Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter

Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Up to date 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 solve a broad set of data analysis problems effectively. You can learn the contemporary versions of pandas, NumPy, and Jupyter in the process.

Written by Wes McKinney, the author of the Python pandas project, this book is a practical, brand new introduction to data science tools in Python. It is ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are to be had on GitHub.

• Use the Jupyter notebook and IPython shell for exploratory computing
• Learn basic and advanced features in NumPy
• Get began with data analysis tools in the pandas library
• Use flexible tools to load, clean, turn into, 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 solve real-world data analysis problems with thorough, detailed examples