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Python data science handbook : essential tools for working with data

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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Detail Information

Series Title

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Call Number

006.312 Van p

Publisher

Beijing : O'reilly., 2017

Collation

529 p. ; 24 cm.

Language

ISBN/ISSN

9781491912058

Classification

006.312

Content Type

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Media Type

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Carrier Type

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Edition

First Edition

Subject(s)

DATA MINING
Python (Computer program language)
Database management
Data structures (Computer science)

Specific Detail Info

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Statement of Responsibility

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