Python for Data Analysis

Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you’ll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.

Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.

  • Use the IPython interactive shell as your primary development environment
  • Learn basic and advanced NumPy (Numerical Python) features
  • Get started with data analysis tools in the pandas library
  • Use high-performance tools to load, clean, transform, merge, and reshape data
  • Create scatter plots and static or interactive visualizations with matplotlib
  • Apply the pandas groupby facility to slice, dice, and summarize datasets
  • Measure data by points in time, whether it’s specific instances, fixed periods, or intervals
  • Learn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples

Table of Contents
Chapter 1. Preliminaries
Chapter 2. Introductory Examples
Chapter 3. IPython: An Interactive Computing and Development Environment
Chapter 4. NumPy Basics: Arrays and Vectorized Computation
Chapter 5. Getting Started with pandas
Chapter 6. Data Loading, Storage, and File Formats
Chapter 7. Data Wrangling: Clean, Transform, Merge, Reshape
Chapter 8. Plotting and Visualization
Chapter 9. Data Aggregation and Group Operations
Chapter 10. Time Series
Chapter 11. Financial and Economic Data Applications
Chapter 12. Advanced NumPy

Book Details

  • Paperback: 470 pages
  • Publisher: O’Reilly Media (October 2012)
  • Language: English
  • ISBN-10: 1449319793
  • ISBN-13: 978-1449319793
Download [19.6 MiB]

You may also like...

No Responses

  1. koven says:

    wrong link, please upload it again, thanks.

  2. garypaffett says:

    I think there’s the wrong archive attached – it’s from the previous post …

  3. capamichele says:

    hey guy, links are other book’s! plz, fix them 😐

  4. n23 says:

    wrong links

  5. piltdownman says:

    E-book links point to a different book. Please fix this.

  6. hanswurst says:

    Linked book doesn’t match one described in the post.

  7. firewall5634 says:

    Link name is wrong. It’s point to other book. Thanks in advance 😉

  8. quang4me says:

    The download link goes to another book, please correct it! Thanks a lot

  9. gdl77 says:

    Thank you for your excelent job. The prefiles link points to another book.

  10. fracicone says:

    Wrong book!

  11. preduxor says:

    This looks like an interesting one, but the preview links are for the normal release of your previous post, which featured the early-release edition of “Oreilly.Natural.Language.Annotation.for.Machine.Learning”; rather than for the book actually described here, “Python for Data Analysis”.

    Just thought I’d mention it in case you hadn’t already noticed the mis-match between page contents and file contents…

    Thanks for the continuing supply of great reviews on new books!

  12. nikcyber says:

    The download link is for the wrong book

  13. pepitotumbas says:

    The link seems to be wrong, pointing to a previous book.

  14. Wow! says:

    Sorry for my mistake. Link was corrected.
    Thank you 🙂

  15. pepelibro says:



Leave a Reply