Branding and Packaging Reports with R Markdown

January 1, 2020


Create custom R Markdown templates and ggplot2 themes, then package them up to distribute.


January 30, 2020


10:30 AM – 10:52 AM


San Francisco, CA


The creation of research reports and manuscripts is a critical aspect of the work conducted by organizations and individual researchers. Most often, this process involves copying and pasting output from many different analyses into a separate document. Especially in organizations that produce annual reports for repeated analyses, this process can also involve applying incremental updates to annual reports. It is important to ensure that all relevant tables, figures, and numbers within the text are updated appropriately. Done manually, these processes are often error prone and inefficient. R Markdown is ideally suited to support these tasks. With R Markdown, users are able to conduct analyses directly in the document or read in output from a separate analyses pipeline. Tables, figures, and in-line results can then be dynamically populated and automatically numbered to ensure that everything is correctly updated when new data is provided. Additionally, the appearance of documents rendered with R Markdown can be customized to meet specific branding and formatting requirements of organizations and journals. In this presentation, we will present one implementation of customized R Markdown reports used for Accessible Teaching, Learning, and Assessment Systems (ATLAS) at the University of Kansas. A publicly available R package, ratlas, provides both Microsoft Word and LaTeX templates for different types of projects at ATLAS with their own unique formatting requirements. We will discuss how to create brand-specific templates, as well as how to incorporate the templates into an R package that can be used to unify report creation across an organization. We will also describe other components of branding reports beyond R Markdown templates, including customized ggplot2 themes, which can also be wrapped into the R package. Finally, we will share lessons learned from incorporating the R package workflow into an existing reporting pipeline.

Here are links to the various (and very good!) resources I recommend for building branded R Markdown reports and packages:

  • For creating templates for MS Word documents:
  • For polishing reports with custom ggplot2 themes and default knitr chunk options:
    • Bob Rudis’s hrbrthemes, Emily Riederer’s Rtistic, and the BBC’s bbplot all provide great examples and/or templates for creating ggplot2 themes and wrapping them into an R package.
    • A comprehensive list of availalbe {knitr} chunk options are availabe on Yihui Xie’s website.
  • Finally, examples of wrapping R Markdown templates and/or {ggplot2} themes into packages for an organization:
    • The ratlas package used by Accessible Teaching, Learning, and Assessment Systems at the University of Kansas.
    • The sorensonimpact package used by the Sorenson Impact Center at the University of Utah.
    • The thesisdown package for writing theses at Reed College.
      • This package has many forks for other colleges, which are linked to in the {thesisdown} README. This is a great example for how to take an existing package and adapt it to the needs of your organization.
    • The rticles package provides wrappers for templates for a variety of academic journals.
Posted on:
January 1, 2020
3 minute read, 511 words
talk conference R package
ATLAS rmarkdown ggplot2
See Also:
Creating ggplot2 fill and color scales
Tidy Data Science with the tidyverse and tidymodels
Tidy Data Science with the `tidyverse` and `tidymodels`