I am writing a shiny app to realize the following effects:
Whenever I choose variable included by categoryname, the web will generate the slider which provides a divider. It divides the selected variable into 2 groups and form a new column containing the group name added to the original data set.
People here helped me solve the problem using conditional panel in this question but now I use renderUI combined with shinyjs cause conditional panel doesn't work in my large project.
I am stuck by a tiny bug (seems):
Error in data.frame: arguments imply differing number of rows: 32, 0
The following is my code, how to change it so that the function works?
library(shiny)
library(shinyjs)
library(stringr)
categoryname = c("mpg_group", "disp_group")
MT_EG = mtcars[,1:5]
# Define UI for application that draws a histogram
ui <- fluidPage(
useShinyjs(),
# Application title
titlePanel("Mtcars Data"),
# Sidebar with a slider input for number of bins
sidebarLayout(
sidebarPanel(
selectInput(inputId = "arm",
label = "ARM VARIABLE",
choices = c("mpg_group", "cyl", "disp_group", "hp", "drat"),
selected = "cyl"),
# conditionalPanel(
# #condition = "categoryname.includes(input.arm)",
# condition = "input.arm == 'disp_group' | input.arm == 'mpg_group'",
#
# #sliderInput("divider", "divide slider", 1, 100, 20)
# optionalSliderInputValMinMax("divider", "divide slider", c(50,0,100), ticks = FALSE)
# )
uiOutput("divider")
),
# Show a plot of the generated distribution
mainPanel(
uiOutput("data")
)
)
)
# Define server logic required to draw a histogram
server <- function(input, output, session) {
output$divider <- renderUI({
if (input$arm %in% categoryname){
show("divider")
}
else{
hide("divider")
}
sliderInput("divider", "divide slider", 0, 100, 50)
})
observeEvent(
input$arm,
observe(
{
if (input$arm %in% categoryname){
#browser()
# start over and remove the former column if exists
MT_EG = MT_EG[, !(colnames(MT_EG) %in% input$arm)]
id_arm_var <- input$arm
id_arm <- unlist(str_split(id_arm_var,'_'))[1]
# change the range of the slider
val <- input$divider
mx = max(MT_EG[[id_arm]])
mn = min(MT_EG[[id_arm]])
updateSliderInput(session, inputId = "divider", min=floor(mn/2),max = mx + 4,step = 1,value = input$divider)
# generate a new column and bind
divi <- data.frame(id_arm_var = MT_EG[[id_arm]]>input$divider)
divi$id_arm_var[divi$id_arm_var==TRUE] <- paste0(id_arm_var, " Larger")
divi$id_arm_var[divi$id_arm_var==FALSE] <- paste0(id_arm_var, " Smaller")
colnames(divi) <- id_arm_var
MT_EG <- cbind(MT_EG,divi)
}
output$data=renderTable(MT_EG)
}
)
)
}
# Run the application
shinyApp(ui = ui, server = server)
I simply use mtcars dataset so that all of you can get access to
observeEvent and renderUI both depend on "or triggered by" input$arm. What happened is observeEvent ask for input$divider before renderUI rendered probably in the UI and input$divider becomes available for observeEvent which as I mentioned above input$divider ends up with value NULL.
To solve this problem just add req(input$divider) before MT_EG = MT_EG[, !(colnames(MT_EG) %in% input$arm)]. Also change output$divider to output$dividerUI since Shiny doesn't allow input and output with the same id.
See ?shiny::req for more details.
How can I update the global variable using observer?
I have an empty species on start:
speciesChoices <- c()
But I want to add values into it when something has changed on the ui, so it becomes:
speciesChoices <- c(
'PM2.5' = 'particles'
)
Is it possible?
My code so far...
ui.r:
speciesOptions <- selectInput(
inputId = "species",
label = "Species:",
choices = c(
# 'PM2.5' = 'particles',
# 'Humidity %' = 'humidity'
)
)
server.r:
speciesChoices <- c() # global variable
# Define server logic required to draw a histogram
shinyServer(function(input, output, session) {
observe({
key <- input$streams1
stream <- fromJSON(paste(server, "/output/stream?public_key=", key, sep=""),flatten=TRUE)
species <- as.data.frame(stream$species)
# Set choices of title and code for select input.
speciesChoices <- setNames(species$code_name, species$public_name)
updateSelectInput(session, "species", choices = speciesChoices)
})
})
It only update the input on the ui but not the speciesChoices on the server.
any ideas?
Use something like speciesChoices <<- setNames(input$species$code_name, input$species$public_name). You need both the super-assign operator <<- to change a global variable, and you need to use input$_id_ to refer to inputs set in the ui.
Side note: I'm not sure what your endgame is here, but make sure that you actually want to be using an observer and not a reactive. For an idea of the difference between these, see Joe Cheng's slides from useR2016.
The goal
I am working on a Shiny app that allows the user to upload their own data and focus on the entire data or a subset by providing data filtering widgets described by the below graph
The select input "Variable 1" will display all the column names of the data uploaded by the user and the selectize input "Value" will display all the unique values of the corresponding column selected in "Variable 1". Ideally, the user will be able to add as many such rows ("Variable X" + "Value") as possible by some sort of trigger, one possibility being clicking the "Add more" action button.
A possible solution
After looking up online, I've found one promising solution given by Nick Carchedi pasted below
ui.R
library(shiny)
shinyUI(pageWithSidebar(
# Application title
headerPanel("Dynamically append arbitrary number of inputs"),
# Sidebar with a slider input for number of bins
sidebarPanel(
uiOutput("allInputs"),
actionButton("appendInput", "Append Input")
),
# Show a plot of the generated distribution
mainPanel(
p("The crux of the problem is to dynamically add an arbitrary number of inputs
without resetting the values of existing inputs each time a new input is added.
For example, add a new input, set the new input's value to Option 2, then add
another input. Note that the value of the first input resets to Option 1."),
p("I suppose one hack would be to store the values of all existing inputs prior
to adding a new input. Then,", code("updateSelectInput()"), "could be used to
return inputs to their previously set values, but I'm wondering if there is a
more efficient method of doing this.")
)
))
server.R
library(shiny)
shinyServer(function(input, output) {
# Initialize list of inputs
inputTagList <- tagList()
output$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$appendInput
# Return if button not pressed yet
if(is.null(inputsToShow) || inputsToShow < 1) return()
# Initialize list of inputs
inputTagList <- tagList()
# Populate the list of inputs
lapply(1:inputsToShow,function(i){
# Define unique input id and label
newInputId <- paste0("input", i)
newInputLabel <- paste("Input", i)
# Prevent dynamic inputs from resetting
newInputValue <- "Option 1"
if (newInputId %in% names(input)) {
newInputValue <- input[[newInputId]]
}
# Define new input
newInput <- selectInput(newInputId, newInputLabel, c("Option 1", "Option 2", "Option 3"), selected=newInputValue)
# Append new input to list of existing inputs
inputTagList <<- tagAppendChild(inputTagList, newInput)
})
# Return updated list of inputs
inputTagList
})
})
(The solution was guided on Nick's hints in the original gist from where you got the code of the promising solution)
I have read this (How do I make the choices in radioButtons reactive in Shiny?) which shows me how to update radioButtons in a reactive way. However, when I try and update two sets of buttons from the same data, only one set renders. Example:
Server:
# Create example data
Wafer <- rep(c(1:3), each=3)
Length <- c(1,1,2,1,1,1,3,5,1)
Width <- c(3,1,6,1,1,1,1,1,6)
dd <- data.frame(Wafer, Length, Width)
shinyServer(function(input, output, session){
# Create reactive dataframe to store data
values <- reactiveValues()
values$df <- data.frame()
# Get Lengths and Widths of wafer from user input
a <- eventReactive(input$do, {
subset(dd, Wafer %in% input$wafer, select = Length:Width)
})
# Update reactive data frame will all Lengths and Widths that have been selected by the user input
observe({
if(!is.null(a())) {
values$df <- rbind(isolate(values$df), a())
}
})
output$wl <- renderDataTable({ a() })
# Update radio buttons with unique Length and Widths stored in values$df
# Which ever "observe" I put first in the code, is the one which updates
# the radio buttons. Cut and paste the other way round and "width"
# updates but not "length" radio buttons
observe({
z <- values$df
updateRadioButtons(session, "length", choices = unique(z$Length), inline=TRUE)
})
observe({
z <- values$df
updateRadioButtons(session, "width", choices = unique(z$Width), inline=TRUE)
})
})
ui:
library(markdown)
shinyUI(fluidPage(
titlePanel("Generic grapher"),
sidebarLayout(
sidebarPanel(
numericInput("wafer", label = h3("Input wafer ID:"), value = NULL),
actionButton("do", "Search wafer"),
radioButtons("length", label="Length", choices=""),
radioButtons("width", label="Width", choices = "")
),
mainPanel(
dataTableOutput(outputId="wl")
)
)
)
)
In the above, radiobuttons do update but only for the first set of buttons in order of code i.e. above "length" updates but "width" doesn't. If I write them in reverse, "width" updates but "length" doesn't. Do I need to define a new session maybe?
It turns out that:
"it's because a JS error occurs if the choices argument isn't a
character vector."
I have posted an issue on Shiny's Github:
https://github.com/rstudio/shiny/issues/1093
This can be resolved by:
To fix your problem, you can either convert your choices to characters
using as.character or set selected to a random string such as "".
See:
Update two sets of radiobuttons - shiny
I asked this question (Update two sets of radiobuttons reactively - shiny) yesterday but perhaps it was too messy to get a response. I have stripped the question down: why can't I get two sets of radiobuttons to update reactively:
server.R:
# Create example data
Wafer <- rep(c(1:3), each=3)
Length <- c(1,1,2,1,1,1,3,5,1)
Width <- c(3,1,6,1,1,1,1,1,6)
dd <- data.frame(Wafer, Length, Width)
shinyServer(function(input, output, session){
# Get Lengths from user input
a <- eventReactive(input$do, {
subset(dd, Wafer %in% input$wafer, select = Length)
})
# Get Widths from user input
b <- eventReactive(input$do, {
subset(dd, Wafer %in% input$wafer, select = Width)
})
#Observe and update first set of radiobuttons based on a(). Does
#render
observe({
z <- a()
updateRadioButtons(session, "length", choices = unique(z$Length), inline=TRUE)
})
#Observe and update second set of radiobuttons based on b(). Does
#not render
observe({
z <- b()
updateRadioButtons(session, "width", choices = unique(z$Width), inline=TRUE)
})
output$l <- renderDataTable({ a() })
output$w <- renderDataTable({ b() })
})
ui.R:
library(markdown)
shinyUI(fluidPage(
titlePanel("Generic grapher"),
sidebarLayout(
sidebarPanel(
numericInput("wafer", label = h3("Input wafer ID:"), value = NULL),
actionButton("do", "Search wafer"),
radioButtons("length", label="Length", choices=""),
radioButtons("width", label="Width", choices = "")
),
mainPanel(
dataTableOutput(outputId="l"),
dataTableOutput(outputId="w")
)))
)
In the above, I can only get one set of radiobuttons to reactive ("Length"). However, if I comment out the Length observe, the Width one works so my code must be OK in isolation. Maybe I'm missing something simple?
This might be a bug of the updateRadioButtons function. When selected is not set, it is replaced by the first choice. I guess this causes an error if the choices list is numeric.
To fix your problem, you can either convert your choices to characters using as.character or set selected to a random string such as "".
Using as.character is probably better as you then get your first selection automatically selected.