I would like Shiny to print out some different color text depending on the size of a vector. I was thinking something like:
output$some_text <- renderText({
if(length(some_vec) < 20){
paste("This is red text")
<somehow make it red>
}else{
paste("This is blue text")
<somehow make it blue>
...but then I realized, I'm doing this in the server, not the UI.
And, as far as I know, I can't move this conditional logic into the UI.
For example, something like this won't work in the UI:
if(length(some_vec)< 20){
column(6, tags$div(
HTML(paste("This text is ", tags$span(style="color:red", "red"), sep = ""))
)}
else{
tags$div(HTML(paste("This text is ", tags$span(style="color:blue", "blue"), sep = ""))
)}
Does anyone have any creative ideas?
Inspired by jenesaisquoi's answer I tried the following and it worked for me. It is reactive and requires no additional packages. In particular look at output$text3
library(shiny)
ui <- shinyUI(fluidPage(
titlePanel("Reactive"),
sidebarLayout(
sidebarPanel(
helpText("Variables!"),
selectInput("var",
label = "Choose Variable",
choices = c("red", "blue",
"green", "black"),
selected = "Rojo"),
sliderInput("range",
label = "Range:",
min = 0, max = 100, value = c(0, 100))
),
mainPanel(
textOutput("text1"),
textOutput("text2"),
htmlOutput("text3"),
textOutput("text4")
)
)
))
server <- function(input, output) {
output$text1 <- renderText({
paste("You have selected variable:", input$var)
})
output$text2 <- renderText({
paste("You have selected range:", paste(input$range, collapse = "-"))
})
output$text3 <- renderText({
paste('<span style=\"color:', input$var,
'\">This is "', input$var,
'" written ', input$range[2],
' - ', input$range[1],
' = ', input$range[2] - input$range[1],
' times</span>', sep = "")
})
output$text4 <- renderText({
rep(input$var, input$range[2] - input$range[1])
})
}
# Run the application
shinyApp(ui = ui, server = server)
Came hunting for an answer to a similar question. Tried a simple approach that worked for my need. It uses inline html style, and htmlOutput.
library(shiny)
ui <- fluidPage(
mainPanel(
htmlOutput("some_text")
)
)
and
server <- function(input, output) {
output$some_text <- renderText({
if(length(some_vec) < 20){
return(paste("<span style=\"color:red\">This is red text</span>"))
}else{
return(paste("<span style=\"color:blue\">This is blue text</span>"))
}
})
}
Conditionals run server side--it wasn't precisely clear to me from opening question that the author needed the conditional to run in UI. I didn't. Perhaps a simple way to address the issue in common situations.
Well, I have the kernel of an idea, but I'm fairly new to anything HTML/CSS/JavaScript-related, so I'm sure it could be improved quite a bit. That said, this seems to work fairly well, as far as it goes.
The key functions are removeClass() and addClass(), which are well documented in their respective help files in shinyjs:
library(shiny)
library(shinyjs)
shinyApp(
ui = fluidPage(
useShinyjs(), ## Set up shinyjs
## Add CSS instructions for three color classes
inlineCSS(list(.red = "color: red",
.green = "color: green",
.blue = "color: blue")),
numericInput("nn", "Enter a number",
value=1, min=1, max=10, step=1),
"The number is: ", span(id = "element", textOutput("nn", inline=TRUE))
),
server = function(input, output) {
output$nn <- renderText(input$nn)
observeEvent(input$nn, {
nn <- input$nn
if(is.numeric(as.numeric(nn)) & !is.na(as.numeric(nn))) {
## Clean up any previously added color classes
removeClass("element", "red")
removeClass("element", "green")
removeClass("element", "blue")
## Add the appropriate class
cols <- c("blue", "green", "red")
col <- cols[cut(nn, breaks=c(-Inf,3.5, 6.5, Inf))]
addClass("element", col)
} else {}
})
})
It sounds like you are trying to keep it all on the client side, so you could just use a couple of conditionalPanels, which accept javascript as conditional code. For example, coloring the text in response to the current value in a numericInput box with id "len",
library(shiny)
ui <- shinyUI(
fluidPage(
fluidRow(
numericInput('len', "Length", value=19),
conditionalPanel(
condition = "$('#len').val() > 20",
div(style="color:red", "This is red!")),
conditionalPanel(
condition = "$('#len').val() <= 20",
div(style="color:blue", "This is blue!"))
)
)
)
server <- function(input, output, session) {}
shinyApp(ui = ui, server=server)
You could also add an event listener to update the text with javascript. It's kinda ugly inline (and I don't know much javascript), but you could just move the script to a file in wwww/ and use includeScript. As in the previous example, the server does nothing.
ui <- shinyUI(bootstrapPage(
numericInput('len', "Length", value=19),
div(id="divvy", style="color:blue", "This is blue!"),
tags$script(HTML("
var target = $('#len')[0];
target.addEventListener('change', function() {
var color = target.value > 20 ? 'red' : 'blue';
var divvy = document.getElementById('divvy');
divvy.style.color = color;
divvy.innerHTML = divvy.innerHTML.replace(/red|blue/g, color);
});
"))
))
Here's a more flexible answer that uses shinyjs::extendShinyjs() to give R a way to produce some parameterized JavaScript code. Compared to my other answer, the advantage of this one is that the same function can be used to reactively colorize multiple numeric outputs.
library(shiny)
library(shinyjs)
jsCode <-
"shinyjs.setCol = function(params){
var defaultParams = {
id: null,
color : 'red'
};
params = shinyjs.getParams(params, defaultParams);
$('.shiny-text-output#' + params.id).css('color', params.color);
}"
setColor <- function(id, val) {
if(is.numeric(as.numeric(val)) & !is.na(as.numeric(val))) {
cols <- c("green", "orange", "red")
col <- cols[cut(val, breaks=c(-Inf,3.5, 6.5, Inf))]
js$setCol(id, col)
}
}
shinyApp(
ui = fluidPage(
useShinyjs(), ## Set up shinyjs
extendShinyjs(text = jsCode),
numericInput("n", "Enter a number", 1, 1, 10, 1),
"The number is: ", textOutput("n", inline=TRUE),
br(),
"Twice the number is: ", textOutput("n2", inline=TRUE)
),
server = function(input, output) {
output$n <- renderText(input$n)
output$n2 <- renderText(2 * input$n)
observeEvent(input$n, setColor(id = "n", val = input$n))
observeEvent(input$n, setColor(id = "n2", val = 2 * input$n))
})
Related
I want to make an app with 2 actionButtons: 1) to submit the changes before loading a selectizeInput and 2) to draw the plot.
I know how to add a spinner after clicking a actionButton but the majority of the cases is added when you want to show the plot.
However, is it possible to add a spinner without showing any plot?
In this particular case, I want to show a spinner after clicking "Submit" until the selectizeInput from the 'Selection tab' is loaded. As you can see the example that I attach, it takes a bit to load all the choices (since the file has 25000 rows).
I already have one spinner after clicking the second actionButton (Show the plot) but I need one more.
I have created an example, but for some reason the plot is not shown in the shiny app and it appears in the window from R (I don't know why but I added the plot just to show you how I put the second spinner. I want a similar one but with the first actionButton.).
library(shiny)
library(shinycssloaders)
ui <- fluidPage(
titlePanel("My app"),
sidebarLayout(
sidebarPanel(
tabsetPanel(
tabPanel("Submit",
checkboxInput("log2", "Log2 transformation", value = FALSE),
actionButton("submit", "Submit")
),
tabPanel("Selection",
br(),
selectizeInput(inputId = "numbers", label = "Choose one number:", choices=character(0)),
actionButton("show_plot", "Show the plot")
))
),
mainPanel(
conditionalPanel(
condition = "input.show_plot > 0",
style = "display: none;",
withSpinner( plotOutput("hist"),
type = 5, color = "#0dc5c1", size = 1))
)
)
)
server <- function(input, output, session) {
data <- reactive({
data = read.csv("https://people.sc.fsu.edu/~jburkardt/data/csv/hw_25000.csv")
data[,1] <- as.character(data[,1])
if(input$log2 == TRUE){
cols <- sapply(data, is.numeric)
data[cols] <- lapply(data[cols], function(x) log2(x+1))
}
return(data)
})
mylist <- reactive({
req(data())
data <- data()
data <- data[,1]
return(data)
})
# This is to generate the choices (gene list) depending on the user's input.
observeEvent(input$submit, {
updateSelectizeInput(
session = session,
inputId = "numbers",
choices = mylist(), options=list(maxOptions = length(mylist()))
)
})
v <- reactiveValues()
observeEvent(input$show_plot, {
data <- data()
v$plot <- plot(x=data[,1], y=data[,2])
})
# If the user didn't choose to see the plot, it won't appear.
output$hist <- renderPlot({
req(data())
if (is.null(v$plot)) return()
if(input$show_plot > 0){
v$plot
}
})
}
Does anyone know how to help me, please?
Thanks very much
It's a little tricky.
First of all I'd update the selectizeInput on the server side as the warning suggests:
Warning: The select input "numbers" contains a large number of
options; consider using server-side selectize for massively improved
performance. See the Details section of the ?selectizeInput help
topic.
Furthermore I switched to ggplot2 regarding the plotOutput - Please see this related post.
To show the spinner while the selectizeInput is updating choices we'll need to know how long the update takes. This information can be gathered via shiny's JS events - please also see this article.
Finally, we can show the spinner for a non-existent output, so we are able to control for how long the spinner is shown (see uiOutput("dummyid")):
library(shiny)
library(shinycssloaders)
library(ggplot2)
ui <- fluidPage(
titlePanel("My app"),
tags$script(HTML(
"
$(document).on('shiny:inputchanged', function(event) {
if (event.target.id === 'numbers') {
Shiny.setInputValue('selectizeupdate', true, {priority: 'event'});
}
});
$(document).on('shiny:updateinput', function(event) {
if (event.target.id === 'numbers') {
Shiny.setInputValue('selectizeupdate', false, {priority: 'event'});
}
});
"
)),
sidebarLayout(
sidebarPanel(
tabsetPanel(
tabPanel("Submit",
checkboxInput("log2", "Log2 transformation", value = FALSE),
actionButton("submit", "Submit")
),
tabPanel("Selection",
br(),
selectizeInput(inputId = "numbers", label = "Choose one number:", choices=NULL),
actionButton("show_plot", "Show the plot")
))
),
mainPanel(
uiOutput("plotProxy")
)
)
)
server <- function(input, output, session) {
previousEvent <- reactiveVal(FALSE)
choicesReady <- reactiveVal(FALSE)
submittingData <- reactiveVal(FALSE)
observeEvent(input$selectizeupdate, {
if(previousEvent() && input$selectizeupdate){
choicesReady(TRUE)
submittingData(FALSE)
} else {
choicesReady(FALSE)
}
previousEvent(input$selectizeupdate)
})
data <- reactive({
data = read.csv("https://people.sc.fsu.edu/~jburkardt/data/csv/hw_25000.csv")
if(input$log2 == TRUE){
cols <- sapply(data, is.numeric)
data[cols] <- lapply(data[cols], function(x) log2(x+1))
}
return(data)
})
mylist <- reactive({
req(data()[,1])
})
observeEvent(input$submit, {
submittingData(TRUE)
reactivePlotObject(NULL) # reset
updateSelectizeInput(
session = session,
inputId = "numbers",
choices = mylist(), options=list(maxOptions = length(mylist())),
server = TRUE
)
})
reactivePlotObject <- reactiveVal(NULL)
observeEvent(input$show_plot, {
reactivePlotObject(ggplot(data(), aes_string(x = names(data())[1], y = names(data())[2])) + geom_point())
})
output$hist <- renderPlot({
reactivePlotObject()
})
output$plotProxy <- renderUI({
if(submittingData() && !choicesReady()){
withSpinner(uiOutput("dummyid"), type = 5, color = "#0dc5c1", size = 1)
} else {
conditionalPanel(condition = "input.show_plot > 0", withSpinner(plotOutput("hist"), type = 5, color = "#0dc5c1", size = 1), style = "display: none;")
}
})
}
shinyApp(ui, server)
First 100 rows of your example data (dput(head(data, 100)) - your link might be offline some day):
structure(list(Index = 1:100, Height.Inches. = c(65.78331, 71.51521,
69.39874, 68.2166, 67.78781, 68.69784, 69.80204, 70.01472, 67.90265,
66.78236, 66.48769, 67.62333, 68.30248, 67.11656, 68.27967, 71.0916,
66.461, 68.64927, 71.23033, 67.13118, 67.83379, 68.87881, 63.48115,
68.42187, 67.62804, 67.20864, 70.84235, 67.49434, 66.53401, 65.44098,
69.5233, 65.8132, 67.8163, 70.59505, 71.80484, 69.20613, 66.80368,
67.65893, 67.80701, 64.04535, 68.57463, 65.18357, 69.65814, 67.96731,
65.98088, 68.67249, 66.88088, 67.69868, 69.82117, 69.08817, 69.91479,
67.33182, 70.26939, 69.10344, 65.38356, 70.18447, 70.40617, 66.54376,
66.36418, 67.537, 66.50418, 68.99958, 68.30355, 67.01255, 70.80592,
68.21951, 69.05914, 67.73103, 67.21568, 67.36763, 65.27033, 70.84278,
69.92442, 64.28508, 68.2452, 66.35708, 68.36275, 65.4769, 69.71947,
67.72554, 68.63941, 66.78405, 70.05147, 66.27848, 69.20198, 69.13481,
67.36436, 70.09297, 70.1766, 68.22556, 68.12932, 70.24256, 71.48752,
69.20477, 70.06306, 70.55703, 66.28644, 63.42577, 66.76711, 68.88741
), Weight.Pounds. = c(112.9925, 136.4873, 153.0269, 142.3354,
144.2971, 123.3024, 141.4947, 136.4623, 112.3723, 120.6672, 127.4516,
114.143, 125.6107, 122.4618, 116.0866, 139.9975, 129.5023, 142.9733,
137.9025, 124.0449, 141.2807, 143.5392, 97.90191, 129.5027, 141.8501,
129.7244, 142.4235, 131.5502, 108.3324, 113.8922, 103.3016, 120.7536,
125.7886, 136.2225, 140.1015, 128.7487, 141.7994, 121.2319, 131.3478,
106.7115, 124.3598, 124.8591, 139.6711, 137.3696, 106.4499, 128.7639,
145.6837, 116.819, 143.6215, 134.9325, 147.0219, 126.3285, 125.4839,
115.7084, 123.4892, 147.8926, 155.8987, 128.0742, 119.3701, 133.8148,
128.7325, 137.5453, 129.7604, 128.824, 135.3165, 109.6113, 142.4684,
132.749, 103.5275, 124.7299, 129.3137, 134.0175, 140.3969, 102.8351,
128.5214, 120.2991, 138.6036, 132.9574, 115.6233, 122.524, 134.6254,
121.8986, 155.3767, 128.9418, 129.1013, 139.4733, 140.8901, 131.5916,
121.1232, 131.5127, 136.5479, 141.4896, 140.6104, 112.1413, 133.457,
131.8001, 120.0285, 123.0972, 128.1432, 115.4759)), row.names = c(NA,
100L), class = "data.frame")
I need a reactive variable (declared server-side) available after start-up. Using what I learned here How to create a conditional renderUI in Shiny dashboard I tried wrapping in reactive() before defining the UI but no luck. Moving topValuesSelector to the UI inside a conditionalPanel would work except conditional panels apparently do not like the %in% operator (a separate issue that I also tried to resolve w/o success).
if (interactive()) {
library(shiny)
library(shinydashboard)
library(shinydashboardPlus)
ui <-
dashboardPage(header = dashboardHeaderPlus(left_menu = tagList(
dropdownBlock(
id = "prefDropdown",
title = "Preferences",
icon = NULL,
badgeStatus = NULL,
checkboxGroupInput(
inputId = "prefDropdown",
label = NULL,
choices = c("Pareto",
"Legend on chart",
"Cases/1K uniques",
"Top 10 only"),
selected = c("Pareto", "Cases/1K uniques", "Top 10 only")
),
uiOutput("topValues")
)
)),
dashboardSidebar(),
dashboardBody(fluidRow(box(
title = "Top",
textOutput("topN")
))))
server <- function(input, output) {
topValuesSelector <- reactive({
if ("Top 10 only" %in% input$prefDropdown) {
numericInput(
inputId = "topValues",
label = NULL,
width = "25%",
value = 10,
min = 1,
max = 30,
step = 1
)
}
})
output$topValues <- renderUI({
topValuesSelector()
})
observe({
if ("Top 10 only" %in% input$prefDropdown) {
output$topN <- renderText(input$topValues)
} else{
output$topN <- renderText(100)
}
})
}
shinyApp(ui, server)
}
The intent is for the initial value of "topValues" to be 10 with this value immediately available. However, no value is available which causes an error. Using req() avoids the error by pausing execution but that is not a viable approach because "topValues" is needed for a plot. So no plot until selecting "prefDropdown".
It looks like the problem is that input$topValues does not exist until you click on the Preferences button. Since the UI element isn't needed it hasn't been created yet.
In order to work around that you can create a variable that detects whether or not the input is available and if not use a default value.
if (interactive()) {
library(shiny)
library(shinydashboard)
library(shinydashboardPlus)
ui <-
dashboardPage(header = dashboardHeaderPlus(left_menu = tagList(
dropdownBlock(
id = "prefDropdown",
title = "Preferences",
icon = NULL,
badgeStatus = NULL,
checkboxGroupInput(
inputId = "prefDropdown",
label = NULL,
choices = c("Pareto",
"Legend on chart",
"Cases/1K uniques",
"Top 10 only"),
selected = c("Pareto", "Cases/1K uniques", "Top 10 only")
),
uiOutput("topValues")
)
)),
dashboardSidebar(),
dashboardBody(fluidRow(box(
title = "Top",
textOutput("topN")
))))
server <- function(input, output) {
## We want to use the same default value in two places so create a var
default_value <- 10
topValuesSelector <- reactive({
if ("Top 10 only" %in% input$prefDropdown) {
numericInput(
inputId = "topValues",
label = NULL,
width = "25%",
value = default_value, ## Change to use the default value
min = 1,
max = 30,
step = 1
)
}
})
output$topValues <- renderUI({
topValuesSelector()
})
## Create a variable that is the default value unless the input is available
myTopN <- reactive({
if(length(input$topValues)>0){
return(input$topValues)
}
return(default_value)
})
observe({
if ("Top 10 only" %in% input$prefDropdown) {
# output$topN <- renderText(input$topValues)
output$topN <- renderText(myTopN()) ## Use our new variable instead of the input directly
} else{
output$topN <- renderText(100)
}
})
}
shinyApp(ui, server)
}
There are a couple of other things going on with your code. Notice that "Top 10 only" %in% input$prefDropdown will not do what you think it is doing. You have to check to see if "Top 10 only" is TRUE... I'll leave you there to start another question if you get stuck again.
ran into this weird issue when teaching a student about shiny programming.
What i wanted was to make code that deletes the verbatimtextOuput element, rather than print an empty value
This is the code he wrote, but it deletes all buttons, the whole UI basically. Can this be done? I know more complex options like conditional panels etc, but just trying to figure out why removeUI doesn't do what I expected here.
Thanks!
app:
library(shiny)
ui<-fluidPage( h5("Hello there"), #First text on the window
br(), #empty line
actionButton(inputId = "ClickonMe", label = "Make data"), # button 1
actionButton(inputId = "ClickonMe2", label = "Print data"), # button 2
actionButton(inputId = "ClickonMe3", label = "Transform data"),
verbatimTextOutput("Response_text") #reactive text output )
server <- function(input,output) {
values <- reactiveValues()
observeEvent(input$ClickonMe,
values$name <- TRUE )
observeEvent(input$ClickonMe3,
if (values$name == TRUE) { values$name <- FALSE}
else { values$name <- TRUE} )
observeEvent(input$ClickonMe2,
if (values$name == TRUE) { output$Response_text <- renderPrint( isolate({values$name}) ) }
else if (values$name == FALSE) { removeUI(
selector = "div:has(> #Response_text)"
)
}
) }
shinyApp(ui, server)
EDIT VERSION:
changed pork chops answer a little so that this version removes and remakes the verbatim element in the ui.
What i now try to fully understand is, is why the piece req(....) has such an impact. the print(values$name) proofs that the variable exist, and the observer sees it, yet if you # the req( ) line, suddenly the app stops recreating the verbatimtextouput after it has been removed the first time.
Hope I can learn why this is the case. Thank you!
library(shiny)
ui <- fluidPage(
h5("Hello there"), # First text on the window
br(), # empty line
actionButton(inputId = "ClickonMe", label = "Make data"), # button 1
actionButton(inputId = "ClickonMe2", label = "Print data"), # button 2
actionButton(inputId = "ClickonMe3", label = "Transform data"),
mainPanel(verbatimTextOutput("Response_text"))
)
server <- function(input,output,session) {
values <- reactiveValues()
values$name <- T
observeEvent(input$ClickonMe,{
values$name <- T
})
observeEvent(input$ClickonMe3,{
if (values$name){ values$name <- F}
else{ values$name <- T }
})
observeEvent(input$ClickonMe2,{
print(values$name)
output$Response_text <- renderPrint({ isolate({
req(values$name)
if(!values$name){
removeUI(
selector = "div:has(> #Response_text)"
)
}else {
as.character(values$name)}
})
})
})
}
1) First of all please have a look at the Google's R Style Guide when writing code and try to stick to it I think both you and your students will benefit from it.
2) Use curly braces too when using functions such as observeEvent and renderPrint
3) Familiarise yourself with req function which is very handy
Sample Code how to remove UI:
library(shiny)
ui <- fluidPage(
h5("Hello there"), # First text on the window
br(), # empty line
actionButton(inputId = "ClickonMe", label = "Make data"), # button 1
actionButton(inputId = "ClickonMe2", label = "Print data"), # button 2
actionButton(inputId = "ClickonMe3", label = "Transform data"),
mainPanel(verbatimTextOutput("Response_text"))
)
server <- function(input,output,session) {
values <- reactiveValues()
values$name <- NULL
observeEvent(input$ClickonMe,{
values$name <- T
})
observeEvent(input$ClickonMe3,{
if (values$name){
values$name <- F}
else{
values$name <- T
}
})
observeEvent(input$ClickonMe2,{
if (values$name){
values$name <- F
}
else{
values$name <- T
}
})
output$Response_text <- renderPrint({
req(values$name)
if(!values$name){
removeUI(
selector = "div:has(> #Response_text)"
)
}
as.character(values$name)})
}
shinyApp(ui, server)
I want to place a help text for check-box label as a tooltip.
In the following example I use the shinyBS package - but I only get it to work for the title of the checkbox input group.
Any ideas how it could work after the "Lernerfolg" or "Enthusiasmus" labels?
library(shiny)
library(shinyBS)
server <- function(input, output) {
output$distPlot <- renderPlot({
hist(rnorm(input$obs), col = 'darkgray', border = 'white')
output$rendered <- renderUI({
checkboxGroupInput("qualdim", tags$span("Auswahl der Qualitätsdimension",
tipify(bsButton("pB2", "?", style = "inverse", size = "extra-small"),
"Here, I can place some help")),
c("Lernerfolg" = "Lernerfolg" ,
"Enthusiasmus" = "Enthusiasmus"
),
selected = c("Lernerfolg"))
})
})
}
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
sliderInput("obs", "Number of observations:", min = 10, max = 500, value = 100),
uiOutput("rendered")
),
mainPanel(plotOutput("distPlot"))
)
)
shinyApp(ui = ui, server = server)
Sadly, this is one of these moments, where shiny hides most of the construction, which makes it hard to get what you want into the right places.
But like most of the time, some JavaScript will do the trick. I wrote you a function that inserts the bsButton in the right place and calls a shinyBS function to insert the tooltip. (I mainly reconstructed what tipify and bdButton would have done.) With the function you can modifify your tooltip easily without further knowledge about JavaScript.
If you'd like to know more of the details, just ask in comments.
Note: When you refer to the checkbox, use the value of it (the value that is sent to input$qualdim)
library(shiny)
library(shinyBS)
server <- function(input, output) {
makeCheckboxTooltip <- function(checkboxValue, buttonLabel, Tooltip){
script <- tags$script(HTML(paste0("
$(document).ready(function() {
var inputElements = document.getElementsByTagName('input');
for(var i = 0; i < inputElements.length; i++){
var input = inputElements[i];
if(input.getAttribute('value') == '", checkboxValue, "'){
var buttonID = 'button_' + Math.floor(Math.random()*1000);
var button = document.createElement('button');
button.setAttribute('id', buttonID);
button.setAttribute('type', 'button');
button.setAttribute('class', 'btn action-button btn-inverse btn-xs');
button.appendChild(document.createTextNode('", buttonLabel, "'));
input.parentElement.parentElement.appendChild(button);
shinyBS.addTooltip(buttonID, \"tooltip\", {\"placement\": \"bottom\", \"trigger\": \"hover\", \"title\": \"", Tooltip, "\"})
};
}
});
")))
htmltools::attachDependencies(script, shinyBS:::shinyBSDep)
}
output$distPlot <- renderPlot({
hist(rnorm(input$obs), col = 'darkgray', border = 'white')
output$rendered <- renderUI({
list(
checkboxGroupInput("qualdim", tags$span("Auswahl der Qualitätsdimension",
tipify(bsButton("pB2", "?", style = "inverse", size = "extra-small"), "Here, I can place some help")),
choices = c("Lernerfolg" = "Lernerfolg", "Enthusiasmus" = "Enthusiasmus"),
selected = c("Lernerfolg")),
makeCheckboxTooltip(checkboxValue = "Lernerfolg", buttonLabel = "?", Tooltip = "Look! I can produce a tooltip!")
)
})
})
}
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
sliderInput("obs", "Number of observations:", min = 10, max = 500, value = 100),
uiOutput("rendered")
),
mainPanel(plotOutput("distPlot"))
)
)
shinyApp(ui = ui, server = server)
Edit:
Added the ShinyBS Dependencies such that the JavaScript API for shinyBS is loaded into the WebSite. Before, this was (more or less accidentally) happening because of the other call to bsButton.
Edit Nr.2: Much more In-Shiny
So this JavaScript thing is quite nice, but is kinda prone to errors and demands the developer to have some additional language skills.
Here, I present another answer, inspired by #CharlFrancoisMarais , that works only from within R and makes things more integrated than before.
Main things are: An extension function to the checkboxGrouInput that allows for adding any element to each of the Checkbox elements. There, one can freely place the bsButton and tooltips, like you would in normal markup, with all function arguments supported.
Second, an extension to the bsButton to place it right. This is more of a custom thing only for #CharlFrancoisMarais request.
I'd suggest you read the Shiny-element manipulation carefully, because this offers so much customization on R level. I'm kinda exited.
Full Code below:
library(shiny)
library(shinyBS)
extendedCheckboxGroup <- function(..., extensions = list()) {
cbg <- checkboxGroupInput(...)
nExtensions <- length(extensions)
nChoices <- length(cbg$children[[2]]$children[[1]])
if (nExtensions > 0 && nChoices > 0) {
lapply(1:min(nExtensions, nChoices), function(i) {
# For each Extension, add the element as a child (to one of the checkboxes)
cbg$children[[2]]$children[[1]][[i]]$children[[2]] <<- extensions[[i]]
})
}
cbg
}
bsButtonRight <- function(...) {
btn <- bsButton(...)
# Directly inject the style into the shiny element.
btn$attribs$style <- "float: right;"
btn
}
server <- function(input, output) {
output$distPlot <- renderPlot({
hist(rnorm(input$obs), col = 'darkgray', border = 'white')
output$rendered <- renderUI({
extendedCheckboxGroup("qualdim", label = "Checkbox", choiceNames = c("cb1", "cb2"), choiceValues = c("check1", "check2"), selected = c("check2"),
extensions = list(
tipify(bsButtonRight("pB1", "?", style = "inverse", size = "extra-small"),
"Here, I can place some help"),
tipify(bsButtonRight("pB2", "?", style = "inverse", size = "extra-small"),
"Here, I can place some other help")
))
})
})
}
ui <- fluidPage(
shinyjs::useShinyjs(),
tags$head(HTML("<script type='text/javascript' src='sbs/shinyBS.js'></script>")),
# useShinyBS
sidebarLayout(
sidebarPanel(
sliderInput("obs", "Number of observations:", min = 10, max = 500, value = 100),
uiOutput("rendered")
),
mainPanel(plotOutput("distPlot"))
)
)
shinyApp(ui = ui, server = server)
Here is slight change - to add tooltips only to the checkboxes.
library(shiny)
library(shinyBS)
server <- function(input, output) {
makeCheckboxTooltip <- function(checkboxValue, buttonLabel, buttonId, Tooltip){
tags$script(HTML(paste0("
$(document).ready(function() {
var inputElements = document.getElementsByTagName('input');
for(var i = 0; i < inputElements.length; i++) {
var input = inputElements[i];
if(input.getAttribute('value') == '", checkboxValue, "' && input.getAttribute('value') != 'null') {
var button = document.createElement('button');
button.setAttribute('id', '", buttonId, "');
button.setAttribute('type', 'button');
button.setAttribute('class', 'btn action-button btn-inverse btn-xs');
button.style.float = 'right';
button.appendChild(document.createTextNode('", buttonLabel, "'));
input.parentElement.parentElement.appendChild(button);
shinyBS.addTooltip('", buttonId, "', \"tooltip\", {\"placement\": \"right\", \"trigger\": \"click\", \"title\": \"", Tooltip, "\"})
};
}
});
")))
}
output$distPlot <- renderPlot({
hist(rnorm(input$obs), col = 'darkgray', border = 'white')
output$rendered <- renderUI({
checkboxGroupInput("qualdim",
label = "Checkbox",
choiceNames = c("cb1", "cb2"),
choiceValues = c("check1", "check2"),
selected = c("check2"))
})
output$tooltips <- renderUI({
list(
makeCheckboxTooltip(checkboxValue = "check1", buttonLabel = "?", buttonId = "btn1", Tooltip = "tt1!"),
makeCheckboxTooltip(checkboxValue = "check2", buttonLabel = "?", buttonId = "btn2", Tooltip = "tt2!")
)
})
})
}
ui <- fluidPage(
shinyjs::useShinyjs(),
tags$head(HTML("<script type='text/javascript' src='sbs/shinyBS.js'></script>")),
# useShinyBS
sidebarLayout(
sidebarPanel(
sliderInput("obs", "Number of observations:", min = 10, max = 500, value = 100),
uiOutput("rendered"),
uiOutput("tooltips")
),
mainPanel(plotOutput("distPlot"))
)
)
shinyApp(ui = ui, server = server)
I've got a dropdown selector and a slider scale. I want to render a plot with the drop down selector being the source of data. - I've got this part working
I simply want the slider's max value to change based on which dataset is selected.
Any suggestions?
server.R
library(shiny)
shinyServer(function(input, output) {
source("profile_plot.R")
load("test.Rdata")
output$distPlot <- renderPlot({
if(input$selection == "raw") {
plot_data <- as.matrix(obatch[1:input$probes,1:36])
} else if(input$selection == "normalised") {
plot_data <- as.matrix(eset.spike[1:input$probes,1:36])
}
plot_profile(plot_data, treatments = treatment, sep = TRUE)
})
})
ui.R
library(shiny)
shinyUI(fluidPage(
titlePanel("Profile Plot"),
sidebarLayout(
sidebarPanel(width=3,
selectInput("selection", "Choose a dataset:",
choices=c('raw', 'normalised')),
hr(),
sliderInput("probes",
"Number of probes:",
min = 2,
max = 3540,
value = 10)
),
mainPanel(
plotOutput("distPlot")
)
)
))
As #Edik noted the best way to do this would be to use an update.. type function. It looks like updateSliderInput doesnt allow control of the range so you can try using renderUI on the server side:
library(shiny)
runApp(list(
ui = bootstrapPage(
numericInput('n', 'Maximum of slider', 100),
uiOutput("slider"),
textOutput("test")
),
server = function(input, output) {
output$slider <- renderUI({
sliderInput("myslider", "Slider text", 1,
max(input$n, isolate(input$myslider)), 21)
})
output$test <- renderText({input$myslider})
}
))
Hopefully this post will help someone learning Shiny:
The information in the answers is useful conceptually and mechanically, but doesn't help the overall question.
So the most useful feature I found in the UI API is conditionalPanel() here
This means I could create a slider function for each dataset loaded and get the max value by loading in the data initially in global.R. For those that don't know, objects loaded into global.R can be referenced from ui.R.
global.R - Loads in a ggplo2 method and test data objects (eset.spike & obatch)
source("profile_plot.R")
load("test.Rdata")
server.R -
library(shiny)
library(shinyIncubator)
shinyServer(function(input, output) {
values <- reactiveValues()
datasetInput <- reactive({
switch(input$dataset,
"Raw Data" = obatch,
"Normalised Data - Pre QC" = eset.spike)
})
sepInput <- reactive({
switch(input$sep,
"Yes" = TRUE,
"No" = FALSE)
})
rangeInput <- reactive({
df <- datasetInput()
values$range <- length(df[,1])
if(input$unit == "Percentile") {
values$first <- ceiling((values$range/100) * input$percentile[1])
values$last <- ceiling((values$range/100) * input$percentile[2])
} else {
values$first <- 1
values$last <- input$probes
}
})
plotInput <- reactive({
df <- datasetInput()
enable <- sepInput()
rangeInput()
p <- plot_profile(df[values$first:values$last,],
treatments=treatment,
sep=enable)
})
output$plot <- renderPlot({
print(plotInput())
})
output$downloadData <- downloadHandler(
filename = function() { paste(input$dataset, '_Data.csv', sep='') },
content = function(file) {
write.csv(datasetInput(), file)
}
)
output$downloadRangeData <- downloadHandler(
filename = function() { paste(input$dataset, '_', values$first, '_', values$last, '_Range.csv', sep='') },
content = function(file) {
write.csv(datasetInput()[values$first:values$last,], file)
}
)
output$downloadPlot <- downloadHandler(
filename = function() { paste(input$dataset, '_ProfilePlot.png', sep='') },
content = function(file) {
png(file)
print(plotInput())
dev.off()
}
)
})
ui.R
library(shiny)
library(shinyIncubator)
shinyUI(pageWithSidebar(
headerPanel('Profile Plot'),
sidebarPanel(
selectInput("dataset", "Choose a dataset:",
choices = c("Raw Data", "Normalised Data - Pre QC")),
selectInput("sep", "Separate by Treatment?:",
choices = c("Yes", "No")),
selectInput("unit", "Unit:",
choices = c("Percentile", "Absolute")),
wellPanel(
conditionalPanel(
condition = "input.unit == 'Percentile'",
sliderInput("percentile",
label = "Percentile Range:",
min = 1, max = 100, value = c(1, 5))
),
conditionalPanel(
condition = "input.unit == 'Absolute'",
conditionalPanel(
condition = "input.dataset == 'Normalised Data - Pre QC'",
sliderInput("probes",
"Probes:",
min = 1,
max = length(eset.spike[,1]),
value = 30)
),
conditionalPanel(
condition = "input.dataset == 'Raw Data'",
sliderInput("probes",
"Probes:",
min = 1,
max = length(obatch[,1]),
value = 30)
)
)
)
),
mainPanel(
plotOutput('plot'),
wellPanel(
downloadButton('downloadData', 'Download Data Set'),
downloadButton('downloadRangeData', 'Download Current Range'),
downloadButton('downloadPlot', 'Download Plot')
)
)
))
I think you're looking for the updateSliderInput function that allows you to programmatically update a shiny input:
http://shiny.rstudio.com/reference/shiny/latest/updateSliderInput.html. There are similar functions for other inputs as well.
observe({
x.dataset.selection = input$selection
if (x.dataset.selection == "raw") {
x.num.rows = nrow(obatch)
} else {
x.num.rows = nrow(eset.spike)
}
# Edit: Turns out updateSliderInput can't do this,
# but using a numericInput with
# updateNumericInput should do the trick.
updateSliderInput(session, "probes",
label = paste("Slider label", x.dataset.selection),
value = c(1,x.num.rows))
})
Another alternative can be applying a renderUI approach like it is described in one of the shiny gallery examples:
http://shiny.rstudio.com/gallery/dynamic-ui.html