Python for Data Analysis: Data Wrangling with Pandas, NumPy & Jupyter

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