Pythonįor Data Analysis, the cover image, and related trade dress are trademarks The O’Reilly logo is a registered trademark of O’Reilly Media, Inc. Online editions are also available for most titlesĬorporate/institutional sales department: 80 Angela Rufino O’Reilly books may be purchased for educational, business, or sales Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, With Early Release ebooks, you get books in their earliest form-theĪuthor’s raw and unedited content as they write-so you can takeĪdvantage of these technologies long before the official release of theseĬopyright © 2021 Wesley McKinney. 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 group by 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.ĭata Wrangling with Pandas, NumPy, and Jupyter Data files and related material are available on GitHub. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process. Updated for Python 3.9 and pandas 1.2, 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. Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. First six chapters (out of thirteen) and appendices only.
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