Get the comprehensive guide to handling, processing, cleaning, and slicing data sets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this practical guide is filled with real-world case studies that show you how to effectively solve a wide range of data analysis problems.

You will learn the latest versions of pandas, NumPy, and Jupyter in practice. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It is ideal for analysts who are new to Python and for Python developers who are new to data science and scientific computing.

Data files and related materials are available on GitHub. • Use the Jupyter notebook and IPython shell for exploratory computing • Learn basic and advanced features in NumPy • Get started with data analysis tools in the pandas library • Use flexible tools for loading, cleaning, transforming, merging, and reshaping data • Create visualized information with matplotlib • Apply the pandas groupBy feature to slice, group, and summarize data sets • Analyze and handle regular and irregular time series data • Learn how to solve real-world data analysis problems with thorough, detailed examples.

“With this new edition, Wes has updated his book to ensure that it remains the go-to resource for everything related to data analysis with Python and pandas. This book comes highly recommended.” -Paul Barry, Lecturer and author of O’Reilly’s Head First Python.

Wes McKinney, co-founder and CTO of Voltron Data, is an active member of the Python data community and an advocate for using Python in data analysis, finance, and statistical computing applications. A graduate of MIT, he is also a member of the project management committees for the Apache Arrow and Apache Parquet projects of the Apache Software Foundation.