How can I display value only on the browser?
Below is my code.
ui <- shinyUI(bootstrapPage(
absolutePanel(
textOutput("renderText1")
)
)
)
server <- function(input,output,session)
{
observeEvent(input$dropdown, {
query <- sprintf("select ....",input$dropdown)
cabinet_info <- dbGetQuery(con,query)
output$renderText1 <- renderText({
paste(cabinet_info)
})
})
}
Below are the outputs:
c('a','w','r','t')
While Geovany's answer may work, it is not a good practice to use observeEvent with the global assignment operator (<<-).
If you would like to execute a side effect (e.g. writing a file, plotting, printing), then you can use observe or observeEvent, but if you want to use a return value, use eventReactive instead.
ui <- shinyUI(bootstrapPage(
absolutePanel(
selectInput("dropdown", label = 'SelectInput', choices = c('A', 'B')),
textOutput("renderText1")
)
)
)
server <- function(input,output,session)
{
cab <- eventReactive(input$dropdown, {
query <- sprintf("select ....",input$dropdown)
#cabinet_info <- dbGetQuery(con,query) #Replaced by a constant
cabinet_info <- paste(c(input$dropdown, 'a','w','r','t'), sep=",")
})
output$renderText1 <- renderText({
cab()
})
}
shinyApp(ui, server)
Call eventReactive from the server side just like a function: cab()
This could help you
runApp(list(
ui = shinyUI(bootstrapPage(
absolutePanel(
actionButton("dropdown", "dropdown"),
textOutput("renderText1")
)
)
),
server = shinyServer(function(input, output) {
cabinet_info <- NULL
observeEvent(input$dropdown, {
cabinet_info <<- c('a','w','r','t')
})
output$renderText1 <- renderText({
input$dropdown
paste(cabinet_info, collapse = ',')
})
})
))
Related
I want to do operations on data that has been split into tables. The operations should actually affect all tables eg sum of a column
Here is the code I used to split the data frame.
library(shiny)
ui <- fluidPage(
uiOutput("mytabs")
)
server <- function(input, output) {
df1 <- reactive (split(iris, iris$Species))
output$mytabs <- renderUI({
thetabs <- lapply(paste0('table_', names(df1())),
function(x) {
tabPanel(x,
tableOutput(x))
})
do.call(tabsetPanel, thetabs)
})
observe({
lapply(names(df1()), function(x) {
output[[paste0("table_", x)]] <- renderTable({ df1()[x] })
})
})
}
shinyApp(ui = ui, server = server)
We can add a bslib::value_box in the same tabPanel that the tableOutput goes.
Here's an example, notice the use of map2 instead of lapply, this is to loop through the character with the name of the tables and the tables themselves.
thetabs <- purrr::map2(
paste0("table_", names(df1())),
df1(),
function(x, y) {
tabPanel(
title = x,
value_box(
title = glue::glue("Sum of {x}"),
value = sum(y[['Sepal.Length']]),
showcase = bs_icon("plus")
),
tableOutput(x)
)
}
)
App:
library(shiny)
library(bslib)
library(bsicons)
ui <- fluidPage(
uiOutput("mytabs")
)
server <- function(input, output) {
df1 <- reactive(split(iris, iris$Species))
output$mytabs <- renderUI({
thetabs <- purrr::map2(
paste0("table_", names(df1())),
df1(),
function(x, y) {
tabPanel(
title = x,
value_box(
title = glue::glue("Sum of {x}"),
value = sum(y[['Sepal.Length']]),
showcase = bs_icon("plus")
),
tableOutput(x)
)
}
)
do.call(tabsetPanel, thetabs)
})
observe({
lapply(names(df1()), function(x) {
output[[paste0("table_", x)]] <- renderTable({
df1()[x]
})
})
})
}
shinyApp(ui = ui, server = server)
I'm making an app in which the user can create as many tables as he/she wants and display the code necessary to remake each individual table using shinymeta. I can generate the code for each of these tables but I have a problem when I want to create a complete modal that shows every code for each table.
To be clearer, here's a reproducible example:
library(shiny)
library(dplyr)
library(shinymeta)
module_ui <- function(id){
ns <- NS(id)
tagList(
fluidRow(
actionButton(ns("show_table"), "Show table"),
actionButton(ns("show_code"), "Show code"),
tableOutput(ns("table"))
)
)
}
module_server <- function(input, output, session){
data <- metaReactive2({
req(input$show_table)
isolate(metaExpr({
mtcars
}))
})
data2 <- metaReactive({
..(data()) %>%
select(mpg)
})
output$table <- renderTable({
data2()
})
observeEvent(input$show_code, {
showModal(modalDialog(
renderPrint({
expandChain(data(), data2())
})
))
})
return(data())
}
ui <- fluidPage(
actionButton("launch", "Launch"),
actionButton("show_full_code", "Show the full code (at least 2 'launch' before)")
)
server <- function(input, output, session) {
count <- reactiveValues(value = 0)
observeEvent(input$launch, {
count$value <- count$value + 1
insertUI(selector = "#show_full_code",
where = "afterEnd",
ui = module_ui(paste0("x", count$value)))
callModule(module_server, paste0("x", count$value))
})
#### "Merge" the single code modals in one big
observeEvent(input$show_full_code, {
showModal(modalDialog(
renderPrint({
expandChain(x1_data)
})
))
})
}
shinyApp(ui, server)
When you click on "Launch", two buttons are generated and you can display a table ("Show table") and the code to remake this table ("Show code"). You can click on "Launch" indefinitely and the table will be named x1_data, x2_data, etc.
However, when I try to generate the code that unites every individual code (by clicking on "Show the full code"), x1_data is not found. Using x1_data() does not work either. I'm not a fan of asking two questions in one post but I will do this now:
How can I access the reactive elements created inside modules?
How can I "merge" every individual code in a big one?
Also asked on RStudio Community
Edit: following a comment, I add a second reactive expression in my example, so that I can't use return on both of them.
Ok, I came up with an answer that has the module return the expandChain() results rather than trying to render them again in the server:
library(shiny)
library(dplyr)
library(shinymeta)
module_ui <- function(id){
ns <- NS(id)
tagList(
fluidRow(
actionButton(ns("show_table"), "Show table"),
actionButton(ns("show_code"), "Show code"),
tableOutput(ns("table"))
)
)
}
module_server <- function(input, output, session){
data <- metaReactive2({
req(input$show_table)
isolate(metaExpr({
mtcars
}))
})
data2 <- metaReactive({
..(data()) %>%
select(mpg)
})
output$table <- renderTable({
data2()
})
observeEvent(input$show_code, {
showModal(modalDialog(
renderPrint({
expandChain(data(), data2())
})
))
})
########################################
### create list of reactive objects ####
########################################
return(list(
expandChain(data(), data2())
)
)
}
ui <- fluidPage(
actionButton("launch", "Launch"),
actionButton("show_full_code", "Show the full code (at least 2 'launch' before)")
)
server <- function(input, output, session) {
count <- reactiveValues(value = 0)
observeEvent(input$launch, {
count$value <- count$value + 1
insertUI(selector = "#show_full_code",
where = "afterEnd",
ui = module_ui(paste0("x", count$value)))
callModule(module_server, paste0("x", count$value))
})
#### "Merge" the single code modals in one big list object
my_data <- reactive({
req(count$value)
my_set <- 1:count$value
### lapply through the different name spaces so all are captured ###
final <- lapply(my_set, function(x){
temp <- callModule(module_server, paste0("x", x))
return(temp)
})
return(final)
})
#### "Merge" the single code modals in one big
observeEvent(input$show_full_code, {
showModal(modalDialog(
renderPrint({
temp <- sapply(unlist(my_data()), function(x){
print(x)
})
})
))
})
}
shinyApp(ui, server)
I am trying to build an app which; 1) calculates the number of boxes, based on a data.frame, 2) For each box, creates a UI and a corresponding module that will trigger events when the action buttons are clicked, using a subset of that data.frame.
If I am not being explicit enough; the app has n UI's and in each UI, x buttons. I want to loop callModule to create n server functions so when I click on action button in any given UI, I trigger an event specific to that UI.
The problem I am having is that the callModule function apparently does not duplicate itself in a for loop. Instead, I always get only the last id and dataframe (as if the callModule overwrites itself).
I hope I was explicit enough. Here is a MWE:
server.R
library(shinydashboardPlus)
library(shiny)
library(shinydashboard)
source('modules.R')
shinyServer(function(input, output, session) {
# dataframe filtered / updated
dtst <- reactive({
iris[1:input$filter_d, ]
})
# number of items rendered
output$ui <- renderUI({
r <- tagList()
for(k in 1:input$n){
r[[k]] <- u_SimpleTaskView(id = k, d = dtst()[k, ]) # <- grab a subset or column of df
}
r
})
for(y in 1:isolate({input$n})){
callModule(m_UpdateTask, id = y, d = dtst()[, y])
}
})
ui.R
dheader <- dashboardHeaderPlus(title = "s")
dsidebar <- dashboardSidebar(
sidebarMenu(
menuItem("tst", tabName = "tst", icon = icon("bolt"))
)
)
dbody <- dashboardBody(
tabItems(
tabItem(tabName = "tst",
numericInput("n", "number of ui and module pairs", value = 10),
numericInput("filter_d", "RANDOM FILTER", value = 100),
uiOutput("ui")
)
) )
dashboardPagePlus(
title = "s",
header = dheader,
sidebar = dsidebar,
body = dbody
)
modules.R
u_SimpleTaskView <- function(id, d){
ns <- NS(id)
if(length(d) < 5){
# nothing
}else{
renderUI({
tagList(
br(),
HTML(paste0("<strong>Rows: </strong>", "xxxx")),
numericInput("divider", label = "number of rows", value = 2),
br(),
actionButton("go", "go")
)
})
}
}
m_UpdateTask <- function(input, output, session, d){
observeEvent(input$go, {
showModal(
modalDialog(
HTML(paste0("unique: ", length(unique(d))/input$divider ) )
)
)
})
}
Besides not being really minimal (no need for libraries shinydashboardPlus or shinydashboard) there are a couple of issues with your code.
renderUI is a server function not a UI function
If you create controls in the module UI you have to use the namespace function, otherwise you cannot use them in your module server function.
As it is a bit too complicated for me to debug your code directly, let me give you an example from which you can see how to use modules in the way you wanted:
library(shiny)
library(glue)
mod_ui <- function(id, base_df) { ## 3
ns <- NS(id) ## 1
tagList(
helpText(glue("The input parameter 'base_df' has {NROW(base_df)} rows.")),
numericInput(ns("n"), "n:", 2),
textOutput(ns("out"))
)
}
mod <- function(input, output, session) {
get_nr <- reactive(input$n) ## 2
output$out <- renderText(glue("Number selected: {get_nr()}"))
return(list(get_nr = get_nr)) ## 4
}
ui <- fluidPage(
numericInput("n", "number of uis:", 2),
uiOutput("uis"),
textOutput("sum")
)
server <- function(input, output, session) {
handlers <- list()
output$uis <- renderUI({
ret <- lapply(seq.int(input$n),
function(i) mod_ui(glue("mod_{i}"),
data.frame(x = seq.int(i)))) ## 5
tagList(ret)
})
observe(
handlers <<- lapply(seq.int(input$n),
function(i) callModule(mod, glue("mod_{i}"))) ## 6
)
output$sum <- renderText({ ## 7
req(length(handlers) > 0)
m_sum <- sum(sapply(handlers, function(h) h$get_nr()))
glue("Sum of all n: {m_sum}")
})
}
shinyApp(ui, server)
Explanation
In mod_ui we define all the elements one module should have. note the use of ns() for the controls' ids to make use of the namespacing.
In mod (the module server function) we can access controls as we would in the main server function ( i.e. directly liek in input$n.
We can pass arguments to any of the module's functions (like base_df).
If we want to use some of the reactives in the main app, we shoudl return them from the modules server function.
In our main app we use a loop to create the desired number of modules.
We use an observer to store the handlers from the modules in a list
We can access the modules reactives via the handler which we defined earlier.
Update 2021
shiny 1.5.0 introduced an easier interface for modules. The code below uses this "new" interface:
library(shiny)
library(glue)
mod_ui <- function(id, base_df) {
ns <- NS(id)
tagList(
helpText(glue("The input parameter 'base_df' has {NROW(base_df)} rows.")),
numericInput(ns("n"), "n:", 2),
textOutput(ns("out"))
)
}
mod <- function(id) {
moduleServer(id,
function(input, output, session) {
get_nr <- reactive(input$n)
output$out <- renderText(glue("Number selected: {get_nr()}"))
return(list(get_nr = get_nr))
}
)
}
ui <- fluidPage(
numericInput("n", "number of uis:", 2),
uiOutput("uis"),
textOutput("sum")
)
server <- function(input, output, session) {
handlers <- list()
output$uis <- renderUI({
ret <- lapply(seq.int(input$n),
function(i) mod_ui(glue("mod_{i}"),
data.frame(x = seq.int(i))))
tagList(ret)
})
observe({
handlers <<- lapply(seq.int(input$n),
function(i) mod(glue("mod_{i}")))
})
output$sum <- renderText({
req(length(handlers) > 0)
m_sum <- sum(sapply(handlers, function(h) {
res <- h$get_nr()
if(is.null(res)) {
0
} else {
res
}
}))
glue("Sum of all n: {m_sum}")
})
}
shinyApp(ui, server)
SelectInput function in ui is supposed to give me an option to choose "YES" or "NO". When "NO" is selected, it will choose the " if(("NO" %in% input$qualify_pit))" block in renderDataTable function in server and execute that perfectly. However, when I choose "YES" option, its block does not run, not displaying any table. I tried everything to get it to run its block (if(("YES" %in% input$qualify_pit))) but to no avail.
library(shiny)
library(shinythemes)
library(DT)
pit <- read.csv("PIT_STAT.csv")
pit_stat <- c("MLB_name","MLBId","LastName","FirstName","LW","W","L","Sv","BS","HLD","G","GS","CG","GF","QS","SHO","IP","BFP","H","X1B","X2B","X3B",
"HR","R","ER","SH","SF","HBP","BB","IBB","BB_noIBB","K","WP","BLK","GB","FB","LD","POPU","SB",
"CS","PKO","SVO","OUTS","K9","BB9","AVG","BABIP","HR9","GB_percent","HRperFB","ERA","KperBB",
"K_percent","BB_percent","K_minus_BB","WHIP","LD_percent","FB_percent","GBperFB")
pit_def <- c("MLB_name","MLBId","LastName","FirstName","LW","W","L","ERA","IP","H","HR","R","ER","BB","K","K9","BB9","HR9","WHIP",
"GB_percent","FB_percent","LD_percent","K_percent","BB_percent","KperBB","K_minus_BB")
ui <- shinyUI(fluidPage(
shinythemes::themeSelector(),
theme = shinytheme("paper"),
titlePanel("WSFB Stats Lab"),
fluidRow(
uiOutput("uis")
),
fluidRow(
tabsetPanel(id = "tabs",
tabPanel("Pitch Table",dataTableOutput("pitch_table"))
)
)
)
)
server <- shinyServer(function(input, output, session){
output$uis <- renderUI({
if(input$tabs == "Pitch Table")
{
pit <- read.csv("PIT_STAT.csv")
pit_stat <- c("MLB_name","MLBId","LastName","FirstName","LW","W","L","Sv","BS","HLD","G","GS","CG","GF","QS","SHO","IP","BFP","H","X1B","X2B","X3B",
"HR","R","ER","SH","SF","HBP","BB","IBB","BB_noIBB","K","WP","BLK","GB","FB","LD","POPU","SB",
"CS","PKO","SVO","OUTS","K9","BB9","AVG","BABIP","HR9","GB_percent","HRperFB","ERA","KperBB",
"K_percent","BB_percent","K_minus_BB","WHIP","LD_percent","FB_percent","GBperFB")
pit_def <- c("MLB_name","MLBId","LastName","FirstName","LW","W","L","ERA","IP","H","HR","R","ER","BB","K","K9","BB9","HR9","WHIP",
"GB_percent","FB_percent","LD_percent","K_percent","BB_percent","KperBB","K_minus_BB")
wellPanel(
checkboxGroupInput('show_vars', 'Variables to display', pit_stat, inline = TRUE, selected = pit_def),
selectInput("qualify_pit","MIN IP:",choices = c("YES","NO"))
)
}
})
output$pitch_table <- renderDataTable({
if(("YES" %in% input$qualify_pit))
{
pit <- read.csv("PIT_STAT.csv")
pit2 <- pit[pit$IP >= 162,]
DT::datatable(pit2[,input$show_vars, drop = FALSE])
}
if(("NO" %in% input$qualify_pit))
{
pit <- read.csv("PIT_STAT.csv")
DT::datatable(pit[,input$show_vars, drop = FALSE])
}
})
})
shinyApp(ui = ui, server = server)
It works with NO because the DT:datatable is the last expression of the function, therefore it is the implicit return value.
But for the YES, which is not the last evaluation (the if("NO" %in%... is), you have to explicitly use return:
return(DT::datatable(pit2[,input$show_vars, drop = FALSE]))
Otherwise you can simply use else
output$pitch_table <- renderDataTable({
if(("YES" %in% input$qualify_pit))
{
DT::datatable(pit[pit$IP >= 162,input$show_vars, drop = FALSE])
}
else
{
DT::datatable(pit[,input$show_vars, drop = FALSE])
}
})
For more details about using return you can read this thread
first I know there is a lot of threads covering my problem, I read them all, but I did not manage to do it. I got a list of 10 data.frame which I built through the following code :
list_of_df=list()
for (i in seq(1,10)){
number_row=sample(seq(5,10),size = 1)
num=seq(1,number_row)
val=sample(x = letters,size = number_row,replace = TRUE )
df=data.frame(num=num,
val=val)
rownames(df)=NULL
list_of_df[[i]]=df
}
I want the user to enter n, the number of tables he wants to see. And then display n random tables from the list_of_df. I want to display those tables inside tabs. Here is what I did, I grabbed some ideas here and there, but obviously it does not work and I do not know why.
library(shiny)
# ui function
ui = pageWithSidebar(
headerPanel('Dynamic Tabs'),
sidebarPanel(
numericInput(inputId = "numput",label = "number of tables",value = 1,min = 1,max = 5)
),
mainPanel(
uiOutput('mytabs')
)
)
# server function
server = function(input, output, session){
random_tables<- reactive({
index=sample(seq(1,10),size = input$numput,replace=FALSE)
list_of_df[[index]]
})
size<-reactive({
length(random_tables())
})
for (i in 1:size()) {
local({
my_i <- i
tablename <- paste("table_", my_i, sep="")
output[[tablename]] <- renderTable({
random_tables()[[i]]
})
})
}
output$mytabs = renderUI({
nTabs = size()
myTabs = lapply(paste0('table_', 1: nTabs), function(x){
tabPanel(x, tableOutput(x))
})
do.call(tabsetPanel, myTabs)
})
}
shinyApp(ui, server)
So, if you see what I should do ...
Here is a working version:
library(shiny)
# ui function
ui = pageWithSidebar(
headerPanel('Dynamic Tabs'),
sidebarPanel(
numericInput(inputId = 'numput',label = "number of tables",value = 1,min = 1,max = 5)
),
mainPanel(
uiOutput('mytabs')
)
)
# server function
server = function(input, output, session){
list_of_df=list()
for (i in seq(1,10)){
number_row=sample(seq(5,10),size = 1)
num=seq(1,number_row)
val=sample(x = letters,size = number_row,replace = TRUE )
df=data.frame(num=num,
val=val)
rownames(df)=NULL
list_of_df[[i]]=df
}
random_tables<- reactive({
index=sample(seq(1,10),size = input$numput,replace=FALSE)
list_of_df[index]
})
size<-reactive({
input$numput
})
observe({
lapply(seq_len(size()), function(i) {
local({
my_i <- i
tablename <- paste("table_", my_i, sep="")
output[[tablename]] <- renderTable({
random_tables()[[i]]
})
})
})
})
output$mytabs = renderUI({
nTabs = size()
myTabs = lapply(paste0('table_', seq_len(nTabs)), function(x){
tabPanel(x, tableOutput(x))
})
do.call(tabsetPanel, myTabs)
})
}
shinyApp(ui=ui,server=server)
A couple issues, you subset the list with double brackets, but it isn't working like you think it is, you need single brackets. Next when you select a single table random_table() is a data.frame so when you call length you get 2, the number of columns. So just use the input$numput for size() since they are the same anyways. Also, I put the dynamic output in an observe so that it can access the reactive size(). A small thing, but I used seq_len instead of 1:aNumber since it is more robust.
Hope this helps