I was remembering 15 years ago. By that time, I used to plot data with Excell, I did not have any alternative. However, I started to get used to R. I finally have the tool to extract information from bare data.
I first used R because I needed to process biological data. I was comfortable writing code in perl, mainly because much of the data I was using were biological sequences, so it was sufficient. However, I realized data simulation could be a headache in perl, then R appears to be a good alternative. Furthermore, plotting results for my dissertation was pretty straightforward so I become more fluent in R.
For several years I used only plot() function (and also hist() and image()), because I told myself that using code from libraries was a signal of weakness. You know, juvenile thoughts about non-significant things. I refused to learn new syntaxis, and until 2017 I never used ggplot2 library.
I remember when I was trying to figure out how to build a sunburst visualization, and because one of my best friends I take a look on D3. One thing drove me to another until I arrive at plotly. Then I started to go deep and I found that plotly was also in python as well as in julia. So I started to use it. It was a big surprise to me that there was a ggplotly() function that allows regular users of ggplot2 to provide interactivity to their plots, so I was forced to learn ggplot2 (and all the tidyverse package).
Well finally I started to use interactive plots such as the following
ggplot(aes(x=performance, y=ofensive, size=defense, color=matches, text=team)) +
geom_point() +
labs(title="Performance vs offensiveness of National Teams in matches of FIFA World Cup") -> p
ggplotly(p)
And yes, this was the history of how I learned ggplot2 in just the opposite way you normally learn it.