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The breaking changes are all quite severe, I hope there is real demand for the features they are bringing in.

Even if they don't agree with the direction Wickham's Tidyverse is going it showcased how flexible the R language was to being rewritten from the inside. Hadley effectively pulled of a more significant language upgrade with less breakages - the R core team could learn something from him here. Even their sensible na.rm default for new functions is introducing more weird inconsistencies to R.



Tidyverse introduces plenty of breakages, and as noted elsewhere does relentlessly between its own versions. Just check how the docs have evolved on ggplot2 for one example.

Tidyverse seems to be very much aimed at solving the initial learning curve. However, ANY system which uses allows non-experts to fake expertise denies them the ability to achieve real expertise, and also takes away skills from existing experts.

I'm grumpy about some of the reasons given for Tidyverse superiority: The Stringr package is supposedly somehow better because all of its functions start with "string" so you know you are working with strings. Huh? Because it replaces/wraps a lot of functions which begin with grep so you know you are working with regular expressions. Should we also create a "numbr" package which renames every function which works with "numbers"? Or maybe a subset of numbers, maybe we need a package called "integr".

data.table blows tbs out of the water, once you learn how to use it. Yes, it is harder to learn. Yes, it is very much worth it.

Yes, Hadley pulled off a language upgrade, and with the power of RStudio behind him has a strong hand indeed.

Just wonder if it is better or worse?


Stringr is better because the functions are all vectorized in simple and consistent ways.


Agreed! String manipulation functions in base R work differently in ways that make data cleaning annoying. Stringr frees me from having to remember that stuff and lets me focus on what I'm trying to do instead.


At this point Wickham is almost developing a parallel language that happens to be backwards compatible.


Has the R core team publicly stated that they disagree with direction Wickham's Tidyverse is going? Genuinely asking as I love the Tidyverse, but would be interested to hear arguments against it.


I am not sure why the original commenter said that tidyverse is more backwards-compatible compared with R core. It used to introduce breaking changes every 6 months or so.

Also they like it this way and promote it: https://twitter.com/hadleywickham/status/1175388442802479104


They still do.

I like the tidyverse, but Hadley's struggles with lazy evaluation and arguments has cost me lots and lots of time updating internal code at various workplaces.

Don't get me wrong, the tidyverse is great, but if I was writing R code that I expected to run without supervision for a long time, I'd avoid it as much as possible.


There are more then enough ways to keep it going. This has been address by several tools.

Personally I have some tiddy code that is 8 years old and it still is working.


Yes, and I have plenty of it which does not.


If you are looking for a faster, more concise alternative I highly recommend data.table.


perl is also very concise


Moving up to a major version (1.0) implies there could have been breaking changes if you follow semver. And including something like `unnest_legacy()` is helpful for people making the transition.

Just like `stringsAsFactors=FALSE` happened on a transition from 3.x to 4.x, because it is breaking, dplyr 1.0 had breaking changes.


Hadley is a member of the R foundation for what it's worth: https://www.r-project.org/foundation/members.html


R core and R foundation are different things: https://www.r-project.org/contributors.html




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