13. Further Reading#

This section lists some of the books that have been used as a source of material and ideas for this course.

13.1. Python Data Science Handbook#

Provides a good overview of many of the most useful libraries for doing data science with python. In particular, it has comprehensive sections on numpy and pandas. It also examines a number of popular techniques in machine learning with an emphasis on using scikit-learn.

title

  • Title : Python Data Science Handbook: Tools and Techniques for Developers: Essential Tools for Working with Data

  • Author : Jake VanderPlas

  • Publisher : O’Reilly Media; 1st edition (25 Mar. 2016)

  • Language : English

  • Paperback : 300 pages

  • ISBN-10 : 1491912057

  • ISBN-13 : 978-1491912058

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13.2. Python for Data Analysis#

Good introduction to the python language. A wide range of techniques for data cleansing and preprocessing are introduced. Includes NumPy and Pandas.

title

  • Title : Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

  • Author : Wes McKinney

  • Publisher : O’Reilly Media

  • Language : English

  • ISBN-13 : 978-1491957660

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