Data Visualization with R

Claudia A Engel

Last updated: June 24, 2019

Prerequisites and Preparations

To get the most out of this workshop you should have:

• a basic knowledge of R and/or be familiar with the topics covered in the Introduction to R.
• have a recent version of R and RStudio installed.
• have installed the tidyverse package.

Recommended:

• Create a new RStudio project R-data-viz in a new folder R-data-viz and download both CSV files into a subdirectory called data:
  • Download MS_stops.csv from here: https://github.com/cengel/R-data-viz/raw/master/data/MS_stops.csv
  • Download MS_county_stops.csv from here: https://github.com/cengel/R-data-viz/raw/master/data/MS_county_stops.csv
  • If you have your working directory set to R-data-viz which contains a folder called data you can copy, paste, and run the following lines in R:

download.file("https://github.com/cengel/R-data-viz/raw/master/data/MS_stops.csv", 
              "data/MS_stops.csv")

download.file("https://github.com/cengel/R-data-viz/raw/master/data/MS_stops_by_county.csv", 
              "data/MS_stops_by_county.csv")

• Open up a new R Script file R-data-viz.R for the code you’ll create during the workshop.

References

Chang, W. (2012): R Graphics Cookbook. Stanford only online access

Healy, K (2019): Data visualization : a practical introduction. Searchworks

Murrell, P. (2012): R Graphics, 2nd ed. Stanford only online access

Rahlf, T (2017): Data Visualisation with R. http://www.springer.com/us/book/9783319497501

Wickham, H. (2016): ggplot2: Elegant Graphics for Data Analysis. 2nd ed. http://link.springer.com/book/10.1007/978-3-319-24277-4

Acknowledgements

Part of the materials for this tutorial are adapted from http://datacarpentry.org and http://softwarecarpentry.org.

Data sample taken from https://openpolicing.stanford.edu/