An opinionated view of the Tidyverse “dialect” of the R language

This article only briefly touches on what I think is the biggest issue with the Tidyverse. The Tidyverse is incredibly limiting. The "tidy" workflow hides many details of the language, which leads many users to think all data has to be in a tidy "data.frame" (or now tibble) and organized just so. The functions the Tidyverse authors have chosen to implement are seen as the limits of R's capabilities. Every data problem has to be forced into the Tidyverse box (or it is impossible). I cannot tell you how many Tidyverse scripts I have seen where 90% of the operations are munging the data into the correct format for the Tidyverse functions, when the original data can be handled with a single base R function (e.g. lapply). Most Tidyverse users accept this as just the way R is.

Most R users who only learn the Tidyverse never hit its limits, and for them the Tidyverse is perfectly OK. Those that do either resign themselves to the perceived limits of R, or (hopefully) start learning some base R. One friend who took the latter path once exclaimed to me "Logical subsetting is amazing!?!" - this is a foundation piece of the language. That she went 2+ years in the "Tidyverse" without even knowing it was an option was eye opening to me.

To its credit, the Tidyverse is empowering - with very little programming knowledge a beginner can do a lot of data science. However, the majority of these people get stuck as "expert beginners". Some of these become fierce advocates of the Tidyverse without truly understanding base R. Meanwhile, none of the truly advanced R users I encounter use the Tidyverse.

ed.typo

Programming in base R is more akin to assembly language and has accreted a babel of inconsistencies that make it difficult to teach and learn. Learning base R isolates you into a Galapagos island of academics who are either ignorant of the needs of data workers or too elitist to engage with those not in their priesthood.

Learning Tidyverse is a considerably better transition for learning other languages, frameworks, and libraries.

Functional programming is closer to algebra than indexing into data structures with magic numbers. I've found more success teaching functional pipelines of data structures using the idioms in Tidyverse as a general framework for data work than base R. Abstraction has a cost but for learning it is the appropriate cost.

I sense that much of this `monopolistic` fear mongering is really about feeling out of date.

I have not tried it in many years and I don't know how much faster or compatible it is. Nevertheless, I think it's a good thing that an "outsider" is looking at performance issues.

As far as I know it's essentially a one-man's effort. One could imagine that RStudio or Microsoft would be able to improve R performance substantially if they wanted to.

Imho, the data problem Tidyverse is trying to solve is basically the ones we face in a database. So, select, join, inner join and so forth. Show me all the rows in this datatable where the 4th columm is larger than the 6th column and the number itself is odd. Something like that.

There might be other ways to do it, but you want your select, filter, summarize, mutate etc functions to all work with each other, pipe to each other and be compatible.

Maybe there is a better way to do all this -- I haven't seen it but I am not an expert -- but you have to show that to me.

So, in base R, walk through a set of example of mutating, joining, filtering and so forth, and show me how they are all easier. Then I'll say, wow there is an alternative to this Tidyverse thing. But in lieu of that demo, this felt more like an intro to a complaint than an actual complaint.

Edit: Also, its funny that Wickham is (apparently) such a nice fellow that people go out of the way to be nice to him in critiques.