Why I use ggplot2

A somewhat off topic note: that gganimate GIF is 3.5 MB, which is a very large file for a image that is not central to the argument!

That's one of the reasons I was dissuaded from making GIFs from my ggplot2 charts, and it's why I created a Convert Frames to GIF tool (https://github.com/minimaxir/frames-to-gif-osx) to create higher-quality GIFs at manageable file sizes. (the first example GIF in my repo is about the same number of frames and resolution as the OP's GIF, but 1/7th of the filesize, of course due to the nature of GIFs this is not a straight comparison) That said, gganimate does sound like an interesting tool, and certainly much better than the animation package alone.

The killer feature of ggplot2 that cannot easily be replicated in any GUI program is indeed faceting. There are also other geoms that are hard to do in base R/excel are things, like contour maps and native smoothed regression lines (with confidence intervals!)

Python's matplotlib was apparently good enough for the Gravitational Wave paper.

I think both this post and the post it is arguing against are actually arguing the same thing... You have to think about what you are communicating and not just plot out things and say you're done.

I have found that base R graphics were a quick way to get a snapshot of things qplot always frustrated me in their syntax. I have replaced that with ggvis. I can do a 3 seconds of code and get a decent plot. I can then add a drop down menu and explore my data, but ggvis is guilty of Jeff Leek's criticism currently with a limit of the plot you can perform. Also ggvis exported to png is more a hassle then it is worth for me.

A fantastic set of APIs with Matplotlib under the hood: Seaborn

Http://stanford.edu/~mwaskom/software/seaborn/

for heatmaps with dendrograms there is ggdendro: https://plot.ly/ggplot2/ggdendro-dendrograms/

but it's definitely not a streamlined experience.. most of the time I just use pheatmap: https://cran.r-project.org/web/packages/pheatmap/index.html

Earlier post was discussed at https://news.ycombinator.com/item?id=11081961.

Honorable mention for yhat's port of ggplot2 to python. http://ggplot.yhathq.com/