I almost wish Hadley had forked R to make the tidyverse. What I usually see are people that start using tidy functions and coding style, but at some point they realize they don’t know how to do something the tidy way or something hasn’t been implemented in a tidy package yet, so they fall back to base R.<p>Imho, transitioning from tidy to base R makes your code less readable than just using base R throughout.<p>If the tidyverse were forked and base R functions weren’t available then people would be forced to come up with a different solution and maybe they would stay committed to being tidy. I realize that probably won’t ever happen, there is too much work to reimplement all the missing base R functions.
Absolutely not.<p>Theres more to the R ecosystem than tidyverse packages. There's a whole suite of absolutely amazing R packages in the bioconductor ecosystem that rival tidyverse in speed and ease of use but targeting other data structures.<p>Some of the tidyverse packages are over kill and contain lots of foot guns.<p>I've seen code that was clean get butchered because someone had no idea how to do something basic in base R.<p>There's also another separate ecosystem for doing stats with their own flavors.
As a daily R user, hard disagree. With the exception of ggplot (and this is directly related to why I don't use ggplot and instead use base plotting), most of tidyverse is pretty similar to and consistent with most base R functions.<p>Tidyverse standalone would be borderline useless, as most of what it's best at is manipulating, transorming, and re-arranging your data in various ways. You still need to _do_ something with your data at the end, at which point, the entire rest of the R ecosystem comes into play.<p>Tidyverse is valuable specifically because it's the best at doing what it does, and what it does makes everything else easier, more legible, and faster.<p>Forking it would simultaneously make both R and tidyverse worse off.
I worked in a job a decade back where I was the only tech guy and had a special 128 GB RAM machine. All the 'Big data' for the team was done by me using R tidyverse, data.table and few libraries and they thought of it as magic as there were few tech people there.<p>Still feel a lot of enterprises and industries looked over its capabilities then.<p>With LLMs the challenge of R syntax is a little easier for data analysts to climb, especially the new ones.
There's a school of thought of using mostly base R, for all its flaws it already had before Hadley, and selectively using some tidyverse packages. Base R has been the de-facto coding standard for academic statisticians for decades, with all the wealth of open source packages that that entails, and some of the tidyverse packages are just a godsend. ggplot2 is probably the most powerful plotting library I've seen, while being fairly accessible. You don't have to subscribe to an entire philosophy for data wrangling or plotting (and may even frown at the syntax overloading) to get a huge amount of utility out of it.
> I almost wish Hadley had forked R to make the tidyverse<p>I am pretty sure there are R-core members who also wish this is what happened.
As someone that's been using R for 20 years, I don't necessarily wish that had happened, but I think the trend to teach intro R using the tidyverse is a bad development. People that use the tidyverse don't realize that it's complex. There are no doubt complex and frustrating parts of base R. For the most basic things, base R is natural. The tidyverse has you piping and using advanced concepts from the start.
This. They're basically two languages sitting on top of each other. It's fascinating seeing students who have been taught using the tidyverse try to switch gears.