Recommended resources

I mostly use packages that are a part of the tidyverse or which work well with the tidyverse (e.g., sf). The R universe has lots of great resources on those and other topics. Here are some that I’d recommend:

• For general data wrangling and other data management in the tidyverse (dplyr and other tidyverse packages)

  • Tidyverse home page: https://www.tidyverse.org/

  • dplyr home page: https://dplyr.tidyverse.org/

  • R for Data Science: https://r4ds.had.co.nz/.

    • This book by Hadley Wickham and Garrett Grolemund is the authoritative guide for learning dplyr and other tidyverse packages.

    • The chapter on dplyr specifically is https://r4ds.had.co.nz/transform.html.

  • Tips for using dplyr by Dr. Michael Kramer, an Emory colleague, as part of his course on Spatial Epidemiology: https://mkram01.github.io/EPI563-SpatialEPI/dplyr.html

  • For importing rectangular data (e.g., CSV) using readr: https://readr.tidyverse.org/

  • For explanation of more “under-the-hood” technical topics, I would suggest https://adv-r.hadley.nz/

• For manipulating (vector-based) spatial data (sf)

  • sf home page: https://r-spatial.github.io/sf/index.html

  • sf vignettes (1-5), e.g., https://r-spatial.github.io/sf/articles/sf1.html

  • sf cheatsheet: https://github.com/rstudio/cheatsheets/blob/main/sf.pdf

  • Geocomputation with R (Lovelace, Nowosad, Muenchow) : https://geocompr.robinlovelace.net/

    • Key chapters on managing sf:

      • https://geocompr.robinlovelace.net/spatial-operations.html

      • https://geocompr.robinlovelace.net/geometric-operations.html

    • This book also covers raster data and corresponding packages (terra and raster).

  • Chapter on sf in Spatial Data Science (Pebesma, Bivand): https://keen-swartz-3146c4.netlify.app/sf.html#sfintro

  • Tips for working with sf by Dr. Michael Kramer: https://mkram01.github.io/EPI563-SpatialEPI/sf-overview.html

• For making charts and figures (ggplot2)

  • ggplot2 home page: https://ggplot2.tidyverse.org/

  • cookbook: http://www.cookbook-r.com/Graphs/

  • ggplot2 cheat sheet: https://raw.githubusercontent.com/rstudio/cheatsheets/main/data-visualization.pdf

  • Data visualization principles: book (not free) by Kieran Healy, https://kieranhealy.org/publications/dataviz/

• For making maps (mapview, tmap, ggplot2)

  • Chapter on making maps in Geocomputation with R: https://geocompr.robinlovelace.net/adv-map.html

  • Mapview is my favorite mapping package, in part for its simplicity.

    • Its home page is https://r-spatial.github.io/mapview/

    • Several vignettes are available on that page, e.g., https://r-spatial.github.io/mapview/articles/mapview_01-basics.html

  • Tmap is another widely used mapping package and can create both static and interactive maps.

    • https://r-tmap.github.io/tmap/index.html

    • https://r-tmap.github.io/tmap/articles/tmap-getstarted.html

    • https://cengel.github.io/R-spatial/mapping.html#choropleth-with-tmap

    • https://mkram01.github.io/EPI563-SpatialEPI/intro-tmap.html

  • ggplot2 can also be used to make static maps of sf objects:

    • https://ggplot2.tidyverse.org/reference/ggsf.html

    • Chapter in Spatial Data Science: https://keen-swartz-3146c4.netlify.app/plotting.html#geomsf

  • Color palettes:

    • viridis: https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html

      • Note viridis is often the default option in mapview.

      • Note viridis is built into some ggplot2 functions.

    • RColorBrewer:

      • website to see color palettes: https://colorbrewer2.org/

      • R package: https://cran.r-project.org/web/packages/RColorBrewer/index.html

• Other miscellaneous resources I frequently use and reading I recommend:

  • RStudio cheatsheets on dplyr, ggplot2, and more: https://www.rstudio.com/resources/cheatsheets/

  • For downloading free or open-source data into R:

    • Downloading census data (tidycensus): https://walker-data.com/tidycensus/

    • Downloading OpenStreetMap data (osmdata): https://cran.r-project.org/web/packages/osmdata/vignettes/osmdata.html

  • R Markdown:

    • R Markdown, the Definitive Guide: https://bookdown.org/yihui/rmarkdown/

    • R Markdown Cookbook: https://bookdown.org/yihui/rmarkdown-cookbook/

  • On managing working directory and organizing projects:

    • Jenny Bryan on the importance of a project-oriented workflow: https://www.tidyverse.org/blog/2017/12/workflow-vs-script/

    • Jenny Bryan’s Ode to the here package: https://github.com/jennybc/here_here

    • Folder structure of R projects: https://chrisvoncsefalvay.com/2018/08/09/structuring-r-projects/

  • The Epidemiologist R Handbook: https://epirhandbook.com/en/index.html

    • This is an online book whose target audience is public-health professionals and epidemiologists.

    • It has a chapter on transitioning to R targeting those who primarily use Excel, SAS, or STATA: https://epirhandbook.com/en/transition-to-r.html

  • RStudio keyboard shortcuts:

    • https://support.rstudio.com/hc/en-us/articles/200711853-Keyboard-Shortcuts-in-the-RStudio-IDE

    • The two keyboard shortcuts I use the most are:

      Operation	Mac	Windows & Linux
      Run current line / selection	cmd+return	ctrl+enter
      Insert pipe (%>%)	cmd+shift+m	ctrl+shift+m

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