RCall.jl VS AlgebraOfGraphics.jl

I don't use it personally, but RCall.jl[1] is the main R interop package in Julia. You could call libraries that have no equivalent in Julia using that and write your own analyses in Julia instead.

[1] https://github.com/JuliaInterop/RCall.jl

You can have your cake and eat it with the likes of

* PythonCall.jl - https://github.com/cjdoris/PythonCall.jl

* NodeCall.jl - https://github.com/sunoru/NodeCall.j

* RCall.jl - https://github.com/JuliaInterop/RCall.jl

I tend to use Julia for most things and then just dip into another language’s ecosystem if I can’t find something to do the job and it’s too complex to build myself

To inter-operate Julia with the R language, the RCall package is used. Run the following commands on the Julia REPL

https://github.com/JuliaInterop/RCall.jl may help

If you need to bindings to your existing R packages then Julia is the way. Check out RCall.jl

I have no experience with R, but maybe this will be of use: https://github.com/JuliaInterop/RCall.jl

You can use RCall to use R from Julia: https://github.com/JuliaInterop/RCall.jl

I worked with R and Python during the last 3 years but learning and dabbling with Julia since 0.6. Since the availability of [PyCall.jl] and [RCall.jl], the transition to Julia can already be easier for Python/R users.

I agree that most of the time data wrangling is super confortable in R due to the syntax flexibility exploited by the big packages (tidyverse/data.table/etc). At the same time, Julia and R share a bigger heritage from Lisp influence that with Python, because R is also a Lisp-ish language (see [Advanced R, Metaprogramming]). My main grip from the R ecosystem is not that most of the perfomance sensitive packages are written in C/C++/Fortran but are written so deeply interconnect with the R environment that porting them to Julia that provide also an easy and good interface to C/C++/Fortran (and more see [Julia Interop] repo) seems impossible for some of them.

I also think that Julia reach to broader scientific programming public than R, where it overlaps with Python sometimes but provides the Matlab/Octave public with an better alternative. I don't expected to see all the habits from those communities merge into Julia ecosystem. On the other side, I think that Julia bigger reach will avoid to fall into the "base" vs "tidyverse" vs "something else in-between" that R is now.

[PyCall.jl]: https://github.com/JuliaPy/PyCall.jl

[RCall.jl]: https://github.com/JuliaInterop/RCall.jl

[Julia Interop]: https://github.com/JuliaInterop

[Advanced R, Metaprogramming] by Hadley Wickham: https://adv-r.hadley.nz/metaprogramming.html

This illustrates the point perfectly. Julia is attempting this and has a beachhead with Dataframes.jl. Confusingly though, Tidier.jl isn't really analogous to R's Tidyverse. It's more like one of a handful of meta-packages around Dataframes.jl.

Then there are Grammar of Graphics (ggplot was Tidyverse's first star) style plotting libraries that Julia has been building. I'm probably most excited about Algebra of Graphics (https://github.com/MakieOrg/AlgebraOfGraphics.jl/) as part of the Makie Plots ecosystem. It does still feel a bit like Julia community can't decide between following Matplotlib or R's Grid/Ggplot approach.

The seeds of a Tidyverse for Julia are there, but it'll take some time to achieve the consistency and maturity of the original Tidyverse.

Did you maybe overlook something, in https://github.com/JuliaPlots/AlgebraOfGraphics.jl or other package? I looked up "grid" and it seems to have something. I realize R, and ggplot2, were considered best by many (and Gadfly.jl similar, AoG seems to be its replacement?), but I didn't realize it had extensions (that you clarify below). At least you can call R, and thus use its plotting (and I assume its extensions too, can you confirm or deny?). For some reasons you got downvoted, so might you be ignorant of new developments in Julia (also Makie, to me it seemed excellent and I thought Julia caught up with plotting, and also had more options than other languages), or the others, or people simply very opinionated about plotting? It's about features, also speed/latency/TTFP, which is getting better.

Julia has plenty of plotting solutions that are better for stats than matplotlib:

https://github.com/JuliaPlots/AlgebraOfGraphics.jl