[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.