OREILLY PYTHON FOR DATA ANALYSIS

Get the ultimate guide to data manipulation and analysis in Python with the third edition of Python for Data Analysis. Updated for Python 3.10 and pandas 1.4, this hands-on resource, written by Wes McKinney—the creator of the pandas project—provides practical case studies that address a wide range of data analysis challenges.

This book serves as a modern introduction to essential data science tools for both analysts new to Python and Python developers venturing into data science and scientific computing. Readers will gain access to data files and supplementary materials on GitHub.

Inside, you’ll learn how to:

• Use Jupyter notebooks and IPython for exploratory computing.
• Master both basic and advanced features of NumPy.
• Utilize the pandas library for effective data analysis.
• Load, clean, transform, merge, and reshape datasets with flexible tools.
• Create informative visualizations using matplotlib.
• Apply the pandas groupby functionality to summarize and analyze data.
• Work with regular and irregular time series data.
• Solve real-world data analysis problems through detailed examples.

This comprehensive guide equips you with the skills to effectively process and analyze datasets in Python.