I have successfully updated UI dynamically through renderUI(). I have a long list of inputs to choose from. The check boxes are used to dynamically add numeric inputs. So, to implement this, I used lapply. However, I have used values of selected check boxes in checkboxgroup itself to populate IDs of the dynamically added numerical input instead of using paste(input, i) in lapply.
ui code snippet :
checkboxGroupInput(inputId = "checkboxgrp", label = "Select types",
choices = list("ELECTAPP","NB W $","PUR","MANUAL LTR","REDEMPTION","NB W TRANSFER","NB WOUT $","OUTPUT")),
...
fluidRow(column(12, verbatimTextOutput("value")))
...
uiOutput("numerics")
server code snippet :
renderUI({
numInputs <- length(input$checkboxgrp)
if(numInputs==0){
wellPanel("No transaction selected")
}
else{
lapply(1:numInputs, function(i){
x[i]=input$checkboxgrp[i]
list(numericInput(input$checkboxgrp[i], min = 0, label = input$checkboxgrp[i],
value= input[[x[i]]] ))
})
}
})
output$value <- renderPrint({
numInputs <- length(input$checkboxgrp)
lapply(1:numInputs, function(i){
print(input[[x[i]]]) ## ERROR
})
})
I have used input[[x[i]]] as to instantiate value to be retained after adding or removing a numeric input. But, I want to extract values from input$x[i] or input[[x[i]]] into a vector for further use which I'm unable to do.
*ERROR:Must use single string to index into reactivevalues
Any help is appreciated.
EDIT
using 3 different ways of extracting values from input generate 3 different errors:
Using print(input$x[i]) # ERROR
NULL
NULL
NULL
NULL
[[1]]
NULL
[[2]]
NULL
[[3]]
NULL
[[4]]
NULL
Using print(input[[x[i]]]) # ERROR
Must use single string to index into reactivevalues
Using print('$'(input, x[i])) # ERROR
invalid subscript type 'language'
If I understand you correctly, you want to access values of dynamically generated widgets and then just print them out.
In my example below, which should be easy to generalise, the choices are the levels of the variable Setosa from the iris dataset.
The IDs of the generated widgets are always given by the selected values in checkboxGroupInput. So, input$checkboxgrp says to shiny for which level of setosa there should be generated a widget. At the same time input$checkboxgrp gives IDs of generated widgets. That's why you don't need to store the IDs of "active" widgets in other variable x (which is probably a reactive value).
To print the values out you can do the following:
output$value <- renderPrint({
activeWidgets <- input$checkboxgrp
for (i in activeWidgets) {
print(paste0(i, " = ", input[[i]]))
}
})
This line print(input[[x[i]]]) ## ERROR yields an error because x[i] (whatever it is) is not a vector with a single value but with multiple values.
Full example:
library(shiny)
ui <- fluidPage(
titlePanel("Old Faithful Geyser Data"),
sidebarLayout(
sidebarPanel(
checkboxGroupInput("checkboxgrp", "levels", levels(iris$Species))
),
mainPanel(
fluidRow(
column(6, uiOutput("dynamic")),
column(6, verbatimTextOutput("value"))
)
)
)
)
server <- function(input, output) {
output$dynamic <- renderUI({
numInputs <- length(input$checkboxgrp)
if(numInputs==0){
wellPanel("No transaction selected")
}
else{
lapply(1:numInputs, function(i){
x[i]=input$checkboxgrp[i]
list(numericInput(input$checkboxgrp[i], min = 0, label = input$checkboxgrp[i],
value= input[[x[i]]] ))
})
}
})
output$value <- renderPrint({
activeWidgets <- input$checkboxgrp
for (i in activeWidgets) {
print(paste0(i, " = ", input[[i]]))
}
})
}
shinyApp(ui = ui, server = server)
Edit:
You could tweak the lapply part a little bit (mind <<- operator :) )
else{
activeWidgets <- input$checkboxgrp
val <- 0
lapply(activeWidgets, function(i){
val <<- val + 1
list(numericInput(i, min = 0, label = i,
value = val ))
})
}
Edit 2 In response to a comment:
server <- function(input, output) {
output$dynamic <- renderUI({
numInputs <- length(input$checkboxgrp)
if(numInputs==0){
wellPanel("No transaction selected")
}
else{
activeWidgets <- input$checkboxgrp
val <- 0
lapply(activeWidgets, function(i){
val <<- val + 1
list(numericInput(i, min = 0, label = i,
value = val ))
})
}
})
allChoices <- reactive({
# Require that all input$checkboxgrp and
# the last generated numericInput are available.
# (If the last generated numericInput is available (is not NULL),
# then all previous are available too)
# "eval(parse(text = paste0("input$", input$checkboxgrp))))" yields
# a value of the last generated numericInput.
# In this way we avoid multiple re-evaulation of allChoices()
# and errors
req(input$checkboxgrp, eval(parse(text = paste0("input$", input$checkboxgrp))))
activeWidgets <- input$checkboxgrp
res <- numeric(length(activeWidgets))
names(res) <- activeWidgets
for (i in activeWidgets) {
res[i] <- input[[i]]
}
res
})
output$value <- renderPrint({
print(allChoices())
})
}
Related
I'm currently trying to develop a large application using modules. One of those module is used to filter a dataset where the user can first select the columns he wants to filter. Once he selects the columns, the user can then select the values for each column.
As it is a two steps process, the option to select the values is not available while no columns have been chosen.
Now, my issue is that when the selectInput used to select values is first generated its value on the server side does not seem to update to the default selection.
Here's an example of what I'm trying to do:
Module UI
filter_ui <- function(id){
ns <- NS(id)
tagList(
uiOutput(outputId = ns("filter")),
uiOutput(outputId = ns("value"))
)
}
Module Server
filter_server <- function(id){
moduleServer( id, function(input, output, session){
ns <- session$ns
mod_values <- reactiveValues()
output$filter <- renderUI({
selectInput(inputId = ns("filter"),
label = "Filter",
multiple = TRUE,
selected = NULL,
choices = list("variable_a",
"variable_b",
"variable_c"))
})
observeEvent(input$filter, {
output$value <- renderUI({
lapply(input$filter, function(i){
selectInput(inputId = ns(i),
label = paste0("Select ",i),
multiple = FALSE,
choices = list("1",
"2",
"3"))
})
})
mod_values$filter <- input$filter
for (j in input$filter) {
mod_values$values[[paste0(j)]] <- input[[paste0(j)]]
}
})
return(mod_values)
})
}
The reason why I'm using uiOutput instead of just a regular selectInput in the UI is because in the application there are other arguments that will influence what is rendered.
App
ui <- function() {
fluidPage(
filter_ui("filter")
)
}
server <- function(input, output, session) {
filter_value <- filter_server("filter")
variable <- reactive({filter_value$filter})
value <- reactive({filter_value$values})
observeEvent(variable(), {
print(value())
print(variable())
req(value())
n <- 0
for (i in variable()) {
n <- n + 1
print(paste0("the ", n, "th loop value is ", value()[[i]]))
}
})
}
shinyApp(ui, server)
Now, the first time I select any filter the value does not update and I get for example:
[1] "variable_a" "variable_c"
[1] "the 1th loop value is 1"
[1] "the 2th loop value is "
While I need:
[1] "variable_a" "variable_c"
[1] "the 1th loop value is 1"
[1] "the 2th loop value is 1"
I guess my issue comes from a wrong use of reactivity but I can't seem to find what. Any help would be greatly appreciated!
Consider the following shiny app. There are three basic inputs, that the user can change: A, M, and S. The "content" C (in the verbatimTextOuput on the right) depends directly on A and S.
S can be changed in two ways: by the user, or by changing M/A. If the user changes S, then the dependency on M is irrelevant. M is also not used if it is empty.
The situation is depicted in the diagram below.
The problem is when M is not blank and A is changed:
C gets updated based on the old S and new A
S gets updated based on M and the new A
C gets updated based on the new S and new A.
Thus, C gets updated twice, the first time with an invalid value.
What I want to happen is for S to update, based on the new A, then C to update based on the new S and new A.
To see the problem, run the app, then:
Put something in the M box
Change A
Observe that the C is changed twice.
How can I block the first update?
Thanks!
Shiny app code:
library(shiny)
library(digest)
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
textInput("M", "M:", ""),
textInput("S", "S:", "testS"),
selectInput("A", "A:", c("A1","A2"))
),
mainPanel(
verbatimTextOutput("C")
)
)
)
server <- function(input, output, session) {
# Count calculations of C
count = 0
# Make reactive so we can modify the value
# in the input box (inpt$S is an input and output,
# essentially)
S <- reactive({
input$S
})
# Create "content" from A and S
C <- reactive({
count <<- count + 1
Sys.sleep(0.5)
message("Count ", count)
paste(
"Count: ", count, "\n", digest::sha1( c(input$A, S()) )
)
})
# When M changes, we need to change S based on A and M
# OR set S to a default value
observeEvent(input$M, {
# If user gets rid of M, reset S to default
if(input$M == ""){
S = "testS"
}else{
S = digest::sha1(c(input$M,input$A))
}
# Update the input to new S
updateTextInput(
session,
"S",
value = S
)
})
# When A changes, we need to change S based on A and M
# OR if M is blank, do nothing (S doesn't depend on M if M is blank)
observeEvent(input$A, {
# If there's no M, don't use it
if(input$M == "") return()
# Update the input to new S
updateTextInput(
session,
"S",
value = digest::sha1(c(input$M,input$A))
)
})
# "Content"
output$C <- renderText({
C()
})
}
shinyApp(ui = ui, server = server)
This should work (if I've understood the logic of your function). It has a bunch of extra messages so you can see what is updated by when and in what order.
(I also changed the superassignment of count because those just bug me, but I get the it's a little awkward with the isolate, so feel free to put it back ;)
library(shiny)
library(digest)
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
textInput("M", "M:", ""),
textInput("S", "S:", "testS"),
selectInput("A", "A:", c("A1","A2"))
),
mainPanel(
verbatimTextOutput("C")
)
)
)
server <- function(input, output, session) {
# Count calculations of C
count = reactiveVal(0)
S = reactiveVal("testS")
observeEvent(input$S, { message("S updated externally")
S(input$S)
})
# When M changes, we need to change S based on A and M
# OR set S to a default value
observeEvent(input$M, { message("M updated")
# If user gets rid of M, reset S to default
if (input$M == ""){
S("testS")
} else {
S(digest::sha1(c(input$M, input$A)))
}
# Update the input to new S
updateTextInput(inputId = "S", value = S())
message("S updated by M")
})
# When A changes, we need to change S based on A and M
# OR if M is blank, do nothing (S doesn't depend on M if M is blank)
observeEvent(input$A, { message("A updated")
# If there's no M, don't use it
req(input$M)
# Update the input to new S
S(digest::sha1(c(input$M, input$A)))
updateTextInput(inputId = "S", value = S())
message("S updated by A")
})
# "Content"
output$C <- renderText({
n = isolate(count()) + 1
count(n)
#Sys.sleep(0.5)
message("Count ", n)
paste("Count: ", n, "\n", digest::sha1( c(input$A, S())))
})
}
shinyApp(ui = ui, server = server)
The S() reactiveVal updates when the user changes input$S externally or internally by input$M or input$A. The comments show which of those changes the value and output$C only changes when input$A or the S() change.
I think the issue here is that you are using observers when you should use reactives. In general you only want to use observers for side effects (saving a file, pushing a button) not when you want a value in the app. Here I think it's better to use renderUI to generate the UI element reactively rather than updating it with the observer.
library(shiny)
library(digest)
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
textInput("M", "M:", ""),
uiOutput("S_UI"),
selectInput("A", "A:", c("A1","A2"))
),
mainPanel(
verbatimTextOutput("C")
)
)
)
server <- function(input, output, session) {
# Count calculations of C
count = 0
# Create "content" from A and S
C <- reactive({
count <<- count + 1
Sys.sleep(0.5)
message("Count ", count)
paste(
"Count: ", count, "\n", digest::sha1( c(input$A, input$S ))
)
})
output$S_UI <- renderUI({
if (input$M == "") {
val <- "testS"
} else {
val <- "S"
}
return(textInput("S", "S:", val))
})
# "Content"
output$C <- renderText({
C()
})
}
shinyApp(ui = ui, server = server)
I am trying to build a Shiny interface with:
a main selector, which decides:
which submenu (input) to show, which decides:
how many subsequent inputs to show
Here's a minimal reproducible example.
If "First" is chosen from the main selector, then a submenu with two possibilities [1,2] exist. These possibilities result in 1 or 2 subsequent inputs being built. So these possibilities:
If "Second" is chosen from the main selector, then a submenu with two possibilities [3,4] exist. These possibilities result in 3 or 4 subsequent inputs being built.
ui <- fluidPage(
radioButtons(inputId="main_selector",label=h5('Select menu'),
choices = list('First','Second'),selected='First'),
uiOutput("ui_selected")
)
server <- function(input, output, session) {
build_inputs <- function(choices){
output = tagList()
for(i in 1:choices){
output[[i]] = tagList()
output[[i]][[1]] = numericInput(inputId = paste0(i),
label = paste0(i),
value = i)
}
}
# Are these reactive elements necessary? Should they be in the renderUI below?
first_submenu <- reactive({
input$first_submenu
})
second_submenu <- reactive({
input$second_submenu
})
output$ui_selected <- renderUI({
if (input$main_selector == 'First'){
selectInput(inputId = "first_submenu", label="First submenu",
choices=list(1,2))
choices_1 <- first_submenu()
# Build a list of inputs dependent on the choice above
output <- build_inputs(choices_1)
} else if (input$main_selector == 'Second'){
selectInput(inputId = "second_submenu", label="Second submenu",
choices=list(3,4))
choices_2 <- second_submenu()
# Build a list of inputs dependent on the choice above
output <- build_inputs(choices_2)
# Return output as output$ui_selected element
output
})
}
shinyApp(ui, server)
The error I receive is Warning: Error in :: argument of length 0. I believe this is because you can't call the outcome of first_submenu from the renderUI element - but I don't know how to structure my code correctly.
I am not sure whether this is what you are after. The main problem was that your function build_inputs does not return anything. The second problem is that choices from selectInput are not numeric, so you need to convert them beforehand. And one other minor problem, related to the error you mention, is that the elements you want to render exist at the same time, so putting a condition on input$first_submenu will trigger errors (even if it is NULL for a couple of milliseconds), so it's (almost always) good practice to take care of possibly null inputs. The last thing I did was to add another uiOutput for the last layer of dynamic inputs. Hope this helps.
ui <- fluidPage(
radioButtons(inputId="main_selector",label=h5('Select menu'),
choices = list('First','Second'),selected='First'),
uiOutput("ui_selected"),
uiOutput("ui_numeric_inputs")
)
server <- function(input, output, session) {
build_inputs <- function(choices) {
output = tagList()
for(i in 1:choices){
output[[i]] = tagList()
output[[i]][[1]] = numericInput(inputId = paste0(i),
label = paste0(i),
value = i)
}
return(output)
}
output$ui_selected <- renderUI({
if (input$main_selector == 'First'){
selectInput(inputId = "first_submenu", label="First submenu",
choices=c(1,2))
} else if (input$main_selector == 'Second'){
selectInput(inputId = "second_submenu", label="Second submenu",
choices=list(3,4))
}
})
output$ui_numeric_inputs <- renderUI({
if (input$main_selector == 'First' &&
(!is.null(input$first_submenu))) {
build_inputs(as.numeric(input$first_submenu))
} else if (input$main_selector == 'Second' &&
(!is.null(input$second_submenu))){
build_inputs(as.numeric(input$second_submenu))
}
})
}
shinyApp(ui, server)
The goal
I am working on a Shiny app that allows the user to upload their own data and focus on the entire data or a subset by providing data filtering widgets described by the below graph
The select input "Variable 1" will display all the column names of the data uploaded by the user and the selectize input "Value" will display all the unique values of the corresponding column selected in "Variable 1". Ideally, the user will be able to add as many such rows ("Variable X" + "Value") as possible by some sort of trigger, one possibility being clicking the "Add more" action button.
A possible solution
After looking up online, I've found one promising solution given by Nick Carchedi pasted below
ui.R
library(shiny)
shinyUI(pageWithSidebar(
# Application title
headerPanel("Dynamically append arbitrary number of inputs"),
# Sidebar with a slider input for number of bins
sidebarPanel(
uiOutput("allInputs"),
actionButton("appendInput", "Append Input")
),
# Show a plot of the generated distribution
mainPanel(
p("The crux of the problem is to dynamically add an arbitrary number of inputs
without resetting the values of existing inputs each time a new input is added.
For example, add a new input, set the new input's value to Option 2, then add
another input. Note that the value of the first input resets to Option 1."),
p("I suppose one hack would be to store the values of all existing inputs prior
to adding a new input. Then,", code("updateSelectInput()"), "could be used to
return inputs to their previously set values, but I'm wondering if there is a
more efficient method of doing this.")
)
))
server.R
library(shiny)
shinyServer(function(input, output) {
# Initialize list of inputs
inputTagList <- tagList()
output$allInputs <- renderUI({
# Get value of button, which represents number of times pressed
# (i.e. number of inputs added)
i <- input$appendInput
# Return if button not pressed yet
if(is.null(i) || i < 1) return()
# Define unique input id and label
newInputId <- paste0("input", i)
newInputLabel <- paste("Input", i)
# Define new input
newInput <- selectInput(newInputId, newInputLabel,
c("Option 1", "Option 2", "Option 3"))
# Append new input to list of existing inputs
inputTagList <<- tagAppendChild(inputTagList, newInput)
# Return updated list of inputs
inputTagList
})
})
The downside
As pointed by Nick Carchedi himself, all the existing input widgets will undesirably get reset every time when a new one is added.
A promising solution for data subsetting/filtering in Shiny
As suggested by warmoverflow, the datatable function in DT package provides a nice way to filter the data in Shiny. See below a minimal example with data filtering enabled.
library(shiny)
shinyApp(
ui = fluidPage(DT::dataTableOutput('tbl')),
server = function(input, output) {
output$tbl = DT::renderDataTable(
iris, filter = 'top', options = list(autoWidth = TRUE)
)
}
)
If you are going to use it in your Shiny app, there are some important aspects that are worth noting.
Filtering box type
For numeric/date/time columns: range sliders are used to filter rows within ranges
For factor columns: selectize inputs are used to display all possible categories
For character columns: ordinary search boxes are used
How to obtain the filtered data
Suppose the table output id is tableId, use input$tableId_rows_all as the indices of rows on all pages (after the table is filtered by the search strings). Please note that input$tableId_rows_all returns the indices of rows on all pages for DT (>= 0.1.26). If you use the DT version by regular install.packages('DT'), only the indices of the current page are returned
To install DT (>= 0.1.26), refer to its GitHub page
Column width
If the data have many columns, column width and filter box width will be narrow, which makes it hard to see the text as report here
Still to be solved
Despite some known issues, datatable in DT package stands as a promising solution for data subsetting in Shiny. The question itself, i.e. how to dynamically append arbitrary number of input widgets in Shiny, nevertheless, is interesting and also challenging. Until people find a good way to solve it, I will leave this question open :)
Thank you!
are you looking for something like this?
library(shiny)
LHSchoices <- c("X1", "X2", "X3", "X4")
#------------------------------------------------------------------------------#
# MODULE UI ----
variablesUI <- function(id, number) {
ns <- NS(id)
tagList(
fluidRow(
column(6,
selectInput(ns("variable"),
paste0("Select Variable ", number),
choices = c("Choose" = "", LHSchoices)
)
),
column(6,
numericInput(ns("value.variable"),
label = paste0("Value ", number),
value = 0, min = 0
)
)
)
)
}
#------------------------------------------------------------------------------#
# MODULE SERVER ----
variables <- function(input, output, session, variable.number){
reactive({
req(input$variable, input$value.variable)
# Create Pair: variable and its value
df <- data.frame(
"variable.number" = variable.number,
"variable" = input$variable,
"value" = input$value.variable,
stringsAsFactors = FALSE
)
return(df)
})
}
#------------------------------------------------------------------------------#
# Shiny UI ----
ui <- fixedPage(
verbatimTextOutput("test1"),
tableOutput("test2"),
variablesUI("var1", 1),
h5(""),
actionButton("insertBtn", "Add another line")
)
# Shiny Server ----
server <- function(input, output) {
add.variable <- reactiveValues()
add.variable$df <- data.frame("variable.number" = numeric(0),
"variable" = character(0),
"value" = numeric(0),
stringsAsFactors = FALSE)
var1 <- callModule(variables, paste0("var", 1), 1)
observe(add.variable$df[1, ] <- var1())
observeEvent(input$insertBtn, {
btn <- sum(input$insertBtn, 1)
insertUI(
selector = "h5",
where = "beforeEnd",
ui = tagList(
variablesUI(paste0("var", btn), btn)
)
)
newline <- callModule(variables, paste0("var", btn), btn)
observeEvent(newline(), {
add.variable$df[btn, ] <- newline()
})
})
output$test1 <- renderPrint({
print(add.variable$df)
})
output$test2 <- renderTable({
add.variable$df
})
}
#------------------------------------------------------------------------------#
shinyApp(ui, server)
Now, I think that I understand better the problem.
Suppose the user selects the datasets::airquality dataset (here, I'm showing only the first 10 rows):
The field 'Select Variable 1' shows all the possible variables based on the column names of said dataset:
Then, the user selects the condition and the value to filter the dataset by:
Then, we want to add a second filter (still maintaining the first one):
Finally, we get the dataset filtered by the two conditions:
If we want to add a third filter:
You can keep adding filters until you run out of data.
You can also change the conditions to accommodate factors or character variables. All you need to do is change the selectInput and numericInput to whatever you want.
If this is what you want, I've solved it using modules and by creating a reactiveValue (tmpFilters) that contains all selections (variable + condition + value). From it, I created a list with all filters (tmpList) and from it I created the proper filter (tmpListFilters) to use with subset.
This works because the final dataset is "constantly" being subset by this reactiveValue (the tmpFilters). At the beginning, tmpFilters is empty, so we get the original dataset. Whenever the user adds the first filter (and other filters after that), this reactiveValue gets updated and so does the dataset.
Here's the code for it:
library(shiny)
# > MODULE #####################################################################
## |__ MODULE UI ===============================================================
variablesUI <- function(id, number, LHSchoices) {
ns <- NS(id)
tagList(
fluidRow(
column(
width = 4,
selectInput(
inputId = ns("variable"),
label = paste0("Select Variable ", number),
choices = c("Choose" = "", LHSchoices)
)
),
column(
width = 4,
selectInput(
inputId = ns("condition"),
label = paste0("Select condition ", number),
choices = c("Choose" = "", c("==", "!=", ">", ">=", "<", "<="))
)
),
column(
width = 4,
numericInput(
inputId = ns("value.variable"),
label = paste0("Value ", number),
value = NA,
min = 0
)
)
)
)
}
## |__ MODULE SERVER ===========================================================
filter <- function(input, output, session){
reactive({
req(input$variable, input$condition, input$value.variable)
fullFilter <- paste0(
input$variable,
input$condition,
input$value.variable
)
return(fullFilter)
})
}
# Shiny ########################################################################
## |__ UI ======================================================================
ui <- fixedPage(
fixedRow(
column(
width = 5,
selectInput(
inputId = "userDataset",
label = paste0("Select dataset"),
choices = c("Choose" = "", ls("package:datasets"))
),
h5(""),
actionButton("insertBtn", "Add another filter")
),
column(
width = 7,
tableOutput("finalTable")
)
)
)
## |__ Server ==================================================================
server <- function(input, output) {
### \__ Get dataset from user selection ------------------------------------
originalDF <- reactive({
req(input$userDataset)
tmpData <- eval(parse(text = paste0("datasets::", input$userDataset)))
if (!class(tmpData) == "data.frame") {
stop("Please select a dataset of class data.frame")
}
tmpData
})
### \__ Get the column names -----------------------------------------------
columnNames <- reactive({
req(input$userDataset)
tmpData <- eval(parse(text = paste0("datasets::", input$userDataset)))
names(tmpData)
})
### \__ Create Reactive Filter ---------------------------------------------
tmpFilters <- reactiveValues()
### \__ First UI Element ---------------------------------------------------
### Add first UI element with column names
observeEvent(input$userDataset, {
insertUI(
selector = "h5",
where = "beforeEnd",
ui = tagList(variablesUI(paste0("var", 1), 1, columnNames()))
)
})
### Update Reactive Filter with first filter
filter01 <- callModule(filter, paste0("var", 1))
observe(tmpFilters[['1']] <- filter01())
### \__ Other UI Elements --------------------------------------------------
### Add other UI elements with column names and update the filter
observeEvent(input$insertBtn, {
btn <- sum(input$insertBtn, 1)
insertUI(
selector = "h5",
where = "beforeEnd",
ui = tagList(variablesUI(paste0("var", btn), btn, columnNames()))
)
newFilter <- callModule(filter, paste0("var", btn))
observeEvent(newFilter(), {
tmpFilters[[paste0("'", btn, "'")]] <- newFilter()
})
})
### \__ Dataset with Filtered Results --------------------------------------
resultsFiltered <- reactive({
req(filter01())
tmpDF <- originalDF()
tmpList <- reactiveValuesToList(tmpFilters)
if (length(tmpList) > 1) {
tmpListFilters <- paste(tmpList, "", collapse = "& ")
} else {
tmpListFilters <- unlist(tmpList)
}
tmpResult <- subset(tmpDF, eval(parse(text = tmpListFilters)))
tmpResult
})
### \__ Print the Dataset with Filtered Results ----------------------------
output$finalTable <- renderTable({
req(input$userDataset)
if (is.null(tmpFilters[['1']])) {
head(originalDF(), 10)
} else {
head(resultsFiltered(), 10)
}
})
}
#------------------------------------------------------------------------------#
shinyApp(ui, server)
# End
If you are looking for a data subsetting/filtering in Shiny Module :
filterData from package shinytools can do the work. It returns an expression as a call but it can also return the data (if your dataset is not too big).
library(shiny)
# remotes::install_github("ardata-fr/shinytools")
library(shinytools)
ui <- fluidPage(
fluidRow(
column(
3,
filterDataUI(id = "ex"),
actionButton("AB", label = "Apply filters")
),
column(
3,
tags$strong("Expression"),
verbatimTextOutput("expression"),
tags$br(),
DT::dataTableOutput("DT")
)
)
)
server <- function(input, output) {
x <- reactive({iris})
res <- callModule(module = filterDataServer, id = "ex", x = x, return_data = FALSE)
output$expression <- renderPrint({
print(res$expr)
})
output$DT <- DT::renderDataTable({
datatable(data_filtered())
})
data_filtered <- eventReactive(input$AB, {
filters <- eval(expr = res$expr, envir = x())
x()[filters,]
})
}
shinyApp(ui, server)
You can also use lazyeval or rlang to evaluate the expression :
filters <- lazyeval::lazy_eval(res$expr, data = x())
filters <- rlang::eval_tidy(res$expr, data = x())
You need to check for existing input values and use them if available:
# Prevent dynamic inputs from resetting
newInputValue <- "Option 1"
if (newInputId %in% names(input)) {
newInputValue <- input[[newInputId]]
}
# Define new input
newInput <- selectInput(newInputId, newInputLabel, c("Option 1", "Option 2", "Option 3"), selected=newInputValue)
A working version of the gist (without the reset problem) can be found here: https://gist.github.com/motin/0d0ed0d98fb423dbcb95c2760cda3a30
Copied below:
ui.R
library(shiny)
shinyUI(pageWithSidebar(
# Application title
headerPanel("Dynamically append arbitrary number of inputs"),
# Sidebar with a slider input for number of bins
sidebarPanel(
uiOutput("allInputs"),
actionButton("appendInput", "Append Input")
),
# Show a plot of the generated distribution
mainPanel(
p("This shows how to add an arbitrary number of inputs
without resetting the values of existing inputs each time a new input is added.
For example, add a new input, set the new input's value to Option 2, then add
another input. Note that the value of the first input does not reset to Option 1.")
)
))
server.R
library(shiny)
shinyServer(function(input, output) {
output$allInputs <- renderUI({
# Get value of button, which represents number of times pressed (i.e. number of inputs added)
inputsToShow <- input$appendInput
# Return if button not pressed yet
if(is.null(inputsToShow) || inputsToShow < 1) return()
# Initialize list of inputs
inputTagList <- tagList()
# Populate the list of inputs
lapply(1:inputsToShow,function(i){
# Define unique input id and label
newInputId <- paste0("input", i)
newInputLabel <- paste("Input", i)
# Prevent dynamic inputs from resetting
newInputValue <- "Option 1"
if (newInputId %in% names(input)) {
newInputValue <- input[[newInputId]]
}
# Define new input
newInput <- selectInput(newInputId, newInputLabel, c("Option 1", "Option 2", "Option 3"), selected=newInputValue)
# Append new input to list of existing inputs
inputTagList <<- tagAppendChild(inputTagList, newInput)
})
# Return updated list of inputs
inputTagList
})
})
(The solution was guided on Nick's hints in the original gist from where you got the code of the promising solution)
So I asked the following, R Shiny Dynamic Input, a couple of days ago and although the answer is correct given the question, I now want to elaborate some more since I am unable to edit the code given to answer my new question. So originally I wanted to be able to ask the user to specify a number, say k, that would then dynamically generate k fields for the user to fill out. Now, the code given assumes that the output is a numeric, however, I want the user to be able to specify a vector of 5 values in each of the 1,...,k fields. Since, after specifying k, the inputs are going to be k vectors of length 5 of numerical values, I want to be able to store these values in a k by 5 matrix. That way I can use those values to conduct data manipulations later. If it helps, here is the code from the original answer:
library(shiny)
ui <- shinyUI(fluidPage(
titlePanel("Old Faithful Geyser Data"),
sidebarLayout(
sidebarPanel(
numericInput("numInputs", "How many inputs do you want", 4),
# place to hold dynamic inputs
uiOutput("inputGroup")
),
# this is just a demo to show the input values
mainPanel(textOutput("inputValues"))
)
))
# Define server logic required to draw a histogram
server <- shinyServer(function(input, output) {
# observe changes in "numInputs", and create corresponding number of inputs
observeEvent(input$numInputs, {
output$inputGroup = renderUI({
input_list <- lapply(1:input$numInputs, function(i) {
# for each dynamically generated input, give a different name
inputName <- paste("input", i, sep = "")
numericInput(inputName, inputName, 1)
})
do.call(tagList, input_list)
})
})
# this is just a demo to display all the input values
output$inputValues <- renderText({
paste(lapply(1:input$numInputs, function(i) {
inputName <- paste("input", i, sep = "")
input[[inputName]]
}))
})
})
# Run the application
shinyApp(ui = ui, server = server)
Edit
Here is updated code that still doesn't completely work:
library(shiny)
ui <- shinyUI(fluidPage(
titlePanel("Old Faithful Geyser Data"),
sidebarLayout(
sidebarPanel(
numericInput("numInputs", "How many inputs do you want", 4),
# place to hold dynamic inputs
uiOutput("inputGroup")
),
# this is just a demo to show the input values
mainPanel(tableOutput("inputValues"))
)
))
# Define server logic required to draw a histogram
server <- shinyServer(function(input, output) {
# observe changes in "numInputs", and create corresponding number of inputs
observeEvent(input$numInputs, {
output$inputValues <- renderTable({
all <- paste(lapply(1:input$numInputs, function(i) {
inputName <- paste("input", i, sep = "")
input[[inputName]]
}))
matrix <- as.matrix(all, ncol=5)
as.data.frame(matrix)
})
})
# this is just a demo to display all the input values
output$inputValues <- renderText({
paste(lapply(1:input$numInputs, function(i) {
inputName <- paste("input", i, sep = "")
input[[inputName]]
}))
})
})
# Run the application
shinyApp(ui = ui, server = server)
You only need to make a few changes:
Change mainPanel(textOutput("inputValues")) to mainPanel(tableOutput("inputValues")) (this is not essential, it just shows the values in a table/matrix format so you can see them)
Change numericInput(inputName, inputName, 1) to textInput(inputName, inputName, "1 2 3 4 5")
Change output$inputValues <- renderText({...... to
output$inputValues <- renderTable({
all <- paste(lapply(1:input$numInputs, function(i) {
inputName <- paste("input", i, sep = "")
input[[inputName]]
}))
matrix = as.matrix(read.table(text=all))
data.frame(matrix)
})
matrix is what you want: a k by 5 matrix.
Note that I did not do any input verification. It is assumed that user will enter 5 numbers in each input separated by spaces. If they do not, output might be either wrong or you'll see an error. You may need to implement some input checking here to ensure that it is 5 numbers and not anything else.
Complete code
library(shiny)
ui <- shinyUI(fluidPage(
titlePanel("Old Faithful Geyser Data"),
sidebarLayout(
sidebarPanel(
numericInput("numInputs", "How many inputs do you want", 4),
# place to hold dynamic inputs
uiOutput("inputGroup")
),
# this is just a demo to show the input values
mainPanel(tableOutput("inputValues"))
)
))
# Define server logic required to draw a histogram
server <- shinyServer(function(input, output) {
# observe changes in "numInputs", and create corresponding number of inputs
observeEvent(input$numInputs, {
output$inputGroup = renderUI({
input_list <- lapply(1:input$numInputs, function(i) {
# for each dynamically generated input, give a different name
inputName <- paste("input", i, sep = "")
textInput(inputName, inputName, "1 2 3 4 5")
})
do.call(tagList, input_list)
})
})
# this is just a demo to display all the input values
output$inputValues <- renderTable({
all <- paste(lapply(1:input$numInputs, function(i) {
inputName <- paste("input", i, sep = "")
input[[inputName]]
}))
matrix = as.matrix(read.table(text=all))
data.frame(matrix)
})
})
# Run the application
shinyApp(ui = ui, server = server)