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 Title Python Data Science Handbook: Essential Tools for Working with Data
 Author(s) Jake VanderPlas
 Publisher: O'Reilly Media; 1 edition (December 10, 2016); eBook (2018. Updated continuously)
 License(s): Text Content: CCBYNCND; Source Code: MIT License
 Paperback 548 pages
 eBook HTML and PDF
 Language: English
 ISBN10: 1491912057
 ISBN13: 9781491912058
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Book Description
For many researchers, Python is a firstclass 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, ScikitLearn, 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 daytoday issues: 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 musthave reference for scientific computing in Python.
 IPython and Jupyter: provide computational environments for data scientists using Python
 NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python
 Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python
 Matplotlib: includes capabilities for a flexible range of data visualizations in Python
 ScikitLearn: for efficient and clean Python implementations of the most important and established machine learning algorithms
 Use statistical inference to answer questions about realworld data
 Jake VanderPlas is a longtime user and developer of the Python scientific stack. He currently works as an interdisciplinary research director at the University of Washington, conducts his own astronomy research, and spends time advising and consulting with local scientists from a wide range of fields.
 Programming/Engineering Handbooks
 Python Programming
 Data Science
 Data Analysis and Data Mining
 Big Data
 Machine Learning
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