shinyjs
easystats
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| shinyjs | easystats | |
|---|---|---|
| 3 | 3 | |
| 722 | 1,019 | |
| - | 2.8% | |
| 4.9 | 7.8 | |
| 6 months ago | 5 days ago | |
| R | R | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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.
shinyjs
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[Shiny Dashboard] [R6] Dynamic Value boxes - having only one display.
Also, if you want to show/hide a box depending on a parameter, you can observe whether the parameter is present or not, then simply show/hide the box with the shinyjs package.
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Shiny app which Uploads a datafile and create a checkbox and textinput and dropdown list for each column
Have a look at shinyjs. https://deanattali.com/shinyjs/ https://github.com/daattali/shinyjs#overview-main There you can specify which blocks of ui are hidden from the start, you can enable and disable inputs, show and hide, and much more.
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Load Testing Shiny Apps
Shiny is an R package that makes it easy to build interactive web apps straight from R. You can host standalone apps on a webpage or embed them in R Markdown documents or build dashboards. You can also extend your Shiny apps with CSS themes, htmlwidgets, and JavaScript actions.
easystats
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My recommended R packages / functions for behavioral researchers who deal with 2X2 experiments
I'd also recommend the whole easystats suite of packages. They make model post-processing much easier. It includes a more intuitive (but more limited, imo) replacement for emmeans: modelbased.
- Most useful new packages (or package updates) from the last 3 years
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ISO a holy grail RStudio tutorial account, specifically for data analysis in psychology.
The Easystats suite, which includes several packages. It's extremely useful for Bayesian analyses, but even if you stay on the frequentist side, I recommend its performance, parameters, effectsize and correlation packages. Performance is particularly useful in conjunction to DHARMa for model diagnostic and comparison.
What are some alternatives?
RInno - How to install local shiny apps
drake - An R-focused pipeline toolkit for reproducibility and high-performance computing
shinyalert - 🗯️ Easily create pretty popup messages (modals) in Shiny
awesome-R - A curated list of awesome R packages, frameworks and software.
electricShine - Create Standalone Installable Shiny Apps
timevis - 📅 Create interactive timeline visualizations in R
shiny.semantic - Shiny support for powerful Fomantic UI library.
targets - Function-oriented Make-like declarative workflows for R
shinyloadtest - Tools for load testing Shiny applications
afex - Analysis of Factorial EXperiments (R package)
rhino - Build high quality, enterprise-grade Shiny apps at speed
waffle - :maple_leaf: Make waffle (square pie) charts in R