Seamless integration with R Markdown, making it easy to embed numerous applications natively within a larger dynamic document.An attractive default look based on Bootstrap which can also be easily customized with the bslib package or avoided entirely with more direct R bindings to HTML/CSS/JavaScript.A prebuilt set of highly sophisticated, customizable, and easy-to-use widgets (e.g., plots, tables, sliders, dropdowns, date pickers, and more).

Compared to event-based programming, reactivity allows Shiny to do the minimum amount of work when input(s) change, and allows humans to more easily reason about complex MVC logic.

An intuitive and extensible reactive programming model which makes it easy to transform existing R code into a 'live app' where outputs automatically react to new user input.

To share it with the world it will need to be deployed to a server running R.Easily build rich and productive interactive web apps in R - no HTML/CSS/JavaScript required.

This tutorial runs a Shiny app on your computer. library(golem) is particularly helpful for creating modular Shiny apps. Furthermore, if you find yourself writing very large and complicated Shiny apps, then look into ‘modularizing Shiny code’. This does not change the functionality but allows to better organise your code.

It is possible to separate app.R into two separate scripts: ui.R and server.R. More about getting started with Shiny can found here: You now understand the basic skeleton - that there is a user interface (ui) and a server. STEP 5 (optional): Add animate = TRUE inside sliderInput(). You now have a fully functioning Shiny app and all you had to do was wrap your beautiful plot code inside some ()s, add a sliderInput(), and replace 2007 with input$year. Press Control+Shift+Enter or the “Run App” button. Gapminder %>% filter(year = input $year) %>% ggplot( aes(y = lifeExp, x = continent)) +.

Rstudio r shiny