[amkkma]

In addition to the comment about df.jl catching up, they aren't comparable at all.

Julia's DF library is generic and allows user defined ops and types. You can put in GPU vectors, distributed vectors, custom number types etc. Julia optimizes all this stuff.

data.frame is just a giant chunk of c (c++) code that one must interact with in very specific ways

[tylermw]

> Julia's DF library is generic and allows user defined ops and types. You can put in GPU vectors, distributed vectors, custom number types etc. Julia optimizes all this stuff.

These features aren't of interest to practicing statisticians, which the parent comment was talking about.

> data.frame is just a giant chunk of c (c++) code that one must interact with in very specific ways

I don't understand this criticism: yes, data.table has an API.

[amkkma]

>These features aren't of interest to practicing statisticians, which the parent comment was talking about.

It's pretty convenient for things like uncertainty propagation and data cleaning...all things statisticians should care about.

>I don't understand this criticism: yes, data.table has an API

A relatively limited API, walled off from the rest of the language.

[StefanKarpinski]

Many practicing statisticians do actually care about easily using GPUs and doing distributed computations on distributed data sets with the same code they use for a local data set, which is what those Julia capabilities give you.