Book Image

Python for Data Science For Dummies - Second Edition

By : John Paul Mueller, Luca Massaron
Book Image

Python for Data Science For Dummies - Second Edition

By: John Paul Mueller, Luca Massaron

Overview of this book

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. The book begins by discussing how Python can make data science easy. You’ll learn how to work with the Anaconda tool suite that makes coding in Python easy. You’ll also learn to write code using Google Colab. As you progress, you'll discover how to perform interesting calculations and data manipulations using various Python libraries, such as pandas and NumPy. You’ll learn how to create data visualizations with MatPlotLib. While learning the advanced concepts, you’ll learn how to wrangle data by using techniques, such as hierarchical clustering. Finally, you’ll learn how to work with decision trees and use machine learning to make predictions. By the end of the book, you’ll have the skills and the knowledge that’s needed to write code in Python and extract information from data.
Table of Contents (13 chapters)
Free Chapter
1
Cover
9
Index
10
About the Authors
11
Advertisement Page
12
Connect with Dummies
13
End User License Agreement

Where to Go from Here

It’s time to start your Python for data science adventure! If you’re completely new to Python and its use for data science tasks, you should start with Chapter 1 and progress through the book at a pace that allows you to absorb as much of the material as possible.

If you’re a novice who’s in an absolute rush to get going with Python for data science as quickly as possible, you can skip to Chapter 3 with the understanding that you may find some topics a bit confusing later. Skipping to Chapter 5 is okay if you already have Anaconda (the programming product used in the book) installed, but be sure to at least skim Chapter 3 so that you know what assumptions we made when writing this book. If you plan to use your tablet to work with this book, be certain to review Chapter 4 so that you understand the limitations presented by Google Colab in running the example code; not all of the examples work in this IDE. Make sure to install Anaconda with...