Python for Data Analysis

by Wes Mckinney
Python for Data Analysis cover
Good Books rating 4.25
Technology and Innovation
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Technical
  • ID: 8544
  • Added: 2025-12-22
  • Updated: 2025-12-22
  • ISBN: 9781098104009
  • Publisher: "O'Reilly Media, Inc."
  • Published: 2022-08-12
  • Reviews: 3

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. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. /n/n 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.

Reviews
Reddit - learnpython · 2023-07-27
helpful 4.00

The book is praised for its clear and concise presentation of information, with many examples that make it enjoyable to work through. It is considered a helpful resource for learning data analysis with Python.

The reviewer found the book to be incredibly useful, highlighting its clear and concise presentation of information. The numerous examples provided make it an enjoyable and practical resource for learning data analysis with Python. They particularly appreciated the way the book helps readers understand the nuts and bolts of manipulating and processing data, making it a valuable tool for both beginners and experienced users.

Quick quotes

    The book contains many examples and the information is presented concise and clearly.

    It helps to understand the nuts and bolts of manipulating, processing

    I enjoyed working through it quite a bit.

Medium - KnowAditya · KnowAditya · 2022-09-20
informative 4.50

The book is described as incredibly useful and informative, providing a solid introduction to using Python for data analysis. It is highly recommended for those looking to enhance their skills in this area.

The reviewer found the book to be incredibly useful and informative, providing a solid introduction to using Python for data analysis. They appreciate the book's comprehensive coverage of essential tools and techniques, making it a valuable resource for both beginners and experienced users. The reviewer highlights the book's practical approach, which helps readers understand how to apply Python for real-world data analysis tasks. Overall, it is highly recommended for anyone looking to enhance their skills in this area.

Quick quotes

    Overall, I found “Python for Data Analysis” to be an incredibly useful and informative book.

    It provides a solid introduction to using Python for data analysis.

    It is highly recommended for those looking to enhance their skills in this area.

Darribas.org - Personal Blog · Darribas · 2013-09-02
practical 4.25

The book is clear, easy to read, and full of useful examples, making it a valuable resource regardless of how it is read. It is praised for its practical and accessible approach to data analysis with Python.

The reviewer found the book to be clear, easy to read, and full of useful examples, making it a valuable resource for anyone interested in data analysis with Python. They appreciate the book's practical approach, which helps readers understand how to apply Python for real-world data analysis tasks. The reviewer highlights the book's accessibility, noting that it can be useful whether read from cover to cover or used as a reference. Overall, it is praised for its comprehensive and practical approach to data analysis.

Quick quotes

    It is clear, easy to read, full of (cool) examples and incredibly useful

    regardless of whether you read it from first to last page or have it as a reference

    The book is praised for its practical and accessible approach to data analysis with Python.

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