If I'm to dig in the manual, I might as well build my plots with the standard syntax of any random plotting library.
Is this "grammar of graphics" any good if you invest more time in it?
Layers are as follows [1]
1. Data
2. Aesthetic mappings
3. Statistical transformation (stat)
4. Geometric object (geom)
5. Position adjustment
Once you get a hang of this, it becomes easy to create new plots purely from the understanding of the layers. In matplotlib or even in Seaborn, I find myself constantly Googling for examples.
ggplot2 is the most beautiful thing to happen in visualization space!
[1] Wickham, Hadley, and Carson Sievert. "4.4.1 Layers." Ggplot2: Elegant Graphics for Data Analysis. Dordrecht: Springer, 2016. N. pag. Print.
For some, it was probably one of THE things that kept them using R over something else. Yes, definitely worth it.