Appendix A — Packages

Data Wrangling

Reads text data (CSV, TSV) efficiently into R data frames (tibbles).

Wickham H, Hester J, Bryan J (2024). readr: Read Rectangular Text Data. R package version 2.1.5 https://CRAN.R-project.org/package=readr.

Simplifies file paths by automatically locating the project root

Müller K (2020). here: A Simpler Way to Find Your Files. R package version 1.0.1 https://CRAN.R-project.org/package=here.

Core data manipulation package for filtering, selecting, summarizing, and transforming data frames.

Wickham H, François R, Henry L, Müller K, Vaughan D (2023). dplyr: A Grammar of Data Manipulation. R package version 1.1.4 https://CRAN.R-project.org/package=dplyr.

Reshapes data between wide and long formats.

Wickham H, Vaughan D, Girlich M (2024). tidyr: Tidy Messy Data. R package version 1.3.1 https://CRAN.R-project.org/package=tidyr.

Cleans variable names and performs quick data cleaning tasks

Firke S (2023). janitor: Simple Tools for Examining and Cleaning Dirty Data. R package version 2.2.0 https://CRAN.R-project.org/package=janitor.

Simplifies parsing, manipulating, and calculating with dates and times.

Garrett Grolemund, Hadley Wickham (2011). Dates and Times Made Easy with lubridate. Journal of Statistical Software, 40(3), 1-25 https://www.jstatsoft.org/v40/i03/.

Consistent, easy-to-use functions for working with strings and regular expressions.

Wickham H (2023). stringr: Simple, Consistent Wrappers for Common String Operations. R package version 1.5.1 https://CRAN.R-project.org/package=stringr.

Provides tools for controlling how data values are mapped to aesthetics (like adding a thousandth comma separator, e.g: ’1,000` instead of 1000)

Wickham H, Pedersen T, Seidel D (2023). scales: Scale Functions for Visualization. R package version 1.3.0, https://CRAN.R-project.org/package=scales.

Functional programming tools for working with lists, iteration, and mapping operations.

Wickham H, Henry L (2025). purrr: Functional Programming Tools. R package version 1.0.4 https://CRAN.R-project.org/package=purrr.

Provides tools for tidy evaluation and programming with tidyverse-style functions.

Henry L, Wickham H (2025). rlang: Functions for Base Types and Core R and ‘Tidyverse’ Features. R package version 1.1.5 https://CRAN.R-project.org/package=rlang.

Converts calendar dates to MMWR (epidemiological) weeks and years for public health analyses.

Niemi J (2020). MMWRweek: Convert Dates to MMWR Day, Week, and Year. R package version 0.1.3 https://CRAN.R-project.org/package=MMWRweek.

Data Visualization: Tables and Charts

Powers dynamic report generation by embedding R code and output into documents.

Xie Y (2025). knitr: A General-Purpose Package for Dynamic Report Generation in R. R package version 1.50 https://yihui.org/knitr/.

Yihui Xie (2015) Dynamic Documents with R and knitr. 2nd edition. Chapman and Hall/CRC. ISBN 978-1498716963

Yihui Xie (2014) knitr: A Comprehensive Tool for Reproducible Research in R. In Victoria Stodden, Friedrich Leisch and Roger D. Peng, editors, Implementing Reproducible Computational Research. Chapman and Hall/CRC. ISBN 978-1466561595

Extends knitr tables with advanced formatting and styling for HTML and LaTeX.

Zhu H (2024). kableExtra: Construct Complex Table with ‘kable’ and Pipe Syntax. R package version 1.4.0 https://CRAN.R-project.org/package=kableExtra.

Creates customizable, publication-quality data visualizations.

H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016. https://ggplot2.tidyverse.org

Data Visualization: Maps

Bring in Census TIGER/Line Shapefiles (e.g., state and county boundaries)

Walker K (2024). tigris: Load Census TIGER/Line Shapefiles. R package version 2.1 https://CRAN.R-project.org/package=tigris.

The core R package for reading, manipulating, analyzing, and visualizing spatial vector data using the simple features standard (i.e., “shapefiles”).

Pebesma, E., & Bivand, R. (2023). Spatial Data Science: With Applications in R. Chapman and Hall/CRC. https://doi.org/10.1201/9780429459016

Pebesma, E., 2018. Simple Features for R: Standardized Support for Spatial Vector Data. The R Journal 10 (1), 439-446 https://doi.org/10.32614/RJ-2018-009

Tools for calculating data classification intervals (e.g., equal breaks, quantiles, Jenks) for statistical data classification, and is especially helpful for mapping and visualizations.

Bivand R (2025). classInt: Choose Univariate Class Intervals. R package version 0.4-11 https://CRAN.R-project.org/package=classInt.