Collection of personal material and additional resources for the R package {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 - “An Introduction to {ggplot2}” — Stats Group of the Leibniz Institute for Zoo and Wildlife Research 08|2019
Slides
- “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}
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Open-Access Books:
- “ggplot2: Elegant Graphics for Data Analysis” by Hadley Wickham → ggplot2-book.org
- “R for Data Science” by Hadley Wickham → r4ds.had.co.nz
- “Data Visualization: A Practical Introduction” by Kieran Healy → socviz.co
- “R Graphics Cookbook” by Winston Chang → r-graphics.org
- “Analyzing US Census Data: Methods, Maps, and Models in R” by Kyle Walker → walker-data.com/census-r
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Galleries:
- ggplot2 Extension Gallery → exts.ggplot2.tidyverse.org/gallery
- R Graph Gallery → r-graph-gallery.com
- Color Palettes in R → github.com/EmilHvitfeldt/r-color-palettes
- #TidyTuesday Collection → tidytuesday.rocks
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Workshops/Tutorials:
- “SDS 375: Data Visualization in R” by Claus Wilke — Lectures for the Spring 2021 semster → wilkelab.org/SDS375
- “Data Visualization in R” by Brooke Anderson — Workshop for the 2019 Navy and Marine Corps Public Health Conference → geanders.github.io/navy_public_health
- “BBC Visual and Data Journalism cookbook for R graphics” → bbc.github.io/rcookbook
- “Data Visualization with R” by Rob Kabacoff → rkabacoff.github.io/datavis
- “Themes to Improve Your ggplot Figures” → rfortherestofus.com
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Get Help:
- RStudio Community → community.rstudio.com
- R4DS Learning Community → rfordatasci.com
- #TidyTuesday Community → #TidyTuesday on Twitter
- ggplot2 Cheatsheet → github.com/rstudio/cheatsheets
- ggplot2 reference → ggplot2.tidyverse.org/reference
- aesthetics finder → ggplot2tor.com/aesthetics
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Useful Packages (alphabetically):
{cowplot}— plot arrangements, themes & annotations → wilkelab.org/cowplot{ggalt}— alternative coords, geoms, stats & scales → github.com/hrbrmstr/ggalt{gganimate}— create animations → gganimate.com{ggbump}— geoms for bump charts → github.com/davidsjoberg/ggbump{ggforce}— several interesting add-on features → ggforce.data-imaginist.com{ggmaps}— access to Google & Stamen maps → github.com/dkahle/ggmap{ggplotly}— create interactive plots → plot.ly/ggplot2{ggraph}— networks, graphs & trees → github.com/thomasp85/ggraph{ggrepel}— prevent overlapping text labels → github.com/slowkow/ggrepel{ggridges}— geoms for ridgeline plots → github.com/clauswilke/ggridges{ggsankey}— geoms for sankey diagrams → github.com/davidsjoberg/ggsankey{ggstream}— geoms for stream graphs → github.com/davidsjoberg/ggstream{ggtext}— rich-text rendering → github.com/clauswilke/ggtext{ggthemes}— additional themes, sclaes & geoms → github.com/jrnold/ggthemes{hrbrthemes}— typography-centric themes → github.com/hrbrmstr/hrbrthemes{lemon}— axis & legend add-ons → github.com/stefanedwards/lemon{patchwork}— combine ggplots → github.com/thomasp85/patchwork{rayshader}— hillshaded maps in 2D & 3D → github.com/tylermorganwall/rayshader{systemfonts}— use custom fonts → github.com/r-lib/systemfonts
