# Comparison of plotting system outputs in beginner analysts

## TL;DR

This study empirically compares the quality of scientific graphics produced by beginner R users using base R and ggplot2, finding ggplot2 often produces more visually pleasing and understandable plots, especially for complex data.

## Contribution

It provides an empirical evaluation of beginner users' graphic quality in R, highlighting the advantages of ggplot2's faceting system for complex visualizations.

## Key findings

- Both systems produce comparable graphic quality on many metrics.
- ggplot2 graphics are rated more visually pleasing.
- Faceted plots in ggplot2 are easier to understand for beginners.

## Abstract

The R programming language is built on an ecosystem of packages, some that allow analysts to accomplish the same tasks. For example, there are at least two clear workflows for creating data visualizations in R: using the base graphics package (referred to as "base R") and the ggplot2 add-on package based on the grammar of graphics. Here we perform an empirical study of the quality of scientific graphics produced by beginning R users. In our experiment, learners taking a data science course on the Coursera platform were randomized to complete identical plotting exercises in either the base R or the ggplot2 system. Learners were then asked to evaluate their peers in terms of visual characteristics key to scientific cognition. We observed that graphics created with the two systems rated similarly on many characteristics. However, ggplot2 graphics were generally judged to be more visually pleasing and, in the case of faceted scientific plots, easier to understand. Our results suggest that while both graphic systems are useful in the hands of beginning users, ggplot2's natural faceting system may be easier to use by beginning users for displaying more complex relationships.