why does the missing function not work inside of reactive RShiny? - r

I have an R shiny app that filters on some variables and returns a table using modules. I'd like to use missing() so that the app will still work even if no value is provided to the module. However, when I use missing() inside reactive() it gives an error: Warning: Error in missing: 'missing' can only be used for arguments. Does anyone know why this might be the case? Is there a way to get around this?
Example app:
df <- data.frame(a = sample(letters,100,T), b = sample(10,100,T))
dfFilter <- function(data, a, b){
if (!missing(a)) {
if(!is.null(a)){
data <- data[data$a %in% a,]
}
}
if (!missing(b)) {
if(!is.null(b)){
data <- data[data$b %in% b,]
}
}
return(data)
}
filterTable <- function(input, output, session, data, aFetcher, bFetcher){
return(reactive(dfFilter(data = data,
a = switch(!missing(aFetcher),
aFetcher(),NULL),
b = switch(!missing(bFetcher),
bFetcher(), NULL))))
}
displayTableUI <- function(id){
ns <- NS(id)
DT::dataTableOutput(ns('displayer'))
}
displayTable <- function(input, output, session, data){
output$displayer <- DT::renderDataTable(data())
}
chooserUI <- function(id){
ns <- NS(id)
uiOutput(ns('filter'))
}
chooseA <- function(input, output, session, data){
output$filter <- renderUI({
ns <- session$ns
pickerInput(inputId = ns('filter'),
label = 'Choose A:',
choices = unique(data$a),
options = list(`actions-box` = TRUE),
multiple = TRUE)
})
return(reactive(input$filter))
}
chooseB <- function(input, output, session, data){
output$filter <- renderUI({
ns <- session$ns
pickerInput(inputId = ns('filter'),
label = 'Choose B:',
choices = unique(data$b),
options = list(`actions-box` = TRUE),
multiple = TRUE)
})
return(reactive(input$filter))
}
ui <- fluidPage(
tabPanel('data',
sidebarPanel(
chooserUI('aChooser'),
chooserUI('bChooser')
),
mainPanel(
displayTableUI('table1')
)
)
)
server <- function(input,output){
chosenA <- callModule(chooseA,
id = 'aChooser',
data = df)
chosenB <- callModule(chooseB,
id = 'bChooser',
data = df)
table1 <- callModule(filterTable,
data = df,
id = 'tableFilterer',
aFetcher = chosenA,
bFetcher = chosenB)
callModule(displayTable, id = 'table1', data = table1)
}
shinyApp(ui, server)

Fixed by using exists() instead of !missing():
df <- data.frame(a = sample(letters,100,T), b = sample(10,100,T))
dfFilter <- function(data, a, b){
if (!missing(a)) {
if(!is.null(a)){
data <- data[data$a %in% a,]
}
}
if (!missing(b)) {
if(!is.null(b)){
data <- data[data$b %in% b,]
}
}
return(data)
}
filterTable <- function(input, output, session, data, aFetcher, bFetcher){
return(reactive(dfFilter(data = data,
a = switch(exists(aFetcher),
aFetcher(),NULL),
b = switch(exists(bFetcher),
bFetcher(), NULL))))
}
displayTableUI <- function(id){
ns <- NS(id)
DT::dataTableOutput(ns('displayer'))
}
displayTable <- function(input, output, session, data){
output$displayer <- DT::renderDataTable(data())
}
chooserUI <- function(id){
ns <- NS(id)
uiOutput(ns('filter'))
}
chooseA <- function(input, output, session, data){
output$filter <- renderUI({
ns <- session$ns
pickerInput(inputId = ns('filter'),
label = 'Choose A:',
choices = unique(data$a),
options = list(`actions-box` = TRUE),
multiple = TRUE)
})
return(reactive(input$filter))
}
chooseB <- function(input, output, session, data){
output$filter <- renderUI({
ns <- session$ns
pickerInput(inputId = ns('filter'),
label = 'Choose B:',
choices = unique(data$b),
options = list(`actions-box` = TRUE),
multiple = TRUE)
})
return(reactive(input$filter))
}
ui <- fluidPage(
tabPanel('data',
sidebarPanel(
chooserUI('aChooser'),
chooserUI('bChooser')
),
mainPanel(
displayTableUI('table1')
)
)
)
server <- function(input,output){
chosenA <- callModule(chooseA,
id = 'aChooser',
data = df)
chosenB <- callModule(chooseB,
id = 'bChooser',
data = df)
table1 <- callModule(filterTable,
data = df,
id = 'tableFilterer',
aFetcher = chosenA,
bFetcher = chosenB)
callModule(displayTable, id = 'table1', data = table1)
}
shinyApp(ui, server)

Related

Update data SelectInput in shiny modules

I am facing an issue in updating the data selected using SelectInput and modules in Shiny. In a few words, when I select the data to be loaded into the selectInput panel, it updates it on the first selection, but if I then want to go from dataset 1 to dataset 2, the data does not update.
Below you cand find the code to reproduce the specific problem.
# Libraries
pacman::p_load(shiny, shinydashboard,
tidyverse, data.table, DT, stringr,
ggplot2, plotly,
survival, survminer, GGally, scales,
shinycssloaders)
version <- 0.1
# GENERAL PARAMETERS
box.height <<- 700
select.box.height <<- 150
selectAB.box.height <<- 250
select.box.width <<- 12
# Data
men1_1.norm <<- as.numeric(rnorm(50))
men1_1.pois <<- as.numeric(rpois(50, lambda = 1))
men1_2.norm <<- as.numeric(rnorm(50, mean = 1))
men1_2.pois <<- as.numeric(rpois(50, lambda = 2))
# ui modules
LoadDataUI <- function(id,
label = "Select the data:",
sel = "Data 1",
choic = c('Data 1','Data 2')){
ns <- NS(id)
selectInput(ns("data.sel"),
label = label,
choices = choic,
selected = sel)
}
PlotUI <- function(id){
ns <- NS(id)
plotOutput(ns("plot"))
}
# ui
ui <- dashboardPage(
dashboardHeader(title = paste('My Dashboard',version,sep='')),
dashboardSidebar(
sidebarMenu(
id = "sbMenu",
#Tabs for different data displays
menuItem("1st Menu", tabName = "men1", icon = icon('microscope'))
)
),
dashboardBody(
tabItems(
tabItem(tabName = 'men1',
h2(strong('tab 1')),
fluidRow(
### !!!! TO REMOVE ERROR MESSAGES !!!!
# tags$style(type="text/css",
# ".shiny-output-error { visibility: hidden; }",
# ".shiny-output-error:before { visibility: hidden; }"
#,
box(title='Select data to load:', height= select.box.height, width = select.box.width,
LoadDataUI("data1")
),
box(title='Normal', height=box.height,
PlotUI("hist_norm1")
),
box(title='Poisson', height=box.height,
PlotUI("hist_pois1")
)
)
)
)
)
)
# server modules
Panel <- function(id){
moduleServer(
id,
function(input, output, session) {
return(
list(
data = reactive({input$data.sel})
)
)
}
)
}
LoadDataServer <- function(id, menu, data_selected
){
moduleServer(
id,
function(input, output, session){
dt <- reactive(data_selected)
data <- reactiveValues(norm = NULL,
pois = NULL)
data$norm <- reactive({get(paste0(menu(),"_", dt(), ".norm"), envir = .GlobalEnv)})
data$pois <- reactive({get(paste0(menu(),"_", dt(), ".pois"), envir = .GlobalEnv)})
return(
data
)
}
)
}
PlotServer <- function(id,data = NULL){
moduleServer(
id,
function(input, output, session) {
x <- reactive(as.numeric(data))
output$plot <- renderPlot({
hist(x(), col = 'darkgray', border = 'white')
})
# output$plot <- renderPlot({
# if(is.null(data)){return(NULL)}else{
# hist(data, col = 'darkgray', border = 'white')}
# })
}
)
}
# server
server <- function(input, output, session){
data1 <- Panel("data1")
observeEvent(data1$data(), {
updateSelectInput(session, 'data.sel', selected = input$data.sel)
})
pnl1 <- reactive(
switch(data1$data(),
"Data 1" = "1",
"Data 2" = "2")
)
d1 <- LoadDataServer("data1", menu = reactive({input$sbMenu}), data_selected = pnl1())
# Plot
# menu1
output$plot <- PlotServer("hist_norm1", data = d1$norm())
output$plot <- PlotServer("hist_pois1", data = d1$pois())
}
shinyApp(ui, server)
Thanks!
Try this
version <- 0.1
# GENERAL PARAMETERS
box.height <<- 500
select.box.height <<- 150
selectAB.box.height <<- 250
select.box.width <<- 12
# Data
men1_1.norm <<- as.numeric(rnorm(50))
men1_1.pois <<- as.numeric(rpois(50, lambda = 1))
men1_2.norm <<- as.numeric(rnorm(150, mean = 1))
men1_2.pois <<- as.numeric(rpois(150, lambda = 2))
# ui modules
LoadDataUI <- function(id,
label = "Select the data:",
sel = "Data 1",
choic = c('Data 1','Data 2')){
ns <- NS(id)
selectInput(ns("data.sel"),
label = label,
choices = choic,
selected = sel)
}
PlotUI <- function(id){
ns <- NS(id)
tagList(
plotOutput(ns("plot"))
)
}
# ui
ui <- dashboardPage(
dashboardHeader(title = paste('My Dashboard',version,sep='')),
dashboardSidebar(
sidebarMenu(
id = "sbMenu",
#Tabs for different data displays
menuItem("1st Menu", tabName = "men1", icon = icon('microscope'))
)
),
dashboardBody(
tabItems(
tabItem(tabName = 'men1',
h2(strong('tab 1')),
fluidRow(
### !!!! TO REMOVE ERROR MESSAGES !!!!
# tags$style(type="text/css",
# ".shiny-output-error { visibility: hidden; }",
# ".shiny-output-error:before { visibility: hidden; }"
#,
box(title='Select data to load:', height= select.box.height, width = select.box.width,
LoadDataUI("data1")
),
box(title='Normal', height=box.height,
PlotUI("hist_norm1")
),
box(title='Poisson', height=box.height,
PlotUI("hist_pois1")
)
)
)
)
)
)
# server modules
Panel <- function(id){
moduleServer(
id,
function(input, output, session) {
return(
list(
data = reactive({input$data.sel})
)
)
}
)
}
LoadDataServer <- function(id, menu, data_selected
){
moduleServer(
id,
function(input, output, session){
dt <- reactive(
switch(data_selected(),
"Data 1" = "1",
"Data 2" = "2")
)
observe({print(dt())})
data <- reactiveValues(norm = NULL,
pois = NULL)
data$norm <- reactive({get(paste0(menu(),"_", dt(), ".norm"), envir = .GlobalEnv)})
data$pois <- reactive({get(paste0(menu(),"_", dt(), ".pois"), envir = .GlobalEnv)})
return(
data
)
}
)
}
PlotServer <- function(id,data){
moduleServer(
id,
function(input, output, session) {
#x <- reactive(as.numeric(data))
output$plot <- renderPlot({
x <- as.numeric(data())
hist(x, col = 'darkgray', border = 'white')
})
# output$plot <- renderPlot({
# if(is.null(data)){return(NULL)}else{
# hist(data, col = 'darkgray', border = 'white')}
# })
}
)
}
# server
server <- function(input, output, session){
data1 <- Panel("data1")
# observeEvent(data1$data(), {
# updateSelectInput(session, 'data.sel', selected = input$data.sel)
# })
# pnl1 <- reactive(
# switch(data1$data(),
# "Data 1" = "1",
# "Data 2" = "2")
# )
d1 <- LoadDataServer("data1", menu = reactive({input$sbMenu}), data_selected = data1$data )
# Plot
# menu1
PlotServer("hist_norm1", data = reactive(d1$norm()) )
PlotServer("hist_pois1", data = reactive(d1$pois()) )
}
shinyApp(ui, server)
The problem arises because the data you pass to the PlotServer is not reactive. I've made the additional changes:
stored the data in the beginning in a list to avoid using get; it's easier and safer to directly work with a data object
removed the data_selected argument from the LoadDataServer as this information is determined by the input$data.sel variable, however this is only accessible from within the module and not the the main app server. For the initialisation, you need this information only in the UI part of the module (which you already have implemented). This allows me to remove observeEvent code in your main app server as this is handled by the module.
# Libraries
# pacman::p_load(shiny, shinydashboard,
# tidyverse, data.table, DT, stringr,
# ggplot2, plotly,
# survival, survminer, GGally, scales,
# shinycssloaders)
library(shiny)
library(shinydashboard)
library(ggplot2)
version <- 0.1
# GENERAL PARAMETERS
box.height <<- 700
select.box.height <<- 150
selectAB.box.height <<- 250
select.box.width <<- 12
# Data
data_object <- list(
men1_1 = list(
norm = as.numeric(rnorm(50)),
pois = as.numeric(rpois(50, lambda = 1))
),
men1_2 = list(
norm = as.numeric(rnorm(50, mean = 1)),
pois = as.numeric(rpois(50, lambda = 2))
)
)
# ui modules
LoadDataUI <- function(id,
label = "Select the data:",
sel = "Data 1",
choic = c('Data 1' = "1",'Data 2' = "2")){
ns <- NS(id)
selectInput(ns("data.sel"),
label = label,
choices = choic,
selected = sel)
}
PlotUI <- function(id){
ns <- NS(id)
plotOutput(ns("plot"))
}
# ui
ui <- dashboardPage(
dashboardHeader(title = paste('My Dashboard',version,sep='')),
dashboardSidebar(
sidebarMenu(
id = "sbMenu",
#Tabs for different data displays
menuItem("1st Menu", tabName = "men1", icon = icon('microscope'))
)
),
dashboardBody(
tabItems(
tabItem(tabName = 'men1',
h2(strong('tab 1')),
fluidRow(
### !!!! TO REMOVE ERROR MESSAGES !!!!
# tags$style(type="text/css",
# ".shiny-output-error { visibility: hidden; }",
# ".shiny-output-error:before { visibility: hidden; }"
#,
box(title='Select data to load:', height= select.box.height, width = select.box.width,
LoadDataUI("data1")
),
box(title='Normal', height=box.height,
PlotUI("hist_norm1")
),
box(title='Poisson', height=box.height,
PlotUI("hist_pois1")
)
)
)
)
)
)
# server modules
Panel <- function(id){
moduleServer(
id,
function(input, output, session) {
return(
list(
data = reactive({input$data.sel})
)
)
}
)
}
LoadDataServer <- function(id, menu
){
moduleServer(
id,
function(input, output, session){
data <- reactiveValues(norm = NULL,
pois = NULL)
observeEvent(input$data.sel, {
data$norm <- data_object[[paste0(menu(), "_", input$data.sel)]][["norm"]]
data$pois <- data_object[[paste0(menu(), "_", input$data.sel)]][["pois"]]
})
return(
data
)
}
)
}
PlotServer <- function(id,data = NULL){
moduleServer(
id,
function(input, output, session) {
output$plot <- renderPlot({
hist(data(), col = 'darkgray', border = 'white')
})
}
)
}
# server
server <- function(input, output, session){
d1 <- LoadDataServer("data1", menu = reactive({input$sbMenu}))
# Plot
# menu1
output$plot <- PlotServer("hist_norm1", data = reactive({d1$norm}))
output$plot <- PlotServer("hist_pois1", data = reactive({d1$pois}))
}
shinyApp(ui, server)
If you pass the complete d1 object to the PlotServer, you could remove the reactive({}) you currently need to pass the norm or pois data.
I recommend to read into how to pass data between modules and module capsulation, you can start with mastering shiny or my introduction to modules.

CheckboxInput with Edit table in DT R Shiny

I tried to combine editing table by adding, deleting row in DT table with checkboxInput(). It is not quite correct.
If I didn't add editing feature, it returned correct, but if I added editing feature,it didn't response after I added another row. I got stuck for a while, I will appreciate any help from you guys
library(shiny)
library(shinyjs)
library(DT)
# Tab 2 UI code.
tab2UI <- function(id) {
ns <- NS(id)
tabPanel(
"Tab 2",
fluidRow(
#uiOutput(ns('cars')),
h2('The mtcars data'),
DT::dataTableOutput(ns('mytable2')),
uiOutput(ns("edit_1")),
h2("Selected"),
tableOutput(ns("checked"))
)
)
}
# Tab 2 server code.
tab2Server <- function(input, output, session) {
ns <- session$ns
# Helper function for making checkboxes.
shinyInput = function(FUN, len, id, ...) {
inputs = character(len)
for (i in seq_len(len)) {
inputs[i] = as.character(FUN(ns(paste0(id, i)), label = NULL, ...))
}
inputs
}
# Update table records with selection.
subsetData <- reactive({
sel <- mtcars[1:5,]
})
values <- reactiveValues(df = NULL)
observe({
values$df <- subsetData()
})
# Datatable with checkboxes.
output$mytable2 <- DT::renderDataTable(
datatable(
data.frame(values$df,Favorite=shinyInput(checkboxInput,nrow(values$df), "cbox_", width = 10)),
editable = TRUE,
selection = 'single',
escape = FALSE,
options = list(
paging = FALSE,
preDrawCallback = JS('function() {Shiny.unbindAll(this.api().table().node()); }'),
drawCallback = JS('function() {Shiny.bindAll(this.api().table().node()); }')
)
)
)
observeEvent(input$add.row_1,{
# print(paste0("Row selected",input$mytable2_rows_selected))
if (!is.null(input$mytable2_rows_selected)) {
td <- values$df
tid_n = as.numeric(input$mytable2_rows_selected)
tid = as.numeric(input$mytable2_rows_selected) + 1
if(tid_n == nrow(td)){
td<- rbind(data.frame(td[1:tid_n, ]),
data.frame(td[tid_n, ]))
}else{
td<- rbind(data.frame(td[1:tid_n, ]),
data.frame(td[tid_n, ]),
data.frame(td[tid: nrow(td), ]))
}
td <- data.frame(td)
print(td)
values$df <- td
}
})
output$edit_1 <- renderUI({
tagList(
actionButton(inputId = ns("add.row_1"), label = "Add Row", icon = icon("plus"),class = "example-css-selector",style = "background-color:gray; border-color:gray;color:white;height:31px;"),
actionButton(inputId = ns("delete.row_1"), label = "Delete Row", icon = icon("minus"),class = "example-css-selector",style = "background-color:gray; border-color:gray;color:white;height:31px;"),br(),br()
)
})
# Helper function for reading checkbox.
shinyValue = function(id, len) {
values <- unlist(lapply(seq_len(len), function(i) {
value = input[[paste0(id, i)]]
if (is.null(value)) NA else value
}))
return(values)
}
# Output read checkboxes.
observe({
len <- nrow(values$df)
output$checked <- renderTable({
data.frame(selected=shinyValue("cbox_", len))
})
})
}
# Define UI for application.
ui <- fluidPage(
useShinyjs(),
navbarPage(
'Title',
tab2UI("tab2")
)
)
# Define server.
server <- function(input, output, session) {
# Call tab2 server code.
callModule(tab2Server, "tab2")
}
# Run the application
shinyApp(ui = ui, server = server)

Make a Shiny module reactive when creating the module via a function

I'm trying to generalise Shiny modules so different functions can be passed through, but the expected behaviour of reactivity is not working - could someone point me in the right direction? I have a reprex below that illustrates my problem.
I expect that the dynamic selection of view_id to change values in the renderShiny() function. It works on app load but changing selections do not flow through.
Is it something to do with the environment the module function is created within?
library(shiny)
create_shiny_module_funcs <- function(data_f,
model_f,
outputShiny,
renderShiny){
server_func <- function(input, output, session, view_id, ...){
gadata <- shiny::reactive({
# BUG: this view_id is not reactive but I want it to be
data_f(view_id(), ...)
})
model_output <- shiny::reactive({
shiny::validate(shiny::need(gadata(),
message = "Waiting for data"))
model_f(gadata(), ...)
})
output$ui_out <- renderShiny({
shiny::validate(shiny::need(model_output(),
message = "Waiting for model output"))
message("Rendering model output")
model_output()
}, ...)
return(model_output)
}
ui_func <- function(id, ...){
ns <- shiny::NS(id)
outputShiny(outputId = ns("ui_out"), ...)
}
list(
shiny_module = list(
server = server_func,
ui = ui_func
)
)
}
# create the shiny module
ff <- create_shiny_module_funcs(
data_f = function(view_id) mtcars[, view_id],
model_f = function(x) mean(x),
outputShiny = shiny::textOutput,
renderShiny = function(x) shiny::renderText(paste("Mean is: ", x))
)
## ui.R
ui <- fluidPage(title = "module bug Shiny Demo",
h1("Debugging"),
selectInput("select", label = "Select", choices = c("mpg","cyl","disp")),
textOutput("view_id"),
ff$shiny_module$ui("demo1"),
br()
)
## server.R
server <- function(input, output, session){
view_id <- reactive({
req(input$select)
input$select
})
callModule(ff$shiny_module$server, "demo1", view_id = view_id)
output$view_id <- renderText(paste("Selected: ", input$select))
}
# run the app
shinyApp(ui, server)
The problem was the renderShiny function needs to wrap another function that creates the actual output, so its actually two separate capabilities confused by me as one: renderShiny should take the output of another function that actually creates the thing to render. The below then works:
library(shiny)
module_factory <- function(data_f = function(x) mtcars[, x],
model_f = function(x) mean(x),
output_shiny = shiny::plotOutput,
render_shiny = shiny::renderPlot,
render_shiny_input = function(x) plot(x),
...){
ui <- function(id, ...){
ns <- NS(id)
output_shiny(ns("ui_out"), ...)
}
server <- function(input, output, session, view_id){
gadata <- shiny::reactive({
data_f(view_id(), ...)
})
model <- shiny::reactive({
shiny::validate(shiny::need(gadata(),
message = "Waiting for data"))
model_f(gadata(), ...)
})
output$ui_out <- render_shiny({
shiny::validate(shiny::need(model(),
message = "Waiting for model output"))
render_shiny_input(gadata())
})
return(model)
}
list(
module = list(
ui = ui,
server = server
)
)
}
made_module <- module_factory()
## ui.R
ui <- fluidPage(title = "module bug Shiny Demo",
h1("Debugging"),
selectInput("select", label = "Select", choices = c("mpg","cyl","disp")),
textOutput("view_id"),
made_module$module$ui("factory1"),
br()
)
## server.R
server <- function(input, output, session){
callModule(made_module$module$server, "factory1", view_id = reactive(input$select))
output$view_id <- renderText(paste("Selected: ", input$select))
}
# run the app
shinyApp(ui, server)
I think you want something like this.
library(shiny)
library(plyr)
library(dplyr)
library(DT)
library(data.table)
ui <- pageWithSidebar(
headerPanel = headerPanel('data'),
sidebarPanel = sidebarPanel(fileInput(
'mtcars', h4('Uplaodmtcardata in csv format')
),
uiOutput('tabnamesui')),
mainPanel(uiOutput("tabsets"))
)
server <- function(input, output, session) {
mtcarsFile <- reactive({
input$mtcars
})
xxmtcars <-
reactive({
read.table(
file = mtcarsFile()$datapath,
sep = ',',
header = T,
stringsAsFactors = T
)
})
tabsnames <- reactive({
names(xxmtcars())
})
output$tabnamesui <- renderUI({
req(mtcarsFile())
selectInput(
'tabnamesui',
h5('Tab names'),
choices = as.list(tabsnames()),
multiple = T
# selected = SalesGlobalDataFilter1Val()
)
})
tabnamesinput <- reactive({
input$tabnamesui
})
output$tabsets <- renderUI({
req(mtcarsFile())
tabs <-
reactive({
lapply(tabnamesinput(), function(x)
tabPanel(title = basename(x)
,fluidRow(splitLayout(cellWidths = c("50%", "50%"),
plotOutput(paste0('plot1',x)),
plotOutput(paste0('plot2',x)
))),fluidRow(splitLayout(cellWidths =
c("50%", "50%"),
plotOutput(paste0('plot3',x)),
plotOutput(paste0('plot4',x)
))),
dataTableOutput(paste0('table',x))))
})
do.call(tabsetPanel, c(tabs()))
})
# Save your sub data here
subsetdata<-reactive({
list_of_subdata<-lapply(tabnamesinput(), function(x) {
as.data.table((select(xxmtcars(),x)))
})
names(list_of_subdata)<-tabnamesinput()
return(list_of_subdata)
})
observe(
lapply(tabnamesinput(), function(x) {
output[[paste0('table',x)]] <-
renderDataTable({
subsetdata()[[x]]
})}))
observe(
lapply(tabnamesinput(), function(x) {
for(i in paste0("plot",1:4)){
output[[paste0(i,x)]] <-
renderPlot({subsetdata()[[x]]%>%plot()#CODE REPEATED
})
}
})
)
}
runApp(list(ui = ui, server = server))
Data Source:
https://gist.githubusercontent.com/seankross/a412dfbd88b3db70b74b/raw/5f23f993cd87c283ce766e7ac6b329ee7cc2e1d1/mtcars.csv

R Shiny loop logical operator

I have a running example: I am updating a data.table depending on users input via checkboxes. So far Iam filtering the data explicitly, but I would like to do that with the help of a loop using a for loop or a function of the apply-family. Unfortunately I cannot get either to work.
library(shiny)
library(data.table)
library(DT)
tdata <- data.table(fruit = c(rep("Apple",4),rep( "Ban",4)),
bug1 = c(rep(c("+","+", "-","-"),2)),
bug2 = c(rep(c("+","-"),4)),
value = c(rep(c(0.25),4), 0.6,0.4,0,0))
ui <- (fluidPage(tagList(
sidebarLayout(
sidebarPanel(uiOutput("file_input")),
mainPanel(dataTableOutput('fruit_table'))
))))
server <- function(input, output) {
fileData <- reactive(
return(tdata)
)
colname_list <- reactive(
colnames(fileData())
)
output$file_input <- renderUI ({
if(is.null(fileData())){
return()
}else{
tagList(
lapply(1:(length(fileData())-1), function(i){
choice_list = unique(fileData()[,get(colnames(fileData()[,i, with = FALSE]))])
checkboxGroupInput(inputId = colnames(fileData()[,i, with = FALSE]),
label = colnames(fileData()[,i, with = FALSE]),
choices = choice_list,
inline = TRUE,
selected = fileData()[1, i, with = FALSE])
})
)
}
})
# works fine, but usually the number of columns changes so I want to keep it flexible
fruitFilter <- reactive({
fileData()[[paste0(colname_list()[1])]] %in% input[[paste0(colname_list()[1])]] &
fileData()[[paste0(colname_list()[2])]] %in% input[[paste0(colname_list()[2])]] &
fileData()[[paste0(colname_list()[3])]] %in% input[[paste0(colname_list()[3])]]
})
# fruitFilter <- reactive({
# for(i in 1: ((length(fileData()))-1)){
# fileData()[[paste0(colname_list()[i])]] %in% input[[paste0(colname_list()[i])]]
# }
# })
output$fruit_table <- renderDataTable({
datatable(fileData()[fruitFilter(),])
})
}
shinyApp(ui = ui, server = server)
I still consider myself a newby to Shiny. I appreciate any help! Thanks.
In the loop approach, we could initialize a list and then Reduce the output to a single logical vector
fruitFilter <- reactive({
i1 <- head(seq_along(fileData()), -1)
l1 <- vector('list', length(i1))
for(i in i1){
l1[[i]] <- fileData()[[colname_list()[i]]] %in% input[[colname_list()[i]]]
}
Reduce(`&`, l1)
})
With the full code
library(shiny)
library(data.table)
library(DT)
tdata <- data.table(fruit = c(rep("Apple",4),rep( "Ban",4)),
bug1 = c(rep(c("+","+", "-","-"),2)),
bug2 = c(rep(c("+","-"),4)),
value = c(rep(c(0.25),4), 0.6,0.4,0,0))
ui <- (fluidPage(tagList(
sidebarLayout(
sidebarPanel(uiOutput("file_input")),
mainPanel(dataTableOutput('fruit_table'))
))))
server <- function(input, output) {
fileData <- reactive(
return(tdata)
)
colname_list <- reactive(
colnames(fileData())
)
output$file_input <- renderUI ({
if(is.null(fileData())){
return()
}else{
tagList(
lapply(1:(length(fileData())-1), function(i){
choice_list = unique(fileData()[,get(colnames(fileData()[,i, with = FALSE]))])
checkboxGroupInput(inputId = colnames(fileData()[,i, with = FALSE]),
label = colnames(fileData()[,i, with = FALSE]),
choices = choice_list,
inline = TRUE,
selected = fileData()[1, i, with = FALSE])
})
)
}
})
fruitFilter <- reactive({
i1 <- head(seq_along(fileData()), -1)
l1 <- vector('list', length(i1))
for(i in i1){
l1[[i]] <- fileData()[[colname_list()[i]]] %in% input[[colname_list()[i]]]
}
Reduce(`&`, l1)
})
output$fruit_table <- renderDataTable({
datatable(fileData()[fruitFilter()])
})
}
shinyApp(ui = ui, server = server)
--output

How to use built-in data instead of uploaded data

I have an app like below. I want to either read-in data from file upload or use the built-in data. I thought I could put an action button and if somebody hit it the input data will mount on and it goes to the next levels. My problem is later in my real app, some widgets such as selectInput have to be updated and I want to be empty until user decided whether to use uploaded data or the built-in one.
library(shiny)
x <- mtcars
ui <- fluidPage(
fileInput(inputId = "uploadcsv", "", accept = '.csv'),
actionButton(inputId = "a", label = "action button"),
selectInput("select",label = h3("Select box"),choices = "",selected = 1)
)
server <- function(input, output, session) {
data <- reactive({
infile <- input$uploadcsv
if (is.null(infile))
return(NULL)
read.csv(infile$datapath, header = TRUE, sep = ",")
})
DataToUse <- NULL
observe(!is.null(input$uploadedcsv),
DataToUse <- data()
)
observeEvent(input$a,
DataToUse <- x
)
observe({
req(DataToUse)
if (max(DataToUse$cyl) %% 4 == 0){
numberofinterval <- max(DataToUse$cyl) %/% 4
} else {
numberofinterval <- (max(DataToUse$cyl) %/% 4)+1
}
NumPeriod <- seq(0, numberofinterval)
updateSelectInput(session, inputId = "select",
choices = NumPeriod,
selected = NumPeriod)
})
}
shinyApp(ui = ui, server = server)
Something like this should do:
library(shiny)
x <- mtcars
ui <- fluidPage(
fileInput(inputId = "uploadcsv", "", accept = '.csv'),
actionButton(inputId = "a", label = "action button"),
selectInput("select",label = h3("Select box"),choices = "",selected = 1)
)
server <- function(input, output, session) {
data <- reactive({
infile <- input$uploadcsv
if (is.null(infile))
return(NULL)
read.csv(infile$datapath, header = TRUE, sep = ",")
})
v <- reactiveValues()
v$DataToUse <- NULL
observeEvent(input$uploadcsv,{
if(!is.null(input$uploadcsv)){
v$DataToUse <- data()
}
})
observeEvent(input$a,v$DataToUse <- x)
observeEvent(v$DataToUse,{
req(v$DataToUse)
if (max(v$DataToUse$cyl) %% 4 == 0){
numberofinterval <- max(v$DataToUse$cyl) %/% 4
} else {
numberofinterval <- (max(v$DataToUse$cyl) %/% 4)+1
}
NumPeriod <- seq(0, numberofinterval)
updateSelectInput(session, inputId = "select",
choices = NumPeriod,
selected = NumPeriod)
})
}
shinyApp(ui = ui, server = server)

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