But with multiple researchers developing their own solutions - often in personal folders, and by copy-and-pasting from other projects - errors and inconsistencies accumulated. To address this, some of our researchers started developing custom versions of Pew-style graphics using ggplot2, a complex yet highly customizable data visualization tool in the tidyverse suite for R. As a result, our R users typically had two options: produce graphics directly in R that would need extensive reworking prior to publication or leave the R environment entirely in order to create stylistically appropriate visualizations.

However, the standard graphics libraries in R look quite different from Pew Research Center’s in-house style. R allows users to generate iterative graphics directly from analysis scripts, which is helpful for quickly evaluating different ways to visualize results and findings. In recent years, many of our researchers have expressed an interest in using R as an integrated environment for data analysis and graphics development. Traditionally, our report graphics have been generated by individual researchers using a custom Excel template developed by our design team, or on an ad hoc basis by graphic designers using professional tools and mock-up designs.

Creating informative and digestible data visualizations is a foundational aspect of Pew Research Center’s work.

Creating an r package