#rlang
Having gotten my head fully around R pipes, I feel I need to write an article about it before I forget the fiddly details:
|>, %>%, with(), lambdas, %$%, ...
there are a lot of clever tricks for edge cases! (The with() hack I should have figured out for myself though!)
Also, %$% -- the exposition pipe -- why didn't any of you tell me about this one!?!? You're slacking!
#rlang #datascience #stats #statistics #rprogramming #tidyverse #tidydata #Rpipes #pipes!
Fresh WIP piece of #Archaea #phylogenetics data for a collaborator.
Those barplot margins are driving me crazy - it's actually throwing off the immediate impression of the data! (pink bars are essentially all 1/2 or less of the orange bars, which is pretty important in context) I really need to buckle down and get to hand-coding my trees from scratch using #rlang or #julialang soon.
Hmm. How's Julia ecosystem for phylogenetic trees these days?
Ok, why do people keep doing this:
library(tidyverse)
library(lubridate)
when the first call automatically loads the package in the second call? Am I missing something here?
I see this **everywhere**!
Hello again, R . . .
R for sure has deficits (but so does python), but for exploratory data analysis, particularly ones heavy in statistics, R can sometimes shine. I still abhore passing variables into functions, but I get why for simple EDA one might want non-standard evaluation.
R is making a comeback:
https://www.infoworld.com/article/4102696/r-language-is-making-a-comeback-tiobe.html
It is worth noting from the very beginning that a software engineer's work doesn't start with writing code, but with setting up the development environment and the tools that they need to write code effectively. Good tooling can make the difference between you writing clean, tight, maintainable code on the one hand and creating an unmaintainable abomination on the other. This entire first chapter, then, is dedicated to setting up a development environment that lets you build things in R in a consistent, reproducible and easy to fix or revert way. We'll start with basic command line skills, move on to version control and then finally discuss containerisation and the setting up of a development container for your project.
Heya R devs - did you know you can run all your favorite GitHub actions on Codeberg?
Codeberg is rolling out Forgejo actions - an (almost) drop-in replacement for GitHub actions, which means we can (almost) use `r-lib/actions` directly on a free and open source platform!
Just a couple tweaks are needed, and for your convenience I'm automatically mirroring r-lib/actions and applying those changes so they're ready to use.