covid_percentiles
A Shiny app displaying statistics about a user's experience. (by michaelboerman)
rhino
Build high quality, enterprise-grade Shiny apps at speed (by Appsilon)
| covid_percentiles | rhino | |
|---|---|---|
| 1 | 2 | |
| 1 | 263 | |
| - | 4.6% | |
| 2.7 | 9.3 | |
| 8 months ago | 8 days ago | |
| R | R | |
| MIT License | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
covid_percentiles
Posts with mentions or reviews of covid_percentiles.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Show HN: Covid – How did you fare?
This is a great idea, thank you. Currently there is no count of those who got covid vs entire population, but it would be interesting to know! I've added this to the upcoming feature list: https://github.com/michaelboerman/covid_percentiles/issues/7
rhino
Posts with mentions or reviews of rhino.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-04.
-
Can someone explain how R project are organized and deployed?
As for organising code within a project, as mentioned packages really don’t allow this beyond collation order. The best solution in this space is the ‘box’ package which implements a fully-featured module system for R. ‘box’ notably gets used by some folks to implement large-scale Shiny applications; if this is what you’re after, I would recommend the ‘rhino’ framework, which builds upon Siny and ‘box’.
- Rhino 1.3.0 released – RStats/Shiny framework
What are some alternatives?
When comparing covid_percentiles and rhino you can also consider the following projects:
shinyjs - 💡 Easily improve the user experience of your Shiny apps in seconds
ggplot2-book - ggplot2: elegant graphics for data analysis
box - Write reusable, composable and modular R code
timevis - 📅 Create interactive timeline visualizations in R
DesktopDeployR - A framework for deploying self-contained R-based applications to the desktop