I'd divide my work into three categories
- Exploratory plots just for me.
- Plots that I'm going to show to my boss or coworkers.
- Things we're going to distribute to the whole world.
Plots in category #1 are often quick and dirty--I just want to see if an idea worked and don't really care about communicating that idea cleanly.
I could show these plots internally, but it often helps to clean them up a bit first. This avoids us getting bogged down in whether we should be comparing the red/blue lines here or the circle/diamond points there.
This is where ggplot shines--I can go from #1 to #2 with minimal effort. The final version usually still needs some tweaking, but only a small fraction of the plots ever get this far and some of this customization really needs a human in the loop (e.g., in Illustrator or something).
Similarly, while you can use Shiny as final product, it's actually great for letting moderate-sized groups play "what-if" with the data. It's certainly easier than sending them a huge powerpoint deck with "choose your own adventure" style instructions.
Plots in category #1 are often quick and dirty--I just want to see if an idea worked and don't really care about communicating that idea cleanly.
I could show these plots internally, but it often helps to clean them up a bit first. This avoids us getting bogged down in whether we should be comparing the red/blue lines here or the circle/diamond points there.
This is where ggplot shines--I can go from #1 to #2 with minimal effort. The final version usually still needs some tweaking, but only a small fraction of the plots ever get this far and some of this customization really needs a human in the loop (e.g., in Illustrator or something).
Similarly, while you can use Shiny as final product, it's actually great for letting moderate-sized groups play "what-if" with the data. It's certainly easier than sending them a huge powerpoint deck with "choose your own adventure" style instructions.