Python for Data Analysis
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 programmers new to data science and scientific computing. Data files and related material are available on GitHub.
• Use the Jupyter notebook and the 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 mataplotlib
• 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.