This repository contains lesson materials from Chris's RLadies session in April 2019, which covers some basic elements of working with spatial data using tidystl.
By the end of this lesson, learners should be able to:
- The
SETUP.mdfile in thereferences/directory contains a list of packages required for this lesson - The
notebook/directory contains our primary teaching materials, included a completed version of the notebook we will be working on during the seminar. - The
references/directory also contains other notes on changes to the repository, key topics, terms, data sources, and software.
Before you proceed with other installations, it is important to get the sf package installed correctly. You should be able to install sf using:
install.packages("sf")If you run into issues, check the setup instructions for suggestions.
Once you have sf up and running, the packages we'll need for today can be installed using:
install.packages(c("tidyverse", "here", "knitr", "mapview", "remotes", "rmarkdown", "stlcsb", "testthat", "usethis", "viridis"))There are several other packages we'll need which are not yet published on CRAN. These can be installed with the remotes package once you've run the code chunk above:
remotes::install_github(c("slu-openGIS/compstatr", "slu-openGIS/gateway", "slu-openGIS/postmastr"))You can download this lesson to your Desktop easily using usethis:
usethis::use_course("https://github.com/slu-openGIS/rladies19/archive/master.zip")By using usethis::use_course, all of the lesson materials will be downloaded to your computer, automatically extracted, and saved to your desktop. You can then open the .Rproj file to get started.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
The openGIS project is a collaborative effort with SLU students to curate and host GIS data about the St. Louis area in an accessible manner. We also maintain several R packages that contain tools for working with spatial data. The project is a part of the SLU Data Science Seminar.
The SLU Data Science Seminar (DSS) is a collaborative, interdisciplinary group at Saint Louis University focused on building researchers’ data science skills using open source software. We currently host seminars focused on the programming language R. The SLU DSS is co-organized by Christina Gacia, Ph.D. and Christopher Prener, Ph.D.. You can keep up with us here on GitHub, on our website, and on Twitter.
Founded in 1818, Saint Louis University is one of the nation’s oldest and most prestigious Catholic institutions. Rooted in Jesuit values and its pioneering history as the first university west of the Mississippi River, SLU offers nearly 13,000 students a rigorous, transformative education of the whole person. At the core of the University’s diverse community of scholars is SLU’s service-focused mission, which challenges and prepares students to make the world a better, more just place.