trackdown
drake
| trackdown | drake | |
|---|---|---|
| 2 | 1 | |
| 210 | 1,330 | |
| - | 0.1% | |
| 4.8 | 6.1 | |
| 11 months ago | 2 months ago | |
| HTML | R | |
| GNU General Public License v3.0 only | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
trackdown
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Any place to do collaboratie writing in the new quarto format? if not, what's the best place/way to do it in rmarkdown you think?
Perhaps the trackdown package: https://github.com/claudiozandonella/trackdown
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RMarkdown and collaborating with Word
https://github.com/ClaudioZandonella/trackdown https://www.gerkelab.com/blog/2021/04/netlifycms-rmd-ghpages/ https://jksserver.shinyapps.io/shiny_markdown_organiser/ https://danovando.github.io/publications-with-rmarkdown/presentations/pubs-with-rmarkdown#46 https://info201.github.io/git-collaboration.html https://www.youtube.com/watch?v=hXhLGzn6S60
drake
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Your impression of {targets}? (r package)
The targets package is the official successor to Drake, and has the same primary author (Will Landau). He has explained why he created targets, which includes stronger guardrails for users and better UX.
What are some alternatives?
qcoder - Lightweight package to do qualitative coding
targets - Function-oriented Make-like declarative workflows for R
surveydown - An attempt to build a markdown-based survey platform using Quarto & Shiny
easystats - :milky_way: The R easystats-project
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
tabulapdf - Bindings for Tabula PDF Table Extractor Library
ncaahoopR - An R package for working with NCAA Basketball Play-by-Play Data
drat - Drat R Archive Template
fiery - A flexible and lightweight web server
targets-tutorial - Short course on the targets R package
causalglm - Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning