S7
Tidier.jl
| S7 | Tidier.jl | |
|---|---|---|
| 6 | 5 | |
| 436 | 556 | |
| 1.8% | 2.0% | |
| 9.3 | 6.2 | |
| 4 months ago | 4 days ago | |
| R | Julia | |
| GNU General Public License v3.0 or later | MIT License |
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.
S7
- Will they get it right this time?
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Tidyverse 2.0.0
https://adv-r.hadley.nz/oo.html
"There are multiple OOP systems to choose from. In this book, I’ll focus on the three that I believe are most important: S3, R6, and S4. S3 and S4 are provided by base R. R6 is provided by the R6 package, and is similar to the Reference Classes, or RC for short, from base R.
"There is disagreement about the relative importance of the OOP systems. I think S3 is most important, followed by R6, then S4. Others believe that S4 is most important, followed by RC, and that S3 should be avoided. This means that different R communities use different systems."
https://rconsortium.github.io/OOP-WG/
"The S7 package is a new OOP system designed to be a successor to S3 and S4."
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Is python necessary to learn machine learning?
Even if RStudio & the Tidyverse have mostly been promoting a functional programming style in R, it has full support for OOP (see R6 or R7 for more modern implementations of it). Let's not even mention the excellent Stan ecosystem for Probabilistic programming / Bayesian modeling, or Bioconductor, the biggest repository of bioinformatics packages & tools of any language.
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Why is OOP in R so messy?
Not sure if you or others have missed it, as the link from the readme is dead, but the proposal section of that repo is informative of the current state of things: https://github.com/RConsortium/OOP-WG/blob/master/proposal/proposal.org
Tidier.jl
- Tidier.jl: Meta-package for data analysis in Julia, modeled after R tidyverse
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Julia 1.10 Released
btw, there has been a pretty nice effort of reimplementing the tidyverse in julia with https://github.com/TidierOrg/Tidier.jl and it seems to be quite nice to work with, if you were missing that from R at least
- Pandas vs. Julia – cheat sheet and comparison
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Tidyverse 2.0.0
“Tidier.jl is a 100% Julia implementation of the R tidyverse mini-language in Julia.”
https://github.com/TidierOrg/Tidier.jl
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What's Julia's biggest weakness?
A recent package, Tidier.jl, is coming from a R package developer: https://github.com/kdpsingh/Tidier.jl
What are some alternatives?
py-shiny - Shiny for Python
Julia-DataFrames-Tutorial - A tutorial on Julia DataFrames package
AlgebraOfGraphics.jl - An algebraic spin on grammar-of-graphics data visualization in Julia. Powered by the Makie.jl plotting ecosystem.
DataFramesMeta.jl - Metaprogramming tools for DataFrames
stan - Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
tidytable - Tidy interface to 'data.table'