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R Data Visualization Cookbook

By : Gohil

4.2 (6)

R Data Visualization Cookbook

4.2 (6)

By: Gohil

Overview of this book

If you are a data journalist, academician, student or freelance designer who wants to learn about data visualization, this book is for you. Basic knowledge of R programming is expected.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Sections

Conventions

Reader feedback

Customer support

Free Chapter

1. A Simple Guide to R

1. 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

2. 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

3. 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

4. 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

5. 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

6. 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

7. 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

8. 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

9. 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

10. 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

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Creating dendrograms with colors and labels

The dendrogram plot in the previous example was all black and white. While making a good presentation, we would like this to be more informative. We would also like our audience to look at the dendrogram and immediately spot clusters and relationships among variables. We will now move a bit away from basic R plots and use a package called dendroextras. A sample dendrogram is as follows:

Creating dendrograms with colors and labels

Getting ready

For creating a plot that is easy to interpret and study, we would use the dendroextras package.

For a better understanding on installing packages in R, please refer to the recipe Installing packages and getting help in R, in Chapter 1, A Simple Guide to R:

install.packages("dendroextras")
library(dendroextras)

How to do it…

The dendrogram is constructed using the USArrests data available in R. The dataset consists of four variables (Assault, Murder, Rape, and Percent of Urban Population) in each of 50 states of the USA in 1973. We would...

Visually different images

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