Python for Data Analysis 3e

Get the comprehensive guide to manipulating, processing, cleaning, and analyzing datasets 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 about the latest versions of pandas, NumPy, and Jupyter.

Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to the tools of data science in Python. It is ideal for analysts who are new to Python and for Python programmers who are new to data science and scientific computing. Data files and related materials are available on GitHub.

• Use Jupyter Notebook and the IPython shell for exploratory computing
• Learn basic and advanced functions in NumPy
• Familiarize yourself with the data analysis tools in the pandas library
• Utilize flexible tools for loading, cleaning, transforming, merging, and reshaping data
• Create informative visualizations with matplotlib
• Apply the pandas groupby function to segment, analyze, and summarize datasets
• Analyze and manipulate regular and irregular time series data
• Learn how to solve real data analysis problems with thorough, detailed examples.