Python Data Science Handbook PDF | Learning Python PDF

Python Data Science Handbook PDF

This is a book about doing data science with Python, which immediately begs the
question: what is data science?
Python Data Science Handbook PDF Download
[PDF link given below]

Overview

This is a book about doing data science with Python, which immediately begs the
question: what is data science? It’s a surprisingly hard definition to nail down, especially given how ubiquitous the term has become. Vocal critics have variously dismissed the term as a superfluous label (after all, what science doesn’t involve data?) or
a simple buzzword that only exists to salt résumés and catch the eye of overzealous
tech recruiters.

Who Is This Book For?

In my teaching both at the University of Washington and at various tech-focused
conferences and meetups, one of the most common questions I have heard is this:
“how should I learn Python?” The people asking are generally technically minded
students, developers, or researchers, often with an already strong background in writing code and using computational and numerical tools. Most of these folks don’t want
to learn Python per se, but want to learn the language with the aim of using it as a
tool for data-intensive and computational science. While a large patchwork of videos,
blog posts, and tutorials for this audience is available online, I’ve long been frustrated
by the lack of a single good answer to this question; that is what inspired this book.

Outline of This Book

Each chapter of this book focuses on a particular package or tool that contributes a
fundamental piece of the Python data science story.

Python and Jupyter (Chapter 1) :
These packages provide the computational environment in which many Python-
using data scientists work.

NumPy (Chapter 2)
: This library provides the ndarray object for efficient storage and manipulation of
dense data arrays in Python.

Pandas (Chapter 3) :
This library provides the DataFrame object for efficient storage and manipulation
of labeled/columnar data in Python.

Matplotlib (Chapter 4) : This library provides capabilities for a flexible range of data visualizations in
Python.

Scikit-Learn (Chapter 5) :
This library provides efficient and clean Python implementations of the most
important and established machine learning algorithms.

About the Author

Jake VanderPlas is a long-time 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.

PDF INFO

Book’s Name : Python Data Science Handbook
Author : Jake VanderPlas
Copyright Owner : Copyright © 2017 Jake VanderPlas.
Original language : English
Size Of PDF : 21.03 MB
Number of Pages : 558 Pages

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