Data Science. TileDB. Open Source. Quant Research. R. C++. Debian. Linux. Adjunct Clinical Professor, University of Illinois. Lots of coffee. And some running.
If you'd like to colorize #Rstats terminal output you can use {jalvesaq/colorout}
I customize extra color patterns for
- base R: class for `str`
- #RDatatable row id & column class
- #mlr3 R6 field name
I share codes for .Rprofile. See image & link
gist.github.com/kar9222/0e11…
Release 1.0.4 is now both in CRAN's incoming.
And, as processing times remain unpredictable, also in the Rcpp drat repo at rcppcore.github.io/drat/ from where you can install it now (from source) via
install.packages("Rcpp", repos="rcppcore.github.io/drat ")
#rstats#rcpp
My hobby (though @eddelbuettel did all the hard work)
You can use this to embed R inside just about anything, including Stata
Or Octave, Matlab, Fortran, probably even GAUSS if you still use that
Another really nice post.
If you care about fast _and_ correct computing in C++ (and other relevant languages) but don't follow Daniel -- well, then you're doing it wrong ...
We are pleased to announce that the useR! 2021conference will take place in Zurich, Switzerland on 6-9 July 2021. Follow @useR2021zrh for news and updates.
user2021.r-project.org/
Nearly fifteen years worth command-line tools for R are in `inst/examples/` of the `littler` repo.
I use several of them daily, and prefer installing, compiling, testing, rendering, ... away from other (longer-runnng) R sessions increases reliability.
github.com/eddelbuettel/litt…
Rcpp release candidate 1.0.3.8 at Rcpp drat
If you can, please help test prior to the 1.0.4 release.
Details in a post on the rcpp-devel list
lists.r-forge.r-project.org/…#rcpp#rstats
Finally able to catch up to this, and it is fantastic.
Kudos to @stanleynelson1 for an excellent retrospective on @MilesDavis who changed so much in music, and so often.
Streams at pbs.org/video/miles-davis-bi… if you're in the right region (i.e. could not see it in DK last week).
Yes! Related tips:
- use wrappers that encode `Ncpus`, all `littler` ones do
- blog posts about this as even faster than parallel installs are installs that
- use `ccache`
- use binaries instead
- build once, eg in Docker, and reuse
are below dirk.eddelbuettel.com/blog/c…
Quick #rstats Tip: Use `Ncpus` when installing packages
🔹install.packages() has an Ncpus argument determining how many parallel processes to use
🔹This can e.g. speed up installation of {{tidyverse}} from ~11min to ~4.6min
🔹Also works with remotes & devtools install_ functions