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 am trying to create my first shiny app but I am facing a difficulty: in the reproducible example below I am creating a reactive pickerInput (i.e. only show brands proposing a cylindre equal to the input visitors select).
I then want that based on the combination input_cyl and picker_cny (remember that picker_cny depends on input_cyl) to display a table which shows the relevant data for the observation matching the combination input_cyl and picker_cny.
Thank you for your help!
df <- mtcars
df$brand <- rownames(mtcars)
df$brand <- gsub("([A-Za-z]+).*", "\\1", df$brand)
if (interactive()) {
library(shiny)
library(shinyWidgets)
library(shinythemes)
library(shinycssloaders)
# Define UI -----------------------------------------------
ui <- fluidPage(
# Application title
titlePanel("Reproducible Example"),
# Parameters
sidebarLayout(
sidebarPanel(
selectInput(inputId = "input_cyl", label = "Cyl",
choices = c("6", "4", "8")),
pickerInput(
inputId = "picker_cny",
label = "Select Company",
choices = paste0(unique(df$brand)),
options = list(`actions-box` = TRUE),
multiple = TRUE),
width = 2),
# Show Text
mainPanel(
tableOutput("table"),
width = 10)
))
# Define Server ------------------------------------------
server <- function(input, output, session) {
# Reactive pickerInput ---------------------------------
observeEvent(input$input_cyl, {
df_mod <- df[df$cyl == paste0(input$input_cyl), ]
# Method 1
disabled_choices <- !df$cyl %in% df_mod$cyl
updatePickerInput(session = session,
inputId = "picker_cny",
choices = paste0(unique(df$brand)),
choicesOpt = list(
disabled = disabled_choices,
style = ifelse(disabled_choices,
yes = "color: rgba(119, 119, 119, 0.5);",
no = "")
))
}, ignoreInit = TRUE)
output$table <- renderTable(df)
}
}
# Run the application
shinyApp(ui = ui, server = server)
You need a reactive that will handle the change in the input and subset the dataframe before giving it to the output table. For that, you just need to add this block to your server:
data <- reactive({
if (length(input$picker_cny) > 0)
df[df$brand %in% input$picker_cny,]
else
df
})
and update the output$table like this:
output$table <- renderTable(data())
Note: feel free to remove the if else in the reactive to get that:
data <- reactive({
df[df$brand %in% input$picker_cny,]
})
The only difference in that case is: would you show all or nothing when no input has been entered yet. That's a matter of taste.
I am struggling trying to graph two overlaying plots and add checkboxes fro displaying them in my Rshiny app. I am using the following code:
library(shiny)
library(shinyjs)
mpgData <- mtcars
ui <- fluidPage(
# Application title
titlePanel("Test"),
# Sidebar with checkboxes to select plot
sidebarLayout(
sidebarPanel(
helpText("Select type of plot:"),
checkboxGroupInput("checkPlot",
label = ("Plots"),
choices=c("Baseline","Scenario A"),
selected = c("Baseline","Scenario A")
)
),
mainPanel(
textOutput("overview"),
plotOutput("plot")
)
)
)
server <- function(input, output, session) {
#get Check group input (type of plot)
checkedVal <- reactive({
as.vector(input$checkPlot)
})
#plot
output$plot <- renderPlot({
if(("Baseline" %in% checkedVal()) & ("Scenario A" %in% checkedVal()))
# first plot
plot(mpgData$mpg, mpgData$cyl, type='l',col="steelblue",ylim=range(c(mpgData$cyl,mpgData$disp)))
# second plot
par(new = TRUE)
plot(mpgData$mpg, mpgData$disp, type = "l",col="red", ylim=range(c(mpgData$cyl,mpgData$disp)), axes = FALSE, xlab = "", ylab = "")
if ("Baseline" %in% checkedVal())
plot(mpgData$mpg, mpgData$cyl, type='l',col = "steelblue")
if ("Scenario A" %in% checkedVal())
plot(mpgData$mpg, mpgData$disp, type='l',col = "red")
})
}
shinyApp(ui, server)
My checkboxes seem to be working out alright when I just want one graph to be displayed, however, there's definitely an issue when I want to display both on the same axes. Most examples I saw were a little too complex for me to understand and break down, so I tired to infer from previous R knowledge, but clearly I'm off.
any help is much appreciated !
If you were trying to add the baseline on the existing graph, you could use the lines function, as below. Although if for your particular data-set, the base line is really negligible compared to the original plot, you need to use a package other than 'base', like 'ggplot'.
library(shiny)
library(shinyjs)
mpgData <- mtcars
ui <- fluidPage(
# Application title
titlePanel("Test"),
# Sidebar with checkboxes to select plot
sidebarLayout(
sidebarPanel(
helpText("Select type of plot:"),
checkboxGroupInput("checkPlot",
label = ("Plots"),
choices=c("Baseline","Scenario A"),
selected = c("Baseline","Scenario A")
)
),
mainPanel(
textOutput("overview"),
plotOutput("plot")
)
)
)
server <- function(input, output, session) {
#get Check group input (type of plot)
checkedVal <- reactive({
as.vector(input$checkPlot)
})
#plot
# first plot
output$plot <- renderPlot({
if(("Baseline" %in% checkedVal()) & ("Scenario A" %in% checkedVal()))
{ plot(mpgData$mpg, mpgData$cyl, type='l',col="steelblue",ylim=range(c(mpgData$cyl,mpgData$disp)))
lines(mpgData$mpg, mpgData$disp, type = "l",col="red")
}
else if("Baseline" %in% checkedVal())
{
plot(mpgData$mpg, mpgData$cyl, type='l',col = "steelblue")
}
else if("Scenario A" %in% checkedVal())
{
plot(mpgData$mpg, mpgData$disp, type='l',col = "red")
}
})
}
shinyApp(ui, server)
Please let me know if this works for you.
I'm trying to build a simple application that draws a histogram of a selected variable based on a subset filtered by the other input. I get the error in the line hist(dataX()$datasetInput()) which should return dataX$mpg. How can I fix it?
Full code:
library(shiny)
u <- shinyUI(pageWithSidebar(
headerPanel("Staz w bezrobociu"),
sidebarPanel(
selectInput("variable", "Variable:",
list("Milles/gallon",
"Horse power")
),
textInput("nc","Number of cylinders",value = 6)
),
mainPanel(
plotOutput("Plot")
)
))
s <- shinyServer(function(input, output)
{
dataX <- reactive({mtcars[mtcars$cyl==input$nc,,drop = FALSE]})
datasetInput <- reactive({
switch(input$variable,
"Milles/gallon" = mpg,
"Horse power" = hp)
})
output$Plot <- renderPlot({
hist(dataX()$datasetInput())
})
})
shinyApp(u,s)
You complicated the simple app.
You do not need to list all the columns in selectInput. You can just render it from the server side.
Same applies to the cylinders
Shortcuts like u and sare acceptable, but just stick to the naming conventions. It makes your life easy.
Below is a complete working app
library(shiny)
ui <- shinyUI(pageWithSidebar(
headerPanel("Staz w bezrobociu"),
sidebarPanel(uiOutput("SelectColname"),
uiOutput("Cylinders")),
mainPanel(plotOutput("Plot"))
))
server <- shinyServer(function(input, output){
# Create a reactive dataset
dataX <- reactive({
mtcars
})
# Output number cylinders as select box
output$Cylinders <- renderUI({
selectInput("cylinders", "cylinders:", unique(dataX()$cyl))
})
# Output column names as selectbox
output$SelectColname <- renderUI({
selectInput("variable", "Variable:", colnames(dataX()[,c(1,4)]))
})
# Based on the selection by user, create an eventreactive plotdata object
plotdata <- eventReactive(input$cylinders, {
plotdata = dataX()[dataX()$cyl == input$cylinders, , drop = FALSE]
})
# Render the plot, the plot changes when new cylinder is selected
output$Plot <- renderPlot({
if (is.null(plotdata()))
return(NULL)
hist(
plotdata()[, input$variable],
xlab = input$variable,
main = paste(
"Histogram of" ,
input$variable
)
)
})
})
shinyApp(ui, server)
I'm working on building an interactive heatmap Shiny app and would like select columns to sort from a drop down menu (example: sort "mpg" or "wt" in mtcars from low to high). I'm implementing the heatmap with the d3heatmap package and want to reactivity short the dataframe using dplyr. I get the following error when running the code:
Error in eval(substitute(expr), envir, enclos) : invalid subscript
type 'closure'
I have also tried using reactiveValues instead of reactive and included the code as a comment. Using the reactiveValues approach I get the following error:
Warning: Unhandled error in observer: invalid subscript type 'closure'
Any help getting the heatmap sorting to work would be greatly appreciated!
app.R
library(ggplot2)
library(d3heatmap)
library(dplyr)
library(shiny)
## ui.R
ui <- fluidPage(
sidebarPanel(
h5(strong("Dendrogram:")),
checkboxInput("cluster_row", "Cluster Rows", value=FALSE),
checkboxInput("cluster_col", "Cluster Columns", value=FALSE),
selectInput("sort", "Sort By:", c(names(mtcars),"none"), selected="mpg")
),
mainPanel(
h4("Heatmap"),
d3heatmapOutput("heatmap", width = "100%", height="600px") ##
)
)
## server.R
server <- function(input, output) {
# values <- reactiveValues(df=mtcars)
#
# observe({
# if(input$sort != "none"){
# values$df <- arrange(mtcars, input$sort)
# }else{
# values$df <- mtcars
# }
# })
df_sort <- reactive({
df <- mtcars
if(input$sort != "none"){
df <- arrange(mtcars, input$sort)
}else{
df <- mtcars
}
})
output$heatmap <- renderD3heatmap({
d3heatmap(df_sort(),
colors = "Blues",
if (input$cluster_row) RowV = TRUE else FALSE,
if (input$cluster_col) ColV = TRUE else FALSE,
yaxis_font_size = "7px"
)
})
}
shinyApp(ui = ui, server = server)
input$sort is being passed as a character string, so you need to use arrange_ (see the vignette on NSE).
The following should do the trick:
server <- function(input, output) {
df_sort <- reactive({
df <- if(input$sort=='none') mtcars else arrange_(mtcars, input$sort)
})
output$heatmap <- renderD3heatmap({
d3heatmap(
df_sort(),
colors = "Blues",
RowV <- if(input$cluster_row) TRUE else FALSE,
ColV <- if(input$cluster_col) TRUE else FALSE,
yaxis_font_size = "7px"
)
})
}
ui <- fluidPage(
sidebarPanel(
h5(strong("Dendrogram:")),
checkboxInput("cluster_row", "Cluster Rows", value=FALSE),
checkboxInput("cluster_col", "Cluster Columns", value=FALSE),
selectInput("sort", "Sort By:", c(names(mtcars),"none"), selected="mpg")
),
mainPanel(
h4("Heatmap"),
d3heatmapOutput("heatmap", width = "100%", height="600px") ##
)
)