertcart Belgium* *Store origin: BE* *Last updated: 2026-05-02*