gordon_shotwell

Hmmm, I'm not sure there is an Excel style graph wizard, although there's this package which is close https://www.r-statistics.com/2016/11/ggedit-interactive-ggpl...

For PML() kinds of functions, I often just google something like "Excel PML() function in R" and something usually turns up: - https://cran.r-project.org/web/packages/optiRum/optiRum.pdf - https://gist.github.com/econ-r/dcd503815bbb271484ff

Another good tactic is to follow some of the R quants on twitter. A really popular package for this is http://www.quantmod.com/

From the tone of your post I'm thinking that you've made up your mind on this point, but there really is a lot of richness and extensibility in R which isn't available in Excel. For instance my blog is written in an R library called Blogdown, you can process 5 GB datasets on your laptop, send a reproducible analysis to a colleague, stuff like that.

I guess the thing I would ask you to consider when thinking about this stuff is the amount of time you've spent learning Excel. At the time I was learning R I probably had several thousand hours of focused Excel practice under my belt, and I could do a lot with the tool. So Excel was a way better tool for me than R because I was an Excel expert and an R novice. After now putting in about that same amount of time working with R I can say it's a much more powerful and extensible tool. But if you mostly work in areas where Excel...uh...excels, then there's no real reason to make the switch.

The R for Data Science book really is the best, but I would also recommend https://www.datacamp.com/ for some great video tutorials.

I'm thinking of writing a package which displays R errors as Pai Mei gifs.

That's a good point, I'm not exactly sure what the best practice is for using NSE vs. SE functions within functions. My practice is to just use the NSE version unless I have a good reason not to. Generally my goal with teaching beginners to use R is to just not be afraid of functions as the barrier tends to be feeling like they can use them at all rather than using them in the safest way.