[inputcoffee]

I was waiting for the critique... but I never quite saw it.

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.

[barcadad]

His critique is more about the impact of the full ecosystem effect of the Tidyverse, not what you are referring to, which is just the dplyr semantics. The Tidyverse demands that it's many related packages use tidy data principles and lock users into that approach, which differs from base-R. Much of this discussion is really just a debate about dplyr and magrittr rather than the fragmentation that the broader tidyverse has brought on. All that said, I agree with many commenters that the Tidyverse's improvements to speed of development can more than offset the speed of execution issues, at least for small-to-medium datasets.

[RosanaAnaDana]

I think any one making the point of speed of development have seriously missed the boat. Lets be real: tibbles suck. Once you get the hang of data.table syntax for matrix operations, its superiority becomes impeccably clear.

I run a data science group a large geospatial company and we develop day in and day out in R and python. We've purged tidyverse as much as possible from all of our code base. We've moved completely over to data.tables, which make the vast majority of the tidyverse irrelevant.

[hadley]

Let’s keep the discussion civil please. People have legitimately different needs, and just because a package isn’t well suited to your needs doesn’t mean that it doesn’t help people with different backgrounds and goals.