shiny dynamic select input error - r

I learned to use dynamic select input in my shiny application from the Rstudio shiny examples (http://shiny.rstudio.com/gallery/update-input-demo.html). Everything seemed to be OK, but an error occurred. I tested a lot and found the error was due to the dynamic select input used (the observe function in the server.R). But I can't figure out how to fix it. Any help would be highly appreciated. Thanks!
To save space, some of the code was not shown.
server.R
load("./data/genomicVar.RData")
load("./data/geneInfo.RData")
fetchInfoByMsu <- function(locus="") {...}
fetchSnpByMsu <- function(locus="") {...}
fetchIndelByMsu <- function(locus="") {...}
fetchSvByMsu <- function(locus="") {...}
fetchExpByMsu <- function(locus="") {...}
fetchInfoByBin <- function(binNumber="") {...}
fetchGeneByBin <- function(binNumber="") {...}
shinyServer(function(input, output, session) {
output$mytable1 = renderDataTable({...})
output$mytable2 = renderDataTable({...})
output$mytable3 = renderDataTable({...})
output$mytable4 = renderDataTable({...})
output$mytable5 = renderDataTable({...})
output$mytable6 = renderDataTable({...})
output$mytable7 = renderDataTable({...})
observe({
c_bin <- input$bin
c_gene <- fetchGeneByBin(input$bin)
c_gene <- c_gene$locus
# Select input
s_options <- list()
for (i in c_gene) {
s_options[[i]] <- i
}
# Change values for input$inSelect
updateSelectInput(session, "inSelect",
choices = s_options,
selected = c_gene[1]
)
})
output$mytable8 = renderDataTable({...})
output$mytable9 = renderDataTable({...})
output$mytable10 = renderDataTable({...})
output$mytable11 = renderDataTable({...})
output$mytable12 = renderDataTable({...})
})
UI.R
shinyUI(fluidPage(
fluidRow(
absolutePanel(
textInput("msu", label = h4("MSU genomic locus:"),
value = "LOC_Os07g15770"),
tabsetPanel(
tabPanel(strong('Information'), dataTableOutput("mytable1")),
tabPanel(strong('SNP'), dataTableOutput("mytable2")),
tabPanel(strong('Indels'), dataTableOutput("mytable3")),
tabPanel(strong('SVs'), dataTableOutput("mytable4")),
tabPanel(strong('Expression'), dataTableOutput("mytable5"))
),
br(),
p(HTML("<b><div style='background-color:#FADDF2;border:1px solid
blue;'></div></b>")),
textInput("bin", label = h4("Bin ID:"), value = "Bin1078"),
tabsetPanel(
tabPanel(strong('Information'), dataTableOutput("mytable6")),
tabPanel(strong('Gene'), dataTableOutput("mytable7"))
),
wellPanel(
selectInput("inSelect", strong("Select gene:"),
c("gene 1" = "option1",
"gene 2" = "option2"))
),
tabsetPanel(
tabPanel(strong('Information'), dataTableOutput("mytable8")),
tabPanel(strong('SNP'), dataTableOutput("mytable9")),
tabPanel(strong('Indels'), dataTableOutput("mytable10")),
tabPanel(strong('SVs'), dataTableOutput("mytable11")),
tabPanel(strong('Expression'), dataTableOutput("mytable12"))
),
br(),
p(HTML("<b><div style='background-color:#FADDF2;border:1px solid
blue;'></div></b>")),
right=5, left=10
)
)
))

I prefer using uiOutput for dynamic inputs, see this minimal example:
ui.R
shinyUI(fluidPage(
fluidRow(
absolutePanel(
#select bin
textInput("bin", label = h4("Bin ID:"), value = 1),
#dynamic options based on selected bin
uiOutput("inSelect")
)
)
)
)
server.R
shinyServer(function(input, output, session){
#genes dataframe
df <- data.frame(bin=c(1,1,1,2,2,2),
gene=c(12,13,14,21,23,24))
#dynamic select
output$inSelect <- renderUI({
selectInput("inSelect", strong("Select gene:"),
choices = df[ df$bin==input$bin,"gene"])
})
})

Related

How to add a spinner before a selectizeInput has loaded all the choices? [Shiny]

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")

Challenge while updating multiple inputs in shiny

UpdateSliderInput not working...
Hi All,
Seems like a challenge updating sliderInput. So i wanted to develop an application in a way so that filter can be applied dynamically wherein one of the variables needs to be provided with a slider.
Any help can be really appriciable.
library(shiny)
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
fluidRow(
column(6, actionButton('addFilter', 'Add filter')),
offset = 6
),
tags$hr(),
tags$div(id = 'placeholderAddRemFilt'),
tags$div(id = 'placeholderFilter'),
tags$div(id = 'placeholderFilter')
# width = 4 # sidebar
),
mainPanel(
tableOutput("data")
)
)
)
server <- function(input, output,session) {
filter <- character(0)
makeReactiveBinding("aggregFilterObserver")
aggregFilterObserver <- list()
observeEvent(input$addFilter, {
add <- input$addFilter
filterId <- paste0('Filter_', add)
colfilterId <- paste0('Col_Filter_', add)
rowfilterId <- paste0('Row_Filter_', add)
removeFilterId <- paste0('Remove_Filter_', add)
headers <- names(mtcars)
insertUI(
selector = '#placeholderFilter',
# ui = tags$div(id = filterId,
# actionButton(removeFilterId, label = "Remove filter", style = "float: right;"),
# selectInput(colfilterId, label = "Some Filter", choices = as.list(headers), selected = 1),
# sliderInput(rowfilterId, label = "Select variable values",
# min = 1, max = 2, value = 1:4)
# )
ui = tags$div(column(9,id = filterId,
actionButton(removeFilterId, label = "Remove filter", style = "float: right;"),
selectInput(colfilterId, label = "Some Filter", choices = headers, selected = NULL),
conditionalPanel(condition = paste0("input.",colfilterId," != 'mpg'"),
checkboxGroupInput(rowfilterId, label = "Select variable values",
choices = NULL, selected = NULL, width = 4000)),
conditionalPanel(condition = paste0("input.",colfilterId," == 'mpg'"),
sliderInput(rowfilterId,
label = 'select values',
min = 1,#min(datafile$Age),
max = 10,#max(datafile$Age),
value = 1:5))#c(min(datafile$Age),max(datafile$Age))))
)
)
)
observeEvent(input[[colfilterId]], {
col <- input[[colfilterId]]
values <- as.list(unique(mtcars[col]))[[1]]
print(values)
print(paste0("example",as.list(unique(mtcars[col]))))
#
# updateCheckboxGroupInput(session, rowfilterId , label = "Select variable values",
# choices = values, selected = values, inline = TRUE)
#
updateSliderInput(session, rowfilterId , min = min(values), max = max(values), value = c(min(values),max(values)))
updateCheckboxGroupInput(session, rowfilterId , label = "Select variable values",
choices = values, selected = values, inline = TRUE)
aggregFilterObserver[[filterId]]$col <<- col
aggregFilterObserver[[filterId]]$rows <<- NULL
})
observeEvent(input[[rowfilterId]], {
rows <- input[[rowfilterId]]
aggregFilterObserver[[filterId]]$rows <<- rows
})
observeEvent(input[[removeFilterId]], {
removeUI(selector = paste0('#', filterId))
aggregFilterObserver[[filterId]] <<- NULL
})
})
output$data <- renderTable({
dataSet <- mtcars
invisible(lapply(aggregFilterObserver, function(filter){
dataSet <<- dataSet[which((dataSet[[filter$col]] %in% filter$rows)), ]
}))
dataSet
})
}
shinyApp(ui = ui, server = server)
Mpg values are not being updated, Is this due to conditionalPanel because of which the sliderInput is not being updated?
Everything seems to be perfect apart from the inputid you are using for 2 input types.
I just created one more variable for Sliderinput which will create dynamic input id.
library(shiny)
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
fluidRow(
column(6, actionButton('addFilter', 'Add filter')),
offset = 6
),
tags$hr(),
tags$div(id = 'placeholderAddRemFilt'),
tags$div(id = 'placeholderFilter'),
width = 4 # sidebar
),
mainPanel(
tableOutput("data")
)
)
)
server <- function(input, output,session) {
filter <- character(0)
makeReactiveBinding("aggregFilterObserver")
aggregFilterObserver <- list()
observeEvent(input$addFilter, {
add <- input$addFilter
filterId <- paste0('Filter_', add)
colfilterId <- paste0('Col_Filter_', add)
rowfilterId <- paste0('Row_Filter_', add)
rowfilterId_num <- paste0('Row_Filter_num_', add)
removeFilterId <- paste0('Remove_Filter_', add)
headers <- names(mtcars)
insertUI(
selector = '#placeholderFilter',
ui = tags$div(id = filterId,
actionButton(removeFilterId, label = "Remove filter", style = "float: right;"),
selectInput(colfilterId, label = "Some Filter", choices = as.list(headers), selected = 1),
sliderInput(rowfilterId_num, label = "Select variable values",
min = 1, max = 2, value = 1:4)
)
)
observeEvent(input[[colfilterId]], {
print(rowfilterId)
print(paste0(input[[colfilterId]]))
col <- input[[colfilterId]]
values <- as.list(unique(mtcars[col]))[[1]]
print(values)
print(paste0("example",as.list(unique(mtcars[col]))))
updateCheckboxGroupInput(session, rowfilterId , label = "Select variable values",
choices = values, selected = values, inline = TRUE)
updateSliderInput(session, rowfilterId_num , label = "Select variable",min = min(values), max = max(values), value = c(min(values),max(values)))
aggregFilterObserver[[filterId]]$col <<- col
aggregFilterObserver[[filterId]]$rows <<- NULL
})
observeEvent(input[[rowfilterId]], {
rows <- input[[rowfilterId]]
aggregFilterObserver[[filterId]]$rows <<- rows
})
observeEvent(input[[removeFilterId]], {
removeUI(selector = paste0('#', filterId))
aggregFilterObserver[[filterId]] <<- NULL
})
})
output$data <- renderTable({
dataSet <- mtcars
invisible(lapply(aggregFilterObserver, function(filter){
dataSet <<- dataSet[which((dataSet[[filter$col]] %in% filter$rows)), ]
}))
dataSet
})
}
shinyApp(ui = ui, server = server)
just check and let me know that this is what you wanted to achieve. let me know incase any thing else is required.

How to get data from radio button to plot from the file I have read in

I have read in a FCS file and I have got the parameters in a radio button, I am able to read the table data but I dont know how to plot the data.
there are 6 channels here as shown below.I have printed the data in a tabular format.enter image description here
My ui.r script is
rm(list = ls())
library(shiny)
library(flowCore)
shinyUI(fluidPage(
titlePanel("CD4/CD8 count GUI DEMO"),
fluidRow(
column(3,
fileInput('fcsFiles', strong('Choose fcs file:'),
accept = c('text/fcs', '.fcs')),
actionButton("goButton", "Submit!"),
hr(),
## sample limits: 50
uiOutput("sample_select"),
lapply(1:50, function(i) {
uiOutput(paste0('timeSlider', i))
}),
hr(),
uiOutput(outputId= "marker_select"),
uiOutput(outputId= "marker_select121"),
hr()
),
sidebarPanel(
numericInput("num1", label = h6("WBC COUNT"), value = 1,min = 0, max = NA, step = NA),
hr(),
fluidRow(column(3, verbatimTextOutput("wbc"))),
numericInput("num2", label = h6("lymphocyte percentage"), value = 1,min = 0, max = NA, step = NA),
hr(),
fluidRow(column(3, verbatimTextOutput("lymphocyte"))),
textOutput("ablymph"),
uiOutput(outputId= "xaxis"),
hr(),
uiOutput(outputId= "yaxis"),
hr(),
actionButton("goButton", "Submit!")
),
mainPanel(
tableOutput("filetable"),
plotOutput("fowardside"),
plotOutput("cd3plot"),
plotOutput("cd4plot"),
plotOutput("meplot"),
plotOutput("cd8plot")
)
)
))
and my Server.R script is
rm(list = ls())
library(flowCore)
library(shiny)
library(flowViz)
library(flowStats)
shinyServer(function(input, output,session) {
output$ablymph <- renderText({
W <- input$num1
L <- input$num2
x <- W*(L/100)
paste("Absolute Lymphocytes Count is =", x)
})
set <- reactive({
if (input$goButton == 0)
return()
isolate({fcsFiles<- input$fcsFiles
if (is.null(fcsFiles))
return (NULL)
set <- read.flowSet(fcsFiles$datapath)
sampleNames(set)<- fcsFiles$name})
return(set)
print(set)
})
output$sample_select <- renderUI({
if(is.null(set())){
return(NULL)
}else{
checkboxGroupInput('samples', strong('Select samples:'),
sampleNames(set()), selected = sampleNames(set()))
}
})
markerNames <- reactive({
if(is.null(set()))
return(NULL)
pd <- set()[[1]]#parameters#data
markers <- paste("<", pd$name, ">:", pd$desc, sep = "")
return(markers)
})
output$marker_select <- renderUI({
if(is.null(markerNames())){
return(NULL)
}else{
radioButtons(inputId = 'paras', label = ('Select markers for X-AXIS:'),
choices = markerNames(), selected = )
}
})
output$marker_select121 <- renderUI({
if(is.null(markerNames())){
return(NULL)
}else{
radioButtons(inputId = 'paras1', label = ('Select markers for Y-AXIS:'),
choices = markerNames(), selected = NULL)
}
})
output$filetable <- renderTable({
data1<- set()[[1]]#parameters#data
return(data1)
})
output$cd3plot<-renderPlot({
plot(set()[[1]]#parameters#data1[paras],set()[[1]]#parameters#data1[paras1])
})
})
can anyone help me with this please
thanks

Shiny R: Modifying the variable class

I am trying to create a shiny-app that load data-set, present the variable list and their classes and allow the user to modify the class of a selected variable. All the functions in the following code are working except to the last function in the server- observeEvent which not working when trying to modify the variable class. Any suggestions?
Thank you in advance,
Rami
`
rm(list = ls())
library(shiny)
library(shinydashboard)
library(DT)
ui <- dashboardPage(
dashboardHeader(title = "Shiny Example"),
#--------------------------------------------------------------------
dashboardSidebar(
sidebarMenu(
menuItem("Data", tabName = "data", icon = icon("th"))
)
),
#--------------------------------------------------------------------
dashboardBody(
#--------------------------------------------------------------------
tabItem(tabName = "data",
fluidPage(
fluidRow(
box(
selectInput('dataset', 'Select Dataset', list(GermanCredit = "GermanCredit",
cars = "cars",
iris = "iris")),
title = "Datasets",width = 4, status = "primary",
checkboxInput("select_all", "Select All Variable", value = TRUE),
conditionalPanel(condition = "input.select_all == false",
uiOutput("show.var"))
),
box(
title = "Variable Summary", width = 4, status = "primary",
DT::dataTableOutput('summary.data')
),
box(
title = "Modify the Variable Class", width = 4, status = "primary",
radioButtons("choose_class", label = "Modify the Variable Class",
choices = list(Numeric = "numeric", Factor = "factor",
Character = "character"),
selected = "numeric"),
actionButton("var_modify", "Modify")
)
)
)
)
)
)
#--------------------------------------------------------------------
# Server Function
#--------------------------------------------------------------------
server <- function(input, output,session) {
#--------------------------------------------------------------------
# loading the data
get.df <- reactive({
if(input$dataset == "GermanCredit"){
data("GermanCredit")
GermanCredit
}else if(input$dataset == "cars"){
data(cars)
cars
}else if(input$dataset == "iris"){
data("iris")
iris
}
})
# Getting the list of variable from the loaded dataset
var_list <- reactive(names(get.df()))
# Choosing the variable - checkbox option
output$show.var <- renderUI({
checkboxGroupInput('show_var', 'Select Variables', var_list(), selected = var_list())
})
# Setting the data frame based on the variable selction
df <- reactive({
if(input$select_all){
df <- get.df()
} else if(!input$select_all){
df <- get.df()[, input$show_var, drop = FALSE]
}
return(df)
})
# create list of variables
col.name <- reactive({
d <- data.frame(names(df()), sapply(df(),class))
names(d) <- c("Name", "Class")
return(d)
})
# render the variable list into table
output$summary.data <- DT::renderDataTable(col.name(), server = FALSE, rownames = FALSE,
selection = list(selected = 1, mode = 'single'),
options = list(lengthMenu = c(5, 10, 15, 20), pageLength = 20, dom = 'p'))
# storing the selected variable from the variables list table
table.sel <- reactive({
df()[,which(colnames(df()) == col.name()[input$summary.data_rows_selected,1])]
})
# Trying to modify the variable class
observeEvent(input$var_modify,{
modify.row <- which(colnames(df()) == col.name()[input$summary.data_rows_selected,1])
if( input$choose_class == "numeric"){
df()[, modify.row] <- as.numeric(df()[, modify.row])
} else if( input$choose_class == "factor"){
df()[, modify.row] <- as.factor(df()[, modify.row])
} else if( input$choose_class == "character"){
df()[, modify.row] <- as.character(df()[, modify.row])
}
})
}
shinyApp(ui = ui, server = server)
`
I would use reactiveValues() instead.
library(shiny)
# Define UI for application that draws a histogram
ui <- shinyUI(fluidPage(
sidebarLayout(
sidebarPanel(
selectInput("classType", "Class Type:", c("as.numeric", "as.character"))
),
mainPanel(
textOutput("class")
)
)
))
server <- shinyServer(function(input, output) {
global <- reactiveValues(sample = 1:9)
observe({
global$sample <- get(input$classType)(global$sample)
})
output$class <- renderText({
print(class(global$sample))
})
})
shinyApp(ui = ui, server = server)
In case you are interested:
Concerning your attempt: reactive() is a function and you called the output of the function by df()[, modify.row]. So in your code you try to change the output of the function, but that does not change the output of futures calls of that function.
Maybe it is easier to see in a simplified version:
mean(1:3) <- 1
The code can not change the mean function to output 1 in future. So thats what reactiveValues() help with :). Hope that helps!

R Shiny Make slider value dynamic

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

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