👨‍🏫 {ggplot2} Teaching Material 

Selected Presentations on {ggplot2}

• “ggplot Wizardry: My favorite tricks and secrets for beautiful plots in R” — Outlier Conference 2021 hosted by the Data Visualization Society (Talk + Seminar)
  Slides | Recording | Hands-On Tutorial
• “ggplot Wizardry: My favorite tricks and secrets for beautiful plots in R (Extended Version)” — useR Oslo 03|2021
  Slides | Recording
• “Beyond bar and box plots: chart alternatives and how to design them with ggplot2” — USGS Community for Data Integration 09|2021
  Slides | Recording | Hands-On Tutorial
• “My favorite ggplot2 extension packages” — R Ladies Tunis 07|2021
  Slides | Recording
• “#30DayMapChallenge: The good, the bad and the ugly of crafting maps with ggplot2” — R Ladies Bangalore 12|2021
  Slides | Recording

Selected Blog Posts about {ggplot2}

• “A {ggplot2} Tutorial for Beautiful Plotting in R” — Extensive "How to"-tutorial based on a version from 2016 by Zev Ross
• “The Evolution of a ggplot (Part 1)” — Blog post on how to turn a default ggplot into a plot that visualizes information in an appealing and easily understandable way
• “Visualizing Distributions with Raincloud Plots (and How to Create Them with ggplot2)” — Tutorial illustrating why raincloud plots are great and numerous ways how to create such hybrid charts with {ggplot2}
• “A Quick How-to on Labelling Bar Graphs in ggplot2” — Blog poston how one can add percentage labels inside bar plots and how to highlight specific bars with {ggplot2}

Helpful Resources

• Open-Access Books:

  • “ggplot2: Elegant Graphics for Data Analysis” by Hadley Wickham, Danielle Navarro, and Thomas Lin Pedersen.
  • “R for Data Science” by Hadley Wickham and Garrett Grolemund
  • “Data Visualization: A Practical Introduction” by Kieran Healy
  • “R Graphics Cookbook” by Winston Chang
  • “Analyzing US Census Data: Methods, Maps, and Models in R” by Kyle Walker

• Galleries:

  • ggplot2 Extension Gallery
  • R Graph Gallery
  • Color Palettes in R (unofrtunately quite outdated by now)
  • #TidyTuesday Community: #TidyTuesday on Twitter
  • #TidyTuesday Collection: tidytuesday.rocks

• Workshops/Tutorials:

  • “SDS 375: Data Visualization in R” by Claus Wilke — Lectures for the Spring 2021 semester
  • “Data Visualization in R” by Brooke Anderson — Workshop for the 2019 Navy and Marine Corps Public Health Conference
  • “BBC Visual and Data Journalism cookbook for R graphics”
  • “Data Visualization with R” by Rob Kabacoff
  • “Themes to Improve Your ggplot Figures” by R for the Rest of Us

• Get Help:

  • Official ggplot2 reference
  • Official ggplot2 cheatsheet
  • RStudio Community
  • R4DS Learning Community
  • aesthetics finder

• Useful Packages (alphabetically):

  • {cowplot} — plot arrangements, themes & annotations
  • {ggalt} — alternative coords, geoms, stats & scales
  • {gganimate} — create animations
  • {ggbump} — geoms for bump charts
  • {ggforce} — several interesting add-on features
  • {ggiraph} — geoms for dynamic, interactive visualizations
  • {ggmaps} — access to Google & Stamen maps
  • {ggplotly} — create interactive plots
  • {ggraph} — networks, graphs & trees
  • {ggrepel} — prevent overlapping text labels
  • {ggridges} — geoms for ridgeline plots
  • {ggsankey} — geoms for sankey diagrams
  • {ggstream} — geoms for stream graphs
  • {ggtext} — rich-text rendering
  • {ggthemes} — additional themes, scales & geoms
  • {hrbrthemes} — typography-centric, minimal themes
  • {lemon} — axis & legend add-ons
  • {patchwork} — combine ggplots to multi-panel graphics
  • {rayshader} — hillshaded maps in 2D & 3D
  • {systemfonts} — use custom fonts (replaces {extrafont} and {showtext})

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