Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.9 and pandas 1.2, 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. YouÃ??Ã?Â¢??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. ItÃ??Ã?Â¢??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
Table of contents
- 1.1 What Is This Book About?
- 1.2 Why Python for Data Analysis?
- 1.3 Essential Python Libraries
- 1.4 Installation and Setup
- 1.5 Community and Conferences
- 1.6 Navigating This Book
Python Language Basics, IPython, and Jupyter Notebooks
- 2.1 The Python Interpreter
- 2.2 IPython Basics
- 2.3 Python Language Basics
- 2.4 Conclusion
- Title: Python for Data Analysis, 3rd Edition
- Release date: September 2022
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781098103965
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