I am referring to my previous post: while updating the datatable in R shiny, how to make column inputs necessary fields using "validate" and "need" in R shiny
I'm making a R shiny app in which the user can add numerous rows by clicking the "Add" button and saving the data to a .xpt file. As of now, everything is in working order.
I just stuck below:
However, in order to expand this app, I've added the button "clear" to the server function, as well as'reactiveValues', so that when users click it, all previous rows (added rows) are removed (cleared), and the app is ready to accept new rows. I can still add rows, but the clear option doesn't work and doesn't give me any errors. Is there anyone who can assist me?
code
library(shiny)
library(stringr)
library(shinydashboard)
library(tidyverse)
library(DT)
library("SASxport")
ui <- fluidPage(
fluidRow(tabsetPanel(id='tabs',
tabPanel("Tab1",
div(id = "form",
textInput("schoolId", label="SchoolId *" ),
selectInput("userId", label="UserId", choices = c("UserA", "UserB", "UserC"),selected = "UserA"),
textInput("class", label = "class"),
selectInput("result", label="result", choices = c("PASS", "FAIL" )),
#dateInput("resultdate", value = NA, label = "Date of the result / Remarks for fail"
#, format = "yyyy-mm-dd" )
),
actionButton("add", "Add"),
actionButton("clear", "Clear")
),
tabPanel("Tab2",
tabPanel("View",
conditionalPanel("input.add != 0",
DTOutput("DT2"), hr(), downloadButton('downloadData', 'Download'))
)
)
)
)
)
server <- function(input, output, session) {
store <- reactiveValues()
observeEvent(input$add,{
new_entry <- data.frame(SCHOOLID=input$schoolId, USERID=input$userId
, CLASS= input$class
, RESULT=input$result
)
# new_entry <- data.frame(SCHOOLID=input$schoolId, USERID=input$userId
# , CLASS= input$class
#, RESULT=input$result,
#RESULT_DATE = input$resultdate)
if("value" %in% names(store)){
store$value<-bind_rows(store$value, new_entry)
} else {
store$value<-new_entry
}
# If you want to reset the field values after each entry use the following two lines
for(textInputId in c("schoolId", "class")) updateTextInput(session, textInputId, value = "")
updateSelectInput(session, "userId", selected = "UserA")
updateSelectInput(session, "result", selected = "PASS")
# updateDateInput(session, "resultdate")
})
output$DT2 <- renderDT({
store$value
})
output$downloadData <- downloadHandler(
filename = paste0("mydata", ".xpt"),
content = function(file){
write.xport(store$value, file = file)
}
)
new_frame <- reactive({
store$value
})
#function allows to clear the rows
values <- reactiveValues(df_data = new_frame)
observeEvent(input$clear,{
if (!is.null(input$table1_rows_selected)) {
values$df_data <- values$df_data[-as.character(input$table1_rows_selected),]
}
})
output$Tab2 <- renderDataTable({
values$df_data
})
}
shinyApp(ui, server)
The problem here is a slight oversight in how the selected rows are obtained for deletion. Instead of getting selected rows from the DT table, one has to get them straight from the ui element which is DT2
Also, you can work directly on the DT table created in server, instead of storing a new reactive value
Here's the revised (relevant) server code :
#xxxxxxxx this not needed
#values <- reactiveValues(df_data = new_frame)
observeEvent(input$clear,{
if (!length(input$DT2_rows_selected)==0) {
#work directly on store variable
store$value<- store$value[-as.numeric(input$DT2_rows_selected),]
}
})
I've tested this and it works. Can post the whole app code if needed.
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 have a selectizeInput with some grouped elements with multiple selection. Is there an elegant way (e.g. using the options argument) of allowing just one element per group, so that a whole group will discarded (or disabled) when an element of this specific group is selected?
So far I tried it programmatically, but than the dropdown menu of the selectizeInput will be closed when updating the selectizeInput.
Minimal example:
library(shiny)
ui <- fluidPage(
selectizeInput("selInput", "Default",
choices=list(g1 = c(A="A",B="B"),
g2 = c(C="C",D="D")),
multiple=T),
selectizeInput("oneElementPerGroup", "One element per group",
choices=list(g1 = c(A="A",B="B"),
g2 = c(C="C",D="D")),
multiple=T)
)
server <- function(session, input, output) {
#Removes the corresponding groups of selected items
observeEvent(input$oneElementPerGroup, ignoreNULL = F, {
plusChoice <- input$oneElementPerGroup
names(plusChoice) <- input$oneElementPerGroup
choices <- list(g1 = c(A="A",B="B"),
g2 = c(C="C",D="D"))
if(any(input$oneElementPerGroup %in% c("A", "B"))){
choices[["g1"]] <- NULL
}
if(any(input$oneElementPerGroup %in% c("C", "D"))){
choices[["g2"]] <- NULL
}
choices$we <- plusChoice
updateSelectizeInput(session,"oneElementPerGroup",
choices = choices,
selected=input$oneElementPerGroup)
})
}
shinyApp(ui = ui, server = server)
You can use pickerInput from {shinyWidgets}. Then we can add a little javascript to do what you want. No server code is needed, very simple. Read more about the data-max-options option: https://developer.snapappointments.com/bootstrap-select/options/.
We need to add the limit to each group, not an overall limit, so we can't add it through the options argument in pickerInput, have to do it in raw HTML or use some js code to inject like what I do.
Be sure your inputId="pick" matches the id in the script #pick. Rename pick to whatever you want.
ui <- fluidPage(
shinyWidgets::pickerInput(
inputId = "pick", label = "Selected",
choices =list(g1 = c(A="A",B="B"), g2 = c(C="C",D="D")),
multiple = TRUE
),
tags$script(
'
$(function(){
$("#pick optgroup").attr("data-max-options", "1");
})
'
)
)
server <- function(input, output, session){}
shinyApp(ui, server)
updates:
If you need to update, we need to run the script again but from server. We can send js by using {shinyjs}. Imagine an observer triggers the update event.
library(shinyjs)
ui <- fluidPage(
useShinyjs(),
shinyWidgets::pickerInput(
inputId = "pick", label = "Selected",
choices =NULL,
multiple = TRUE
)
)
server <- function(input, output, session){
observe({
shinyWidgets::updatePickerInput(session, "pick", choices = list(g1 = c(A="A",B="B"), g2 = c(C="C",D="D")))
observeEvent(once = TRUE, reactiveValuesToList(session$input), {
runjs('$("#pick optgroup").attr("data-max-options", "1");')
}, ignoreInit = TRUE)
})
}
shinyApp(ui, server)
I am trying to create a shiny code that is able to filter a table non pre-determined number of times. When the user uploads a different (new) table, unfortunately the code breaks as I need to restart a lapply loop somehow, throwing out the previously stored column names.
I would like to create an non pre-defined filtering options for a table within Shiny. The user can select a column and filter a table choosing different categorical variables within that column. It is possible to add additional selection fields by pressing the 'Add' button.
the UI:
library(shiny)
library(shinydashboard)
library(dplyr)
ui <- shinyUI(
pageWithSidebar(
headerPanel("testing of dynamic number of selection"),
sidebarPanel(
uiOutput("buttons")),
mainPanel(
uiOutput("drops")
,tableOutput("table")
)
))
The server:
A table (test.csv) is automatically stored in a reactive values and a first searching field appears with 3 buttons (Add = to add a new searching field by reading in the colnames and a multiselect that stores the unique variables from that columns. The filtering function is activated by the Calculate button)
server<-function(input, output, session) {
###### read in test file
values<-reactiveValues(number = 1,
upload = NULL,
input = NULL)
values$upload<-read.csv("test.csv")
#just the "add" button, in this instance it shouldn't be a uiOutput
output$buttons <- renderUI({
div(
actionButton(inputId = "add", label = "Add"), actionButton(inputId = "calc", label = "Calculate"),
actionButton(inputId = "new", label = "new table")
)
})
#pressing the add button
observeEvent(input$add, {
cat("i adding a new record\n")
values$number <- values$number + 1L })
daStuff <- function(i){
inputName<-paste0("drop", i)
inputName2<-paste0("select", i)
inputText<-if(values$number>0){input[[paste0("drop",i)]]}else{F} # previously selected value for dropdown
inputSelect <- if(values$number>1){input[[paste0("select",i)]]}else{F} # previously selected value for dropdown
fluidRow(
column(6,selectInput(inputName, inputName, c(colnames(values$upload)), selected = inputText)),
column(6,selectInput(inputName2, inputName2,
na.omit(unique(as.vector(values$upload[,input[[paste0("drop",i)]]]))),
multiple=TRUE, selectize=TRUE, selected=inputSelect)) )}
output$drops<- renderUI({
lapply(seq_len(values$number), daStuff)})
By pressing the Calculate button, the uploaded table is subjected to filtering, depending on the selected unique values and shown in the output$table
observeEvent(input$calc, {
values$input<-NULL
for (i in 1:values$number){
if(!is.null(input[[paste0("select",i)]])){
if(is.null(values$input)){
values$input<- filter(values$upload,values$upload[,input[[paste0("drop",i)]]] %in% input[[paste0("select",i)]])}
else{
values$input<- filter(values$input,values$input[,input[[paste0("drop",i)]]] %in% input[[paste0("select",i)]])}
} }
if (is.null(values$input)){values$input<-values$upload}
output$table <- renderTable({values$input})
})
My problem is when I upload a new table (test2.csv), I don't know how to erase the previously stored selections (drop* and select* values) and gives back an error message.
observeEvent(input$new,{
values$upload<-read.csv("test2.csv")
})
}
shinyApp(ui=ui, server = server)
I suppose I should stop somehow the lapply loop and restart it over, so the previously stored values are replaced depending on the new selection, but I am a bit stuck on how I could achieve that.
Just in case you might still be looking for solutions, I wanted to share something that was similar and could potentially be adapted for your needs.
This uses observeEvent for all select inputs. If it detects any changes, it will update all inputs, including the possibilities for select based on drop.
In addition, when a new file is read, the selectInput for drop and select are reset to first value.
Edit: I forgot to keep selected = input[[paste0("drop",i)]] in place for the dropdown (see revised code). It seems to keep the values now when new filters are added - let me know if this is what you had in mind.
library(shiny)
library(shinydashboard)
library(dplyr)
myDataFrame <- read.csv("test.csv")
ui <- shinyUI(
pageWithSidebar(
headerPanel("Testing of dynamic number of selection"),
sidebarPanel(
fileInput("file1", "Choose file to upload", accept = ".csv"),
uiOutput("buttons")
),
mainPanel(
uiOutput("inputs"),
tableOutput("table")
)
)
)
server <- function(input, output, session) {
myInputs <- reactiveValues(rendered = c(1))
myData <- reactive({
inFile <- input$file1
if (is.null(inFile)) {
d <- myDataFrame
} else {
d <- read.csv(inFile$datapath)
}
d
})
observeEvent(lapply(paste0("drop", myInputs$rendered), function(x) input[[x]]), {
for (i in myInputs$rendered) {
updateSelectInput(session,
paste0('select', i),
choices = myData()[input[[paste0('drop', i)]]],
selected = input[[paste0("select",i)]])
}
})
output$buttons <- renderUI({
div(
actionButton(inputId = "add", label = "Add"),
actionButton(inputId = "calc", label = "Calculate")
)
})
observeEvent(input$add, {
myInputs$rendered <- c(myInputs$rendered, max(myInputs$rendered)+1)
})
observeEvent(input$calc, {
showData <- NULL
for (i in 1:length(myInputs$rendered)) {
if(!is.null(input[[paste0("select",i)]])) {
if(is.null(showData)) {
showData <- filter(myData(), myData()[,input[[paste0("drop",i)]]] %in% input[[paste0("select",i)]])
}
else {
showData <- filter(showData, showData[,input[[paste0("drop",i)]]] %in% input[[paste0("select",i)]])
}
}
}
if (is.null(showData)) { showData <- myData() }
output$table <- renderTable({showData})
})
observe({
output$inputs <- renderUI({
rows <- lapply(myInputs$rendered, function(i){
fluidRow(
column(6, selectInput(paste0('drop',i),
label = "",
choices = colnames(myData()),
selected = input[[paste0("drop",i)]])),
column(6, selectInput(paste0('select',i),
label = "",
choices = myData()[1],
multiple = TRUE,
selectize = TRUE))
)
})
do.call(shiny::tagList, rows)
})
})
}
shinyApp(ui, server)