Python Data Science Handbook: Essential Tools for Working with Data

by Jake VanderPlas

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to

Genres: Programming, Computer Science, Nonfiction, Technical, Reference, Technology, Coding

548 pages, Paperback

First published March 25, 2016

About the author

Jake VanderPlas is a well-known data scientist, researcher, and educator. He is recognized for his contributions to the fields of machine learning, data science, and astronomy. VanderPlas is particularly famous for his work in Python programming for data analysis and scientific computing.
He is the author of several popular resources, including:
"Python Data Science Handbook": A highly regarded book that provides a comprehensive guide to data science with Python, covering topics such as data manipulation, visualization, and machine learning.
He has also contributed to open-source projects related to data science and scientific computing, particularly within the Python ecosystem.
In addition to his work in data science, Jake VanderPlas is also an academic with a background in astronomy. He has worked at the University of Washington and has been involved in research related to both machine learning applications and astrophysics.

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[Magdalena]

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