The scripts for data collection and analysis are in the R/ folder. dm_outcome.R is the data mangement script for the CDC infant mortality data; dm_census.R is the data management script for the Census data; and helper_functions.R contains a function that prints an lm object as an equation in LaTeX.
Each section of the paper has a dedicated .Rmd script, each of which can be found in the Rmd/ folder. Because these are knit as children to the main paper.Rmd, the environment (i.e., all the objects and loaded libraries) from paper.Rmd are loaded into each section's markdown file.
To avoid storing data in GitHub, all .csv files are included in the .gitignore. The raw data from the CDC is stored in this repository, as I had to download these data manually (i.e., not programatically through an API). The first time you knit the paper, the data will download and save, which will take a bit of time; the following times, the report should pull from the saved, processed data.
After cloning the repository, double-click on the final_project.RProj file to open the R project in RStudio. Then, open your R console and install the renv package: install.packages("renv"). renv creates a virtual environment to keep all package dependencies nice and organized. If this is your first installation of renv, quit and reopen RStudio before proceeding. To install all the packages necessary for knitting this paper, in the console run: renv::restore(). I've found that renv can be a bit finicky—especially on Macs—so you may have to run renv::restore(), close RStudio, open the project again, and then run renv::restore() a second time.
Finally, knit paper.Rmd, which will in turn knit and stitch together all of the sections of the paper.
Note: You will need a Census API key to download Census data. If you don't have a key, get one here and use tidycensus::census_api_key(your_key) to install it.