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Similarly to shiny
, shiny.semantic
works well with other popular R packages.
Let’s see how to create a simple application with plotly
.
library(shiny)
library(shiny.semantic)
library(plotly)
ui <- semanticPage(
segment(
class = "basic",
a(class="ui green ribbon label", "Plotly demo"),
plotlyOutput("plot")
)
)
server <- function(input, output, session) {
output$plot <- renderPlotly({
plot_ly(economics, x = ~date, color = I("black")) %>%
add_lines(y = ~uempmed) %>%
add_lines(y = ~psavert, color = I("red"))
})
}
shinyApp(ui = ui, server = server)
And now let’s have a look at similar example, but with leaflet
.
library(shiny)
library(shiny.semantic)
library(leaflet)
ui <- semanticPage(
segment(
class = "basic",
a(class="ui blue ribbon label", "Leaflet demo"),
leafletOutput("map")
)
)
server <- function(input, output, session) {
output$map <- renderLeaflet({
m <- leaflet() %>% addTiles()
m <- m %>% setView(21.00, 52.21, zoom = 12)
m
})
}
shinyApp(ui = ui, server = server)
To add some neat Fomantic styling to your DT
table you need to use
semantic_DT
wrapper.
library(shiny)
library(shiny.semantic)
ui <- semanticPage(
h2("Pretty tables in Shiny Semantic"),
semantic_DTOutput("table")
)
server <- function(input, output, session) {
output$table <- DT::renderDataTable(
semantic_DT(mtcars)
)
}
shinyApp(ui, server)
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They may not be fully stable and should be used with caution. We make no claims about them.
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