R Data Visualization Recipes

Translate your data into info-graphics using popular packages in R
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R Data Visualization Recipes

Vitor Bianchi Lanzetta

Translate your data into info-graphics using popular packages in R

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Book Details

ISBN 139781788398312
Paperback334 pages

Book Description

R is an open source language for data analysis and graphics that allows users to load various packages for effective and better data interpretation. Its popularity has soared in recent years because of its powerful capabilities when it comes to turning different kinds of data into intuitive visualization solutions.

This book is an update to our earlier R data visualization cookbook with 100 percent fresh content and covering all the cutting edge R data visualization tools. This book is packed with practical recipes, designed to provide you with all the guidance needed to get to grips with data visualization using R. It starts off with the basics of ggplot2, ggvis, and plotly visualization packages, along with an introduction to creating maps and customizing them, before progressively taking you through various ggplot2 extensions, such as ggforce, ggrepel, and gganimate. Using real-world datasets, you will analyze and visualize your data as histograms, bar graphs, and scatterplots, and customize your plots with various themes and coloring options. The book also covers advanced visualization aspects such as creating interactive dashboards using Shiny

By the end of the book, you will be equipped with key techniques to create impressive data visualizations with professional efficiency and precision.

Table of Contents

Chapter 1: Installation and Introduction
Introduction
Installing and loading graphics packages
Using ggplot2, plotly, and ggvis
Making plots using primitives
Chapter 2: Plotting Two Continuous Variables
Introduction
Plotting a basic scatterplot
Hacking ggvis add_axis() function to operate as a title function
Plotting a scatterplot with shapes and colors
Plotting a shape reference palette for ggplot2
Dealing with over-plotting, reducing points
Dealing with over-plotting, jittering points
Dealing with over-plotting, alpha blending
Rug the margins using geom_rug()
Adding marginal histograms using ggExtra
Drawing marginal histogram using gridExtra
Crafting marginal plots with plotly
Adding regression lines
Adding quantile regression lines
Drawing publish-quality scatterplots
Chapter 3: Plotting a Discrete Predictor and a Continuous Response
Introduction
Installing car package and getting familiar to data
Drawing simple box plots
Adding notches and jitters to box plots
Drawing bivariate dot plots using ggplot2
Using more suitable colors for geom_dotplot
Combining box with dot plots
Using point geometry to work as dots using ggvis, plotly and ggplot2
Crafting simple violin plots
Using stat_summary to customize violin plots
Manually sorting and coloring violins 
Using joy package to replace violins
Creating publication quality violin plots
Chapter 4: Plotting One Variable
Introduction
Creating a simple histogram using geom_histogram()
Creating an histogram with custom colors and bins width
Crafting and coloring area plots using geom_area() and more
Drawing density plots using geom_density()
Drawing univariate colored dot plots with geom_dotplot()
Crafting univariate bar charts
Using rtweet and ggplot2 to plot twitter words frequencies
Drawing publish quality density plot
Chapter 5: Making Other Bivariate Plots
Introduction
Creating simple stacked bar graphs
Crafting proportional stacked bar
Plotting side-by-side bar graph
Plotting a bar graphic with aggregated data using geom_col()
Adding variability estimates to plots with geom_errrorbar()
Making line plots
Making static and interactive hexagon plots
Adjusting your hexagon plot
Developing a publish quality proportional stacked bar graph
Chapter 6: Creating Maps
Introduction
Making simple maps - 1854 London Streets
Creating an interactive cholera map using plotly
Crafting choropleth maps using ggplot2
Zooming in on the map
Creating different maps based on different map projection types
Handling shapefiles to map Afghanistan health facilities
Crafting an interactive globe using plotly
Creating high quality maps
Chapter 7: Faceting
Introduction
Creating a faceted bar graph
Crafting faceted histograms
Creating a facet box plot
Crafting a faceted line plot
Making faceted scatterplots
Creating faceted maps
Drawing facets using plotly
Plotting a high quality faceted bar graph
Chapter 8: Designing Three-Dimensional Plots
Introduction
Drawing a simple contour plot using ggplot2
Picking a custom number of contour lines
Using the directlabels package to label the contours
Crafting a simple tile plot with ggplot2
Creating simple raster plots with ggplot2
Designing a three-dimensional plot with plotly
Crafting a publication quality contour plot
Chapter 9: Using Theming Packages
Introduction
Drawing a bubble plot
Popular themes with ggthemes
Applying sci themes with ggsci
Importing new fonts with the extrafont package
Using ggtech to mimic tech companies themes
Wrapping a custom theme function
Applying awesome themes and checking misspells with hrbrthemes
Chapter 10: Designing More Specialized Plots
Introduction
Drawing wonderful facets zoom with the ggforce package
Drawing sina plots with ggforce
Using ggrepel to plot non-overlaying texts
Visualizing relational data structures with ggraph
Draw alternative lollipop and density plots with ggalt
Chapter 11: Making Interactive Plots
Introduction
Using ggiraph to create interactive plots
Using gganimate to craft animated ggplots
Crafting animated plots with tweenr
Chapter 12: Building Shiny Dashboards
Introduction
Installing and loading a shiny package
Creating basic shiny interactive plots
Developing intermediate shiny interactive plots
Building a shiny dashboard

What You Will Learn

  • Get to know various data visualization libraries available in R to represent data
  • Generate elegant codes to craft graphics using ggplot2, ggvis and plotly
  • Add elements, text, animation, and colors to your plot to make sense of data
  • Deepen your knowledge by adding bar-charts, scatterplots, and time series plots using ggplot2
  • Build interactive dashboards using Shiny.
  • Color specific map regions based on the values of a variable in your data frame
  • Create high-quality journal-publishable scatterplots
  • Create and design various three-dimensional and multivariate plots

Authors

Table of Contents

Chapter 1: Installation and Introduction
Introduction
Installing and loading graphics packages
Using ggplot2, plotly, and ggvis
Making plots using primitives
Chapter 2: Plotting Two Continuous Variables
Introduction
Plotting a basic scatterplot
Hacking ggvis add_axis() function to operate as a title function
Plotting a scatterplot with shapes and colors
Plotting a shape reference palette for ggplot2
Dealing with over-plotting, reducing points
Dealing with over-plotting, jittering points
Dealing with over-plotting, alpha blending
Rug the margins using geom_rug()
Adding marginal histograms using ggExtra
Drawing marginal histogram using gridExtra
Crafting marginal plots with plotly
Adding regression lines
Adding quantile regression lines
Drawing publish-quality scatterplots
Chapter 3: Plotting a Discrete Predictor and a Continuous Response
Introduction
Installing car package and getting familiar to data
Drawing simple box plots
Adding notches and jitters to box plots
Drawing bivariate dot plots using ggplot2
Using more suitable colors for geom_dotplot
Combining box with dot plots
Using point geometry to work as dots using ggvis, plotly and ggplot2
Crafting simple violin plots
Using stat_summary to customize violin plots
Manually sorting and coloring violins 
Using joy package to replace violins
Creating publication quality violin plots
Chapter 4: Plotting One Variable
Introduction
Creating a simple histogram using geom_histogram()
Creating an histogram with custom colors and bins width
Crafting and coloring area plots using geom_area() and more
Drawing density plots using geom_density()
Drawing univariate colored dot plots with geom_dotplot()
Crafting univariate bar charts
Using rtweet and ggplot2 to plot twitter words frequencies
Drawing publish quality density plot
Chapter 5: Making Other Bivariate Plots
Introduction
Creating simple stacked bar graphs
Crafting proportional stacked bar
Plotting side-by-side bar graph
Plotting a bar graphic with aggregated data using geom_col()
Adding variability estimates to plots with geom_errrorbar()
Making line plots
Making static and interactive hexagon plots
Adjusting your hexagon plot
Developing a publish quality proportional stacked bar graph
Chapter 6: Creating Maps
Introduction
Making simple maps - 1854 London Streets
Creating an interactive cholera map using plotly
Crafting choropleth maps using ggplot2
Zooming in on the map
Creating different maps based on different map projection types
Handling shapefiles to map Afghanistan health facilities
Crafting an interactive globe using plotly
Creating high quality maps
Chapter 7: Faceting
Introduction
Creating a faceted bar graph
Crafting faceted histograms
Creating a facet box plot
Crafting a faceted line plot
Making faceted scatterplots
Creating faceted maps
Drawing facets using plotly
Plotting a high quality faceted bar graph
Chapter 8: Designing Three-Dimensional Plots
Introduction
Drawing a simple contour plot using ggplot2
Picking a custom number of contour lines
Using the directlabels package to label the contours
Crafting a simple tile plot with ggplot2
Creating simple raster plots with ggplot2
Designing a three-dimensional plot with plotly
Crafting a publication quality contour plot
Chapter 9: Using Theming Packages
Introduction
Drawing a bubble plot
Popular themes with ggthemes
Applying sci themes with ggsci
Importing new fonts with the extrafont package
Using ggtech to mimic tech companies themes
Wrapping a custom theme function
Applying awesome themes and checking misspells with hrbrthemes
Chapter 10: Designing More Specialized Plots
Introduction
Drawing wonderful facets zoom with the ggforce package
Drawing sina plots with ggforce
Using ggrepel to plot non-overlaying texts
Visualizing relational data structures with ggraph
Draw alternative lollipop and density plots with ggalt
Chapter 11: Making Interactive Plots
Introduction
Using ggiraph to create interactive plots
Using gganimate to craft animated ggplots
Crafting animated plots with tweenr
Chapter 12: Building Shiny Dashboards
Introduction
Installing and loading a shiny package
Creating basic shiny interactive plots
Developing intermediate shiny interactive plots
Building a shiny dashboard

Book Details

ISBN 139781788398312
Paperback334 pages
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