Section 2 Software Requirements
To recreate or replicate this study, specialized software is needed to obtain and process federal data. All the software that was used in this process is free and available online. It is best practice to use the most updated software version.
- The R coding language from cloud.r-project.org. This language is used to obtain and process data.
- RStudio Desktop from rstudio.com. RStudio is the integrated development environment (IDE) used to run R scripts and develop code.
- Git from git-scm.com. A comprehensive guide to installing Git is available at happygitwithr.com. Git allows version control of edits across a multi-person team of researchers.
- If a GitHub account is needed, one can sign up and register at https://github.com/. Individual free plans are available, as well as free upgrades for qualifying academic purposes. GitHub is used to develop and host this project.
2.1 Download Necessary R Libraries
To make sure the code can be run, please ensure that the following R library packages are installed. If you are using RStudio, packages can be installed from CRAN using the ‘install.packages(“[package_name]”)’ command in the terminal.
- dplyr: Used for manipulating dataframes. (Wickham et al. 2021)
- httr: Used for working with URLs and HTTP. (Wickham 2020)
- jsonlite: Used for interacting with JSON data and web APIs. (Ooms 2014)
- openxlsx: Used for reading, writing and editing xlsx files. (Schauberger and Walker 2021)
- readxl: Used for legacy excel .xls files. (Wickham and Bryan 2019)
- tidyverse: A collection of R packages optimized for data science. (Wickham et al. 2019)
The next section details data necessary to complete this project as well as how to obtain it.