Final answer:
One primary drawback of R's base plotting system is its lack of simple support for creating and managing multi-layered graphics and reusing elements across plots, making it less efficient for complex visualizations.
Step-by-step explanation:
One of the first drawbacks of the base plotting system in R is its lack of support for creating multi-layered graphics easily. In base plotting, each time you plot, you start from a blank canvas and can add elements with subsequent commands. However, creating complex, multi-layered plots can become cumbersome.
For instance, if you desire to superimpose multiple plots, such as a line graph on top of a bar chart, base R plotting would require you to carefully orchestrate the plot order and parameters to ensure correct overlay and alignment.
Moreover, it lacks a consistent way to modify and reuse elements across different plots. When dealing with complex figures that require consistency, such as scientific publications, this limitation means repetitively setting plot configurations, instead of being able to define and apply themes or styles universally across various figures.
These limitations have resulted in the development of alternative plotting systems within R, like ggplot2, which provide a more intuitive grammar for layering and theming graphs. Plot modification in ggplot2 can be done more systematically, allowing users to incrementally add or adjust layers and themes across various plot types. This makes the process of creating sophisticated plots more efficient and less error-prone than when using the base plotting system.