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R Data Visualization Cookbook

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R Data Visualization Cookbook

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R Data Visualization Cookbook
Jan, 2015 | 236 pages
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Table of Contents (17 chapters)
R Data Visualization Cookbook
R Data Visualization Cookbook
Credits
Credits
About the Author
About the Author
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
A Simple Guide to R
A Simple Guide to R
Installing packages and getting help in R
Data types in R
Special values in R
Matrices in R
Editing a matrix in R
Data frames in R
Editing a data frame in R
Importing data in R
Exporting data in R
Writing a function in R
Writing if else statements in R
Basic loops in R
Nested loops in R
The apply, lapply, sapply, and tapply functions
Using par to beautify a plot in R
Saving plots
2
Basic and Interactive Plots
Basic and Interactive Plots
Introduction
Introducing a scatter plot
Scatter plots with texts, labels, and lines
Connecting points in a scatter plot
Generating an interactive scatter plot
A simple bar plot
An interactive bar plot
A simple line plot
Line plot to tell an effective story
Generating an interactive Gantt/timeline chart in R
Merging histograms
Making an interactive bubble plot
Constructing a waterfall plot in R
3
Heat Maps and Dendrograms
Heat Maps and Dendrograms
Introduction
Constructing a simple dendrogram
Creating dendrograms with colors and labels
Creating a heat map
Generating a heat map with customized colors
Generating an integrated dendrogram and a heat map
Creating a three-dimensional heat map and a stereo map
Constructing a tree map in R
4
Maps
Maps
Introduction
Introducing regional maps
Introducing choropleth maps
A guide to contour maps
Constructing maps with bubbles
Integrating text with maps
Introducing shapefiles
Creating cartograms
5
The Pie Chart and Its Alternatives
The Pie Chart and Its Alternatives
Introduction
Generating a simple pie chart
Constructing pie charts with labels
Creating donut plots and interactive plots
Generating a slope chart
Constructing a fan plot
6
Adding the Third Dimension
Adding the Third Dimension
Introduction
Constructing a 3D scatter plot
Generating a 3D scatter plot with text
A simple 3D pie chart
A simple 3D histogram
Generating a 3D contour plot
Integrating a 3D contour and a surface plot
Animating a 3D surface plot
7
Data in Higher Dimensions
Data in Higher Dimensions
Introduction
Constructing a sunflower plot
Creating a hexbin plot
Generating interactive calendar maps
Creating Chernoff faces in R
Constructing a coxcomb plot in R
Constructing network plots
Constructing a radial plot
Generating a very basic pyramid plot
8
Visualizing Continuous Data
Visualizing Continuous Data
Introduction
Generating a candlestick plot
Generating interactive candlestick plots
Generating a decomposed time series
Plotting a regression line
Constructing a box and whiskers plot
Generating a violin plot
Generating a quantile-quantile plot (QQ plot)
Generating a density plot
Generating a simple correlation plot
9
Visualizing Text and XKCD-style Plots
Visualizing Text and XKCD-style Plots
Introduction
Generating a word cloud
Constructing a word cloud from a document
Generating a comparison cloud
Constructing a correlation plot and a phrase tree
Generating plots with custom fonts
Generating an XKCD-style plot
10
Creating Applications in R
Creating Applications in R
Introduction
Creating animated plots in R
Creating a presentation in R
A basic introduction to API and XML
Constructing a bar plot using XML in R
Creating a very simple shiny app in R
Index
Index

About the Author

Atmajitsinh Gohil works as a senior consultant at a consultancy firm in New York City. After graduating, he worked in the financial industry as a Fixed Income Analyst. He writes about data manipulation, data exploration, visualization, and basic R plotting functions on his blog at http://datavisualizationineconomics.blogspot.com.

He has a master's degree in financial economics from the State University of New York (SUNY), Buffalo. He also graduated with a master of arts degree in economics from University of Pune, India. He loves to read blogs on data visualization and loves to go out on hikes in his free time.

This book would not have been possible without the help from numerous data visualizers and data scientists around the globe who bring into existence new and innovative ways to transform data into beautiful stories. I would like to sincerely thank the developers of R and R packages who have contributed so generously to the growing R open source community.

I would like to thank Jer Thorpe and Hans Rosling for their inspiring Ted videos on data visualization.

I would also like to thank all the economists and statisticians who have so often inspired me.

I would like to thank my publisher, Packt Publishing, for giving me the opportunity to work on this book. I would also like to thank all the technical reviewers and content development editors at Packt Publishing for their informative comments and suggestions.

Finally, I would like to thank my amazing family and magnificent friends for always encouraging and supporting me.

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