Python Data Science Handbook

Author: Jacob T. Vanderplas
Editor: O'Reilly Media
ISBN: 9781491912058
File Size: 73,51 MB
Format: PDF, Mobi
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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
Applied Data Science with Python and Jupyter
Language: en
Pages: 192
Authors: Alex Galea
Categories: Computers
Type: BOOK - Published: 2018-10-31 - Publisher: Packt Publishing Ltd

Become the master player of data exploration by creating reproducible data processing pipelines, visualizations, and prediction models for your applications. Key Features Get up and running with the Jupyter ecosystem and some example datasets Learn about key machine learning concepts such as SVM, KNN classifiers, and Random Forests Discover how
Data Science with Python and Dask
Language: en
Pages: 296
Authors: Jesse Daniel
Categories: Computers
Type: BOOK - Published: 2019-07-08 - Publisher: Simon and Schuster

Summary Dask is a native parallel analytics tool designed to integrate seamlessly with the libraries you're already using, including Pandas, NumPy, and Scikit-Learn. With Dask you can crunch and work with huge datasets, using the tools you already have. And Data Science with Python and Dask is your guide to
Beginning Data Science with Python and Jupyter
Language: en
Pages: 194
Authors: Alex Galea
Categories: Computers
Type: BOOK - Published: 2018-06-05 - Publisher: Packt Publishing Ltd

Getting started with data science doesn't have to be an uphill battle. This step-by-step guide is ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction. Key Features Get up and running with the Jupyter ecosystem and some example datasets Learn about key machine
Python for Data Science For Dummies
Language: en
Pages: 496
Authors: John Paul Mueller, Luca Massaron
Categories: Computers
Type: BOOK - Published: 2019-02-27 - Publisher: John Wiley & Sons

The fast and easy way to learn Python programming and statistics Python is a general-purpose programming language created in the late 1980s—and named after Monty Python—that's used by thousands of people to do things from testing microchips at Intel, to powering Instagram, to building video games with the PyGame library.
Data Science from Scratch
Language: en
Pages: 406
Authors: Joel Grus
Categories: Computers
Type: BOOK - Published: 2019-04-12 - Publisher: "O'Reilly Media, Inc."

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. With this updated second edition, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing