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")
How do I create a scrollable list of tables within a tabPanel?
Based on Outputing N tables in shiny, where N depends on the data, I have tried the following
Server.R
userHist <- list(
data.frame(X=1:10,Y=11:20),
data.frame(X=1:10,Y=11:20))
output$groupHistory <- renderUI({
userHistList <- lapply( seq(userHist), function(i){
hist_i <- userHist[[i]]
TabName <- paste0("User", i)
fluidRow( column(10,
h2(TabName),
hr(),
column(3, renderTable(hist_i, rownames=TRUE) )
) )
} )
userHistList
})
ui.R
tabsetPanel(id="tabsetpanel",
tabPanel(h1("Group History"),
style="overflow-y:scroll;",
uiOutput("groupHistory")
)
)
There is a main firefox scrollbar that shows up when the list gets long, but there is a second scrollbar for the table that does not scroll vertically. Ideally I would also eliminate horizontal scrolling.
You need to call the render first to create the output objects and the compose the UI with those objects:
ui <- fluidPage(
tabsetPanel(
id = "tabsetpanel",
tabPanel(
style = "overflow-y:scroll; max-height: 600px",
h1("Group History"),
numericInput("n_users", "Number of Users", value = 5, min = 1, max = 10),
uiOutput("group_history")
)
)
)
server <- shinyServer(function(input, output) {
df_list <- reactive({
n <- input$n_users
# generate some observations
obs_x <- seq(3)
obs_y <- obs_x + n
# generate the df
df_template <- data.frame(x = obs_x, y = obs_y)
# make a list of df and return
lapply(seq(n), function(n) {
df_template
})
})
# use the constructed renders and compose the ui
output$group_history <- renderUI({
table_output_list <- lapply(seq(input$n_users), function(i) {
table_name <- paste0("table", i)
tab_name <- paste("User", i)
fluidRow(
column(
width = 10,
h2(tab_name),
hr(), column(3, tableOutput(table_name))
)
)
})
# Convert the list to a tagList - this is necessary for the list of items
# to display properly.
do.call(tagList, table_output_list)
})
# Call renderTable for each one. Tables are only actually generated when they
# are visible on the web page.
observe({
data <- df_list()
for (i in seq(input$n_users)) {
# Need local so that each item gets its own number. Without it, the value
# of i in the renderPlot() will be the same across all instances, because
# of when the expression is evaluated.
local({
my_i <- i
tab_name <- paste0("table", my_i)
output[[tab_name]] <- renderTable(data[[my_i]], rownames = TRUE)
})
}
})
})
shinyApp(ui, server)
Based off of Winston Chang's work here
I wrapped the list in fluidPage or wellPanel and everything works as I want.
Server.R
userHist <- list(
data.frame(X=1:10,Y=11:20),
data.frame(X=1:10,Y=11:20))
output$groupHistory <- renderUI({
userHistList <- lapply( seq(userHist), function(i){
hist_i <- userHist[[i]]
TabName <- paste0("User", i)
fluidRow( column(10,
h2(TabName),
hr(),
column(3, renderTable(hist_i, rownames=TRUE) )
) )
} )
table_output_list <- fluidPage(userHistList,
style="overflow-y:scroll; max-height: 90vh")
})
UI.R
tabsetPanel(id="tabsetpanel",
tabPanel(h1("Group History"),
style="overflow: visible",
uiOutput("groupHistory")
)
)
ran into this weird issue when teaching a student about shiny programming.
What i wanted was to make code that deletes the verbatimtextOuput element, rather than print an empty value
This is the code he wrote, but it deletes all buttons, the whole UI basically. Can this be done? I know more complex options like conditional panels etc, but just trying to figure out why removeUI doesn't do what I expected here.
Thanks!
app:
library(shiny)
ui<-fluidPage( h5("Hello there"), #First text on the window
br(), #empty line
actionButton(inputId = "ClickonMe", label = "Make data"), # button 1
actionButton(inputId = "ClickonMe2", label = "Print data"), # button 2
actionButton(inputId = "ClickonMe3", label = "Transform data"),
verbatimTextOutput("Response_text") #reactive text output )
server <- function(input,output) {
values <- reactiveValues()
observeEvent(input$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$name)})
}
shinyApp(ui, server)
How to show warning to user in shiny in R. The user's input is correct, but the output is not suitable to show. The aim is to remind the user only a subset data are shown due to too many. warning() is shown in console only. Thank you.
Here is a fake code to explain the question due to the original is long. There is a warning in the renderTable. it aims to check data if the data is big, only first several items will be shown.
ui.R
shinyUI(fluidPage(
titlePanel("Validation App"),
sidebarLayout(
sidebarPanel(
selectInput("data", label = "Data set",
choices = c("", "mtcars", "faithful", "iris"))
),
# Show a plot of the generated distribution
mainPanel(
tableOutput("table"),
plotOutput("plot")
)
)
))
server.R
shinyServer(function(input, output) {
data <- reactive({
validate(
need(input$data != "", "Please select a data set")
)
get(input$data, 'package:datasets')
})
output$plot <- renderPlot({
hist(data()[, 1], col = 'forestgreen', border = 'white')
})
output$table <- renderTable({
warning("Warning message.")
head(data())
})
})
Update:
I put some more work into this and made the warning panel conditional.
However it only works if I include out the textOutput("warnstat") on every page. I assume because it is not setting the javascript variable output.warnstat unless I do this.
You could just build a warning panel into your UI, and set it accordingly. Here is a simple example, but it could be more elaborate than just a verabtim print statement.
ui.r
shinyUI(fluidPage(
titlePanel("Validation App"),
sidebarLayout(
sidebarPanel(
selectInput("data", label = "Data set",
choices = c("", "mtcars", "faithful", "iris"))
),
# Show a plot of the generated distribution
mainPanel(
conditionalPanel(condition = "output.warnstat == 'Error'",
verbatimTextOutput("warnmsg")),
tableOutput("table"),
plotOutput("plot")
)
)
))
server.r
shinyServer(function(input, output) {
errstat <- reactive({
ifelse (input$data=="mtcars",T,F)
})
data <- reactive({
validate(
need(input$data != "", "Please select a data set")
)
get(input$data, 'package:datasets')
})
output$plot <- renderPlot({
hist(data()[, 1], col = 'forestgreen', border = 'white')
})
output$table <- renderTable({
warning("Warning message.")
head(data())
})
output$warnmsg <- renderPrint({
if (errstat()){
print("Warning message - blah blah blah")
print(input$data)
head(data())
} else {
print("No error")
}
})
output$warnstat <- renderText({ifelse(errstat(),"Error","No error") })
outputOptions(output, "warnstat", suspendWhenHidden=FALSE)
})
With conditional warning panel:
Without conditional warning panel:
I use this wrapping function to capture errors, warnings and messages and display them as dismissible notifications to the user.
quietly <- function(.f) {
fun <- .f %>% purrr::quietly() %>% purrr::safely()
function(...) {
res <- fun(...)
if(!is.null(res$error)) { # safely output
showNotification(res$error$message, duration = 10, type="error")
return(res$result)
}
res <- res$result # quietly output
if(!is.null(res$warnings) && length(res$warnings) > 0) {
lapply(unique(res$warnings), showNotification, duration = 10, type="warning")
}
return(res$result)
}
}