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
