This is a simple collection of resources that I find useful. In the future, this site will feature more extensive discussions about R, stata, GitHub and python coding practices.
traceback(), debug() and browser() Demo by Kara Woo
How to structure a data science project by David Neuzerling
Organising your work in RMarkdown Original Title: First World Problems: Very long RMarkdown documents by Martin Chan
Reproducing Work in a Project:The {fertile} #Rstats package boosts reproducibility by helping detect common mistakes programmers make when performing analysis in R 📦 https://t.co/BDrS8qSXHn pic.twitter.com/Ef0lUWCLF5
— Dan Quintana (@dsquintana) September 1, 2020
Cool website of the day 🤙
— Dean Attali (@daattali) February 9, 2021
Navigate a GitHub repo as if you're in VS Code. You can even open multiple tabs add and use “markdown preview mode”
Just append “1s” to “github” in the URL. Example: https://t.co/x15Rwkg5mh pic.twitter.com/DzViIXn7Lz
This is probably one of the best intro to #Docker and #Kubernetes I've ever read:https://t.co/cnVm90fyy9 pic.twitter.com/cypTvfHGbZ
— Colin Fay 🤘 (@_ColinFay) February 9, 2021
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There's a simple rule for tables in presentations: Plan to read out every value in the table.
— Claus Wilke (@ClausWilke) February 6, 2021
“But there's so many of them, it'll take forever and bore the audience.”
Then you know what you have to do. https://t.co/ZrKjAQkeDL
Every time I see long tables full of numbers, a little piece of my love for numbers flies away.
— Julyan Arbel (@JulyanArbel) September 4, 2020
Please consider @StatModeling parallel dot plots instead!https://t.co/pQ127rOpbR
Code: https://t.co/rTu4wATYpY https://t.co/lC1LfkWtkR pic.twitter.com/eiA06BB0hH