Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process. 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's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material 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 to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples

About the Author
Wes McKinney is an open source software developer focusing on data analysis tools. He created the Python pandas project and is a co-creator of Apache Arrow, his current development focus. He authored 2 editions of the reference book Python for Data Analysis. Wes is a Member of The Apache Software Foundation and also a PMC member for Apache Parquet. He is the director of Ursa Labs, an not-for-profit development group focused on data science tools for Python and R powered by Apache Arrow, built in partnership with RStudio. Previously, he worked for Two Sigma, Cloudera, and AQR Capital Management, and he was co-founder and CEO of the startup DataPad.


Book Information
ISBN 9781098104030
Author Wes McKinney
Format Paperback
Page Count 550
Imprint O'Reilly Media
Publisher O'Reilly Media