Data Science. TileDB. Open Source. Quant Research. R. C++. Debian. Linux. Adjunct Clinical Professor, University of Illinois. Lots of coffee. And some running.
New r2u demo showing easy, reliable installation of three CRAN #RStats packages onto @Ubuntu 20.04 which had otherwise frustrated a SO user. With gif :)
Answer: error in library.dynam(lib, package, package.lib) shared ovject <library_name>.so not found stackoverflow.com/a/73351708…
The CRAN Task View on High-Performance Computing has some recommendations on 'big data' with #RStats
Seehttps://CRAN.R-project.org/view=HighPerformanceComputing and/or its markdown file github.com/cran-task-views/H…
Make it a factor! #Rstats
> vec <- c("red", "blue", "red")
> table(vec)
vec
blue red
1 2
> fvec <- factor(vec, levels=c("red", "blue", "green"))
> table(fvec)
fvec
red blue green
2 1 0
>
Delete all those tweets ASAP.
You never get an academic (or industry) job using `rm(list=ls())` as all your colleagues will be terrified expecting their work to get pulverized too.
Seriously, it's a rather bad habit. Write #Rstats scripts and work in clean, fresh shells.
Neat story if you've ever listened to the phenomenal album "My Life in the Bush of Ghosts". And if you haven't yet what the heck did you do the last 40 years?
‘Better late than never’: how @brianeno and @DBtodomundo finally laid a musical ghost to rest theguardian.com/music/2022/a…
See `rticles` for journal paper templates, or my package `binb` (for beamer presentations), `linl` (latex letter), `tint` (Tufte style), and `pinp` (PNAS style paper). All follow the same setup, as do a few other packages. A bit of initial work but worth it later! #rstats
Old school:
- install into, say, /opt/R-4.2.1, /opt/R-4.1.3, /opt/R-devel and as many others as you want
- call respective version, either by adjusting $PATH or explicitly with full path
- once you 'run' that main R process, it knows its directies and libs and "just" works
Yes I enjoyed using it during the few years our campus had a it as a pilot. Small nuisances (eg new dotfiles and hence git setup for each project) but overall good. We will now pivot back to RStudio Server on our own server for all students. Likely easier, and no extra fees.
First release {r2c}, a new experimental #rstats pkg to convert* R to C for blazing fast group statistics. Lots of caveats, but pretty exciting IMO.
github.com/brodieG/r2c
* (a small but useful subset of)
1/3
There are several CRAN packages allowing Julia to be called from R (JuliaCall, JuliaConnectoR) and there papers published on them. Plus there is the (excellent, though now dated) discussion in Chambers 2016 book "Extending R". Can you dig in an provide a review? #rstats
Well we happily do 'the opposite': packages with _full and complete dependencies_ that are moreover shipped as _binaries_ so you don't even need to build. See eddelbuettel.github.io/r2u/ for @ubuntu 20.04 and 22.04, similar repos exists for Fedora and OpenSUSE. #rstats#r2u
Hey @espn here is another product idea: "data science battle royale" between base #rstats, #tidyverse, #pandas
... because friends still don't let friends use E@$el for real data work.
📢 EXCEL ESPORTS IS COMING TO @ESPN! This Friday, August 5, tune in for "Excel Esports: All-Star Battle" on #ESPN8: The Ocho.
We are beyond excited about this and hope that Excel Esports will be the most-viewed show! 😎
The show hosted by @MrExcel and @OzExcel#excel