Applied Data Visualization with R and ggplot2 E-Book

Dr. Tania Moulik

• Herausgeber: Packt Publishing
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 81

Veröffentlichungsjahr: 2018

Beschreibung

Develop informative and aesthetic visualizations that enable effective data analysis in less time

Key Features

• Discover structure of ggplot2, grammar of graphics, and geometric objects
• Study how to design and implement visualization from scratch
• Explore the advantages of using advanced plots

Book Description

Applied Data Visualization with R and ggplot2 introduces you to the world of data visualization by taking you through the basic features of ggplot2. To start with, you’ll learn how to set up the R environment, followed by getting insights into the grammar of graphics and geometric objects before you explore the plotting techniques.

You’ll discover what layers, scales, coordinates, and themes are, and study how you can use them to transform your data into aesthetical graphs. Once you’ve grasped the basics, you’ll move on to studying simple plots such as histograms and advanced plots such as superimposing and density plots. You’ll also get to grips with plotting trends, correlations, and statistical summaries.

By the end of this book, you’ll have created data visualizations that will impress your clients.

What you will learn

• Set up the R environment, RStudio, and understand structure of ggplot2
• Distinguish variables and use best practices to visualize them
• Change visualization defaults to reveal more information about data
• Implement the grammar of graphics in ggplot2 such as scales and faceting
• Build complex and aesthetic visualizations with ggplot2 analysis methods
• Logically and systematically explore complex relationships
• Compare variables in a single visual, with advanced plotting methods

Who this book is for

Applied Data Visualization with R and ggplot2 is for you if you are a professional working with data and R. This book is also for students who want to enhance their data analysis skills by adding informative and professional visualizations. It is assumed that you know basics of the R language and its commands and objects.

Dr. Tania Moulik has a PhD in particle physics. She worked at CERN and the Tevatron at Fermi National Accelerator Laboratory in IL, USA. She has worked with C++, Python, and R. She also worked in big data projects and grid computing. She has a passion for data analysis and likes to share her knowledge with others who would like to delve into the world of data analytics. She especially likes R and ggplot2 as a powerful analytics package.

Leseprobe

Applied Data Visualization with R and ggplot2

Create useful, elaborate, and visually appealing plots

Dr. Tania Moulik

BIRMINGHAM - MUMBAI

Applied Data Visualization with R and ggplot2

Copyright © 2018 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Acquisitions Editor: Aditya DateContent Development Editors: Darren Patel, Tanmayee PatilProduction Coordinator: Arvindkumar Gupta

First published: September 2018

Production reference: 1270918

Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK.

ISBN 978-1-78961-215-8

www.packtpub.com

About the Author

Dr. Tania Moulik has a PhD in particle physics. She worked at CERN and the Tevatron at Fermi National Accelerator Laboratory in IL, USA. She has worked with C++, Python, and R. She also worked in big data projects and grid computing. She has a passion for data analysis and likes to share her knowledge with others who would like to delve into the world of data analytics. She especially likes R and ggplot2 as a powerful analytics package.

 

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Table of Contents

Title Page

Copyright and Credits

Applied Data Visualization with R and ggplot2

About the Author

About the Author

Packt Upsell

Why Subscribe?

PacktPub.com

Preface

Who This Book Is For

What This Book Covers

To Get the Most out of This Book

Download the Example Code Files

Conventions Used

Get in Touch

Reviews

Basic Plotting in ggplot2

Introduction to ggplot2

Similar Packages

The RStudio Workspace

Loading and Exploring a Dataset Using R Functions

The Main Concepts of ggplot2

Types of Variables

Exploring Datasets

Making Your First Plot

Plotting with qplot and R

Analysis

Geometric Objects

Analyzing Different Datasets

Histograms

Creating a Histogram Using qplot and ggplot

Activity: Creating a Histogram and Explaining its Features

Creating Bar Charts

Creating a One-Dimensional Bar Chart

Creating a Two-Dimensional Bar Chart

Analyzing and Creating Boxplots

Creating a Boxplot for a Given Dataset

Scatter Plots

Line Charts

Creating a Line Chart

Activity: Creating One- and Two-Dimensional Visualizations with a Given Dataset

One-Dimensional Plots

Two-Dimensional Plots

Three-Dimensional Plots

The Grammar of Graphics

Rebinning

Analyzing Various Histograms

Changing Boxplot Defaults Using the Grammar of Graphics

Activity: Improving the Default Visualization

Summary

Grammar of Graphics and Visual Components

More on the Grammar of Graphics

Layers

Using More Layers to Customize a Histogram

Scales

Using Scales to Analyze a Dataset

Types of Coordinates

Understanding Polar Coordinates

Activity: Applying the Grammar of Graphics to Create a Complex Visualization

Facets

Using Facets to Split Data

Activity: Using Faceting to Understand Data

Changing Styles and Colors

Using Different Colors to Group Points by a Variable

Activity: Using Color Differentiation in Plots

Themes and Changing the Appearance of Graphs

Using a Theme to Customize a Plot

Analysis

Using or Setting Your Own Theme Globally

Changing the Color Scheme of the Given Theme

Activity: Using Themes and Color Differentiation in a Plot

Geoms and Statistical Summaries

Using Grouping to Create a Summarized Plot

Summary

Advanced Geoms and Statistics

Advanced Plotting Techniques

Creating a Bubble Chart

Density Plots

Using Density Plots

Superimposing Plots

Using Density Plots to Compare Distributions

Time Series

Creating a Time Series Plot

Explanation of the Code

Activity: Plot the Monthly Closing Stock Prices and the Mean Values

Maps

Displaying Information with Maps

Activity: Creating a Variable-Encoded Regional Map

Trends, Correlations, and Statistical Summaries

Creating a Time Series Plot with the Mean, Median, and Quantiles

Trends, Correlations, and Scatter plots

Creating a Scatter Plot and Fitting a Linear Regression Model

Creating a Correlation Plot

Activity: Studying Correlated Variables

Summary

Solutions

Chapter 1:  Basic Plotting in ggplot2

Activity: Creating a Histogram and Explaining its Features

Activity: Creating One- and Two-Dimensional Visualizations with a Given Dataset

Activity: Improving the Default Visualization

Chapter 2:  Grammar of Graphics and Visual Components

Activity: Applying Grammar of Graphics to Create a Complex Visualization

Activity: Using Faceting to Understand Data

Activity: Using Color Differentiation in Plots

Activity: Using Themes and Color Differentiation in a Plot

Chapter 3:  Advanced Geoms and Statistics

Activity: Using Density Plots to Compare Distributions

Activity: Plot the Monthly Closing Stock Prices and the Mean Values

Activity: Creating a Variable-Encoded Regional Map

Activity: Studying Correlated Variables

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Preface

This book introduces you to the world of data visualization by talking about the basic features of ggplot2. Learn all about setting up the R environment and then begin exploring features of ggplot2. Grammar of graphics and geometric objects are the fundamentals you must know before you dive deep into the plotting techniques. Read and discover what are layers, scales, coordinates, and themes, and explore how you can use them to transform your data into aesthetical graphs. Learn the simple plots, such as histograms, and then some advanced plots, such as superimposing plots and density plots. Learn to plot trends, correlations, and statistical summaries. After reading this book, your data visualizations will wow clients.

After completing this book, you will be able to:

Set up the R environment, RStudio, and explain structure of ggplot2

Distinguish types of variables and use best practices to visualize them

Change visualization defaults to reveal more information about data

Implement the grammar of graphics in ggplot2 such as scales and faceting

Build complex, aesthetic visualizations with ggplot2 analysis methods

Logically and systematically explore complex relationships

Compare variables in a single visual, with advanced plotting methods

Who This Book Is For

This book is meant for professionals, who work with data and R, and for students, who want to enhance their data analysis skills by adding informative and professional visualizations. We assume that readers know basics of the R language, its commands, and objects.

What This Book Covers

Chapter 1, Basic Plotting in ggplot2, will help you to understand Kubernetes patterns which would be presented with the examples from Kubernetes itself and external applications.

Chapter 2, Grammar of Graphics and Visual Components, will help you to cover accessing Kubernetes API with raw HTTP queries to complex libraries with both in-cluster and out-cluster examples.

Chapter 3, Advanced Geoms And Statistics, will present extension capabilities of Kubernetes with custom resource definitions, custom controllers, dynamic admission controllers, and custom schedulers.

To Get the Most out of This Book

For an optimal experience, we recommend the following hardware configuration:

Processor: Intel Core i5 or equivalent

Memory: 4GB RAM

Storage: 35 GB available space

You'll also need the following software installed in advance:

OS: Windows 7 SP1 64-bit, Windows 8.1 64-bit, or Windows 10 64-bit

Browser: Google Chrome, Latest Version

Installing R

: 

To install the R package and libraries, go to 

http://cran.us.r-project.org/

 in your browser.

Click on

Download R for Windows

, click on base, then click on 

Download R 3.5.0 for Windows

(or any newer version that appears). 

Install R. Leave all default settings as they are in the 

installation options.

Installing RStudio

:

To install RStudio, go to 

http://rstudio.org/download/desktop

.

Choose the default installation.

Open RStudio after installation. It uses the underlying R package and 

will open it automatically in the IDE.