%(Recommended) - Why You Should Read Python Data Science Handbook: Tools and Techniques for Developers by Jake Vanderplas Online or Download [MOBI EPUB PDF]

ISBN: Developers

Category: Novel


Posted on 2019-07-17, by Jung9580.

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Top Reason Why Python Data Science Handbook: Tools and Techniques for Developers by Jake Vanderplas Become Most Wanted Book And Must Pinned To The Top Reading List Soon.


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Python Data Science Handbook: Tools and Techniques for Developers by Jake Vanderplas was published in 2016 With 1491912057 ISBN code for this book.

Jake Vanderplas was known as one of the best authors in this millenial world, many best books was written and always become popular books.
After Python Data Science Handbook: Tools and Techniques for Developers was published now this book got 4.5 / 5 rating and will always increase according to the most wanted data list in Marketplaces voters.

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Short Overview For Python Data Science Handbook: Tools and Techniques for Developers :

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 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 must-have reference for scientific computing in Python.

With this handbook, you’ll learn how to use:
* 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
* Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms


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