index.Rmd

---
title: "Dataviz Shortcourse"
description: A bootcamp-style course on data visualization
site: distill::distill_website
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)

# Learn more about creating websites with Distill at:
# https://rstudio.github.io/distill/website.html

# Learn more about publishing to GitHub Pages at:
# https://rstudio.github.io/distill/publish_website.html#github-pages

```

This is the home page for a dataviz shortcourse by Claus O. Wilke. The course is an abbreviated version of a [semester-long course](https://wilkelab.org/SDS375) taught at The University of Texas at Austin. Many of the materials presented are taken from the book [Fundamentals of Data Visualization.](https://clauswilke.com/dataviz/)

<!--
To run any of the R code examples locally on your own machine, you will need the following:

- A recent version of R, [download from here.](https://cloud.r-project.org/)
- A recent version of RStudio, [download from here.](https://rstudio.com/products/rstudio/download/#download)
- The following R packages:    
  broom, cluster, colorspace, cowplot, distill, gapminder, GGally, gganimate,  ggiraph, ggdendro, ggdist, ggforce, ggplot2movies, ggrepel, ggridges, ggthemes, gifski, glue, knitr, learnr, naniar, margins, MASS, Matrix, nycflights13, palmerpenguins, patchwork, rgdal, rmarkdown, sf, tidyverse, transformr, umap, xaringan

You can install all required R packages at once by running the following code in the R command line:

```{r eval = FALSE, echo = TRUE}
install.packages(
  c(
    "broom", "cluster", "colorspace", "cowplot", "distill", "gapminder", 
    "GGally", "gganimate", "ggiraph", "ggdendro", "ggdist", "ggforce",
    "ggplot2movies", "ggrepel", "ggridges", "ggthemes", "gifski", "glue",
    "knitr", "learnr", "naniar", "margins", "MASS", "Matrix",
    "nycflights13", "palmerpenguins", "patchwork", "rgdal", "rmarkdown",
    "sf", "tidyverse", "transformr", "umap", "xaringan"
  )
)
```
-->

## Reuse {.appendix}

Text and figures are licensed under Creative Commons Attribution [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). Any computer code (R, HTML, CSS, etc.) in slides and worksheets, including in slide and worksheet sources, is also licensed under [MIT](https://github.com/wilkelab/SDS375/LICENSE.md). Note that figures in slides may be pulled in from external sources and may be licensed under different terms. For such images, image credits are available in the slide notes, accessible via pressing the letter 'p'.