Frustration-One-Year-With-R VS cheatsheets

R is my least favorite language to use, thanks to the uni courses that force it

https://github.com/ReeceGoding/Frustration-One-Year-With-R

python is a lot more consistent than R. it doesn't have most of the bullshit detailed here: https://github.com/ReeceGoding/Frustration-One-Year-With-R

See my friend's essay about it.

A friend of mine wrote a [recently viral R takedown](https://github.com/ReeceGoding/Frustration-One-Year-With-R) that shocked people in the same way.

I 100% agree, I think the functional features that have been added across all the popular languages (map, reduce, fold etc.) has been a positive. Nothing demonstrates it better (imo) than purrr in R: https://github.com/rstudio/cheatsheets/blob/main/purrr.pdf

I also think there is some merit to “high syntactical density” clearly if you can see the entire code in one place instead of having to navigate through many files or sections that’s beneficial. (Heavily discussed in the last big HN thread: https://news.ycombinator.com/item?id=38981639)

I also think JQ has proven the merit of tacit functional languages in that you can concisely write arbitrary transforms/queries on json that can be more expressive than SQL (many SQL engines have added JSONPath anyway). And I also think postfix is great for processing pipelines.

But I am not totally convinced in the approach of APL/J/Q/KDB for the combination of terse style + prefix + tacit because it makes the code so difficult to read. I think if you took an approach similar to JQ where instead of relying on symbols operators were just human readable words it would be easier to get us half way there to trying out the verb, adverbs etc. approach of the APL family. The problem with making it human readable text is that you lose the conciseness which is part of the draw of the APL family as they want to have a high syntax density and analogous code to mathematical expressions.

If you're an R user, stringr + its cheatsheet gets you very close to remembering what to do without needing to look further!

For more information on how to use ggplot2 and create charts consult the ggplot2 official page or the ggplot2 cheat graphic.

I'd suggest you have a look at cheatsheets (or download them from GitHub) if you want to get to know your way around a package or set if functions, it saves you a lot of time.

You could use geom_hline and geom_vline, geom_abline, or geom_segment for this. (The ggplot cheat sheet is very useful for answering these kinds of questions, BTW.)

I can't say for sure because I don't know what your ultimate aim is for your visualization. Check out the cheat sheet for ggplot2 here.

Finally just do your analysis. You should also should give a try and see the cheat sheet for data importing on the tidyverse package.

That said, when I’m trying to come up with an interesting way to visualize data, I find the ggplot cheat sheet very helpful: https://github.com/rstudio/cheatsheets/raw/main/data-visualization-2.1.pdf

Here's a cheat sheet: https://github.com/rstudio/cheatsheets/blob/main/strings.pdf

The cheat sheet of the stringr package should give you good overview of string manipulation/ regex in R.