R Shiny create input using renderUI and function results - r

I am new to R Shiny and I am trying to create an app which I need it to be as interactive as possible. One problem that I am dealing with is this. In the ui.R I have the following:
helpText("Select a feature"),
uiOutput("sliders")
And in the server.R:
output$sliders <- renderUI({
selectInput('feature_name',
'Feature name', #Description
choice = c("F1"='1', "F2"='2'))
})
My question is that is it possible to change something in renderUI so that instead of setting c("F1"='1', "F2"='2')) statically I can pass the results of a function to it so it can be more dynamic (a function which generates a feature list based on something that user does and passes the list to renderUI to create the selectInput). Something like following:
output$sliders <- renderUI({
selectInput('feature_name',
'Feature name', #Description
choice = c(feature_creator(method)))
})
Where "feature_creator" is a function and it returns: "F1"='1', "F2"='2' based on the method selected by user (variable "method" is defined and I have the value). My question to be more specific is what should "feature_creator" return as output?
Hope my question is clear enough. Let me know if I should add anything to the problem description.
Any help will be much appreciated. Thanks


Assuming that all you really need is the method argument, this is not hard.
1) Make a radioButtons() input in your ui that will let the user select a method, lets give it inputId="MethodChoice".
2) In your choice argument in the selectInput you should use choice=c(feature_creator(input$MethodChoice))
Then feature_creator will get a text value based on the method the user chooses.
In order to work in choice, feature_creator should return a named list, similar in format to what you hard-coded.

Related

How to make changes reflect in many places when input is changed without ObserveEvent() in shiny

I have an input variable input$shop_id. Which is used to get data in server function using:
observeEvent(input$shop_id,{id<<-input$shop_id})
`Data=dbGetQuery(connection_name,paste0("SELECT * FROM tab_name WHERE id_shop=",id"))`
That Data is further used to create dynamic UI using selectInput()
output$dependant=renderUI({
selectInput("choice","Choose the Data you want to view",names(Data))
})
I can't come up with the logic of the arrangement of these functions. I cannot get it to work. I have created a sample data and similar sample code for someone to try on:
library(shiny)
library(ggplot2)
ui=fluidPage(
column(6,uiOutput("shop_select")),
column(6,uiOutput("cust_select")),
column(6,uiOutput("select3")),
column(12,offset=6,uiOutput("plot"))
)
server = function(input, output) {
#sample data
shopdata=data.frame(id=c(1,2,3,4,5,6,7,8,9,10),name=c("a","b","c","d","e","f","g","h","i","j"))
cdata=data.frame(id=c(123,465,6798,346,12341,45764,2358,67,457,5687,4562,23,12124,3453,12112),
name=c("sadf","porhg","wetgfjg","hwfhjh","yuigkug","syuif","rtyg","dygfjg","rturjh","kuser","zzsdfadf","jgjwer","jywe","jwehfhjh","kuwerg"),
shop=c(1,2,1,2,4,6,2,8,9,10,3,1,2,5,7),
bill_total=c(12341,123443,456433,234522,45645,23445,3456246,23522,22345,23345,23454,345734,23242,232456,345456),
crating=c(4,4.3,5,1.2,3.2,4,3.3,2.4,3.8,3,3.2,3.3,1.4,2.8,4.1))
output$shop_select=renderUI({
selectInput("shop_id","Shop ID",shopdata$id)
})
output$cust_select=renderUI({
selectInput("cust_id","Customer ID",cdata$id,multiple = T)
})
output$select3=renderUI({
a=input$shop_id
selectInput("choice","Choose the Data you want to view",names(cdata))
})
output$plot=renderUI({
renderPlot({
require(input$choice)
plotOutput(
ggplot(cdata,aes(x=cust_id,y=input$choice))
)})})
}
shinyApp(ui=ui,server=server)
I know I am not clear on the question. Fixing the code which I posted is more than enough to clear my doubt. Basically, I just need to know what is the logic when we have to use while using a renderUI() which is dependent on another renderUI()

If you want to set up a series of subsetting operations and then call renderUI()s on each subset, you will need to take advantage of Shiny's reactive({}) expressions.
Reactive expressions are code chunks that produce variables and their magic is that they "watch" for any changes to their input data. So in your case one you select a shop_id in the first UI element, the reactive expression detects that and updates itself, automatically!
Here is an example showing the updating, just select different shop_id's and watch the available cust_ids change on the fly.
library(shiny)
library(ggplot2)
library(tidyverse)
ui=fluidPage(
column(6,uiOutput("shop_select")),
column(6,uiOutput("cust_select")),
column(6,uiOutput("select3")),
column(12,offset=6,tableOutput("plot"))
)
server = function(input, output) {
#sample data
shopdata=data.frame(id=c(1,2,3,4,5,6,7,8,9,10),name=c("a","b","c","d","e","f","g","h","i","j"))
cdata=data.frame(id=c(123,465,6798,346,12341,45764,2358,67,457,5687,4562,23,12124,3453,12112),
name=c("sadf","porhg","wetgfjg","hwfhjh","yuigkug","syuif","rtyg","dygfjg","rturjh","kuser","zzsdfadf","jgjwer","jywe","jwehfhjh","kuwerg"),
shop=c(1,2,1,2,4,6,2,8,9,10,3,1,2,5,7),
bill_total=c(12341,123443,456433,234522,45645,23445,3456246,23522,22345,23345,23454,345734,23242,232456,345456),
crating=c(4,4.3,5,1.2,3.2,4,3.3,2.4,3.8,3,3.2,3.3,1.4,2.8,4.1))
output$shop_select=renderUI({
selectInput("shop_id","Shop ID",shopdata$id)
})
cdata_reactive <- reactive({
req(input$shop_id)
filter(cdata, shop == input$shop_id)
})
output$cust_select=renderUI({
selectInput("cust_id","Customer ID",cdata_reactive()$id, multiple = T)
})
output$select3=renderUI({
selectInput("choice","Choose the Data you want to view",names(cdata_reactive()))
})
output$plot <- renderTable({
filter(cdata_reactive(), id %in% input$cust_id) %>%
.[input$choice]
})
}
shinyApp(ui=ui,server=server)

A renderUI generates UI elements. Therefore it can only contain ui functions. You need to use it to generate the plotOutput and then use renderPlot separately to add content.
The names you assign in the aes call are the names of variables in the data frame you provided. Therefore x should be id not the values of input$cust_id (which must be called as input$cust_id, since it refers to an input object.
input$choice returns a string, not an object, so you can't use it normally in aes (recall that if this was a normal dataframe your aes would be aes(x=id, y=choice) not aes(x='id', y='choice'). Therefore, you need to use aes_ with the as.name function to convert those strings into proper variable names.
What I think you want to do with input$cust_id is filter cdata to only include rows with the chosen id values. dplyr::filter is the best way to do that.
Finally, you're missing a geom_* in your ggplot call which is needed to actually render your data.
If you replace your output$plot <- ... call with the below code it should work the way I think you want it to:
output$plot=renderUI({
plotOutput('plotout')
})
output$plotout <- renderPlot({
ggplot(dplyr::filter(cdata, id %in% input$cust_id),
aes_(x=as.name('id'),y=as.name(input$choice))) +
geom_point()
})
As for the question in your title, you only need to use observeEvent if you want to limit the code in the expression to only run when a specific trigger occurs. Any reactive expression (reactive, observe, render_ etc.) will become invalidated and update itself if any reactive value (either a reactiveValues object or an input$...) changes. If you have an input$ or a reactive value in a render_ block, it will update if they change -- no observeEvent needed.

Is it possible to have a Shiny ConditionalPanel whose condition is a global variable?

My goal is to have a tabsetPanel wrapped in a conditionalPanel whose condition is a global variable being false.
ui.R
mainPanel(
conditionalPanel("searchPage == \"false\"",
tabsetPanel(
tabPanel("Summary",htmlOutput("summary")),
tabPanel("Description", htmlOutput("description"))
))),
global.R
searchPage <- "true"
then in server.R I assign new values to it a few different times, but all like this:
observeEvent(input$openButton,
output$results <- renderUI({
textOutput("")
searchPage <- "false"
}))
No matter what I do, I always get "Uncaught ReferenceError: searchPage is not defined". I've tried changing the global.R to multiple different combinations of using quotes, not using quotes, using <- or <<-, making it this.searchPage, my.searchPage and numerous other things (of course always making server.R and ui.R match too), but haven't had much luck at all.

As mentioned in a comment on the question's post, this is a perfect usecase for the shinyjs toggle()/show()/hide() functions. Whenever you need to conditionally show something where the condition is not a simple javascript expression of an input, it's easy to use these functions instead of a conditionalPanel().
In order to use these functions, you need to have some way to specify the element you want to hide/show (in this case, the mainPanel()). The easist way to do this is to just wrap the entire panel in a div with an id. So define the panel like mainPanel(div(id = "mainpanel", ...)) and voila, there's an id to your panel, and now you can call shinyjs::show("mainpanel") or hide() whenever you want in the server code.

What you are trying to do is not really possible the way you are trying to do it (the server and client are in different environments and don't share variables). You will need to explicitly pass the value from server to client, and there are different approaches to doing that. One way:
library(shiny)
runApp(list(ui = fluidPage(
conditionalPanel(condition='output.bool',
HTML("Hello world")),
actionButton("btn","Press me to toggle")
),
server = function(input, output, session) {
value=TRUE
output$bool <- eventReactive(input$btn,{
value
})
outputOptions(output,"bool",suspendWhenHidden=FALSE)
observeEvent(input$btn,
value <<- !value
)
}))
There are probably better approaches. Hope this helps

Slow grep() within shiny program

I have built a shiny application which is located at the URL below.
https://hdoran.shinyapps.io/openAnalysis/
On the tab called "Choose CrossFit Open Data" I have a textInput() function that calls a function that uses grep(), which is used to find names in a data frame.
The first time the program loads and a name is entered, the search seemingly occurs quickly and names are returned. However, when I delete the name and type a second name, the search is seemingly very slow.
Is there something I can do to optimize this so that is performs quickly always?
I'm still quite new at shiny and am not sure if somehow making this a reactive expression would help. If so, I'm not quite sure how.
Thanks in advance.
The relevant portion of code in the ui.R file
textInput("name", label = 'Enter an athlete name and find your scores',
value = "Enter Name Here")
and the relevant portion of code in the server.R file is
output$myScores <- renderPrint({
df <- filedata()
df[grep(input$name, df$Competitor),]
})
And this portion is also in the ui.R file (though I'm not sure it is relevant to the problem)
verbatimTextOutput("myScores"),

If I understand your goal correctly, you want to give the user the ability to select an input variable based on searching a the competitor column of the dataframe called by filedata()? If so, selectizeInput() is what you are looking for, using server-side selection as outlined here.
Adapted to the code you provided:
ui.r
selectizeInput("name", choices = NULL, multiple = FALSE)
server.r
updateSelectizeInput(session, "name", choices = filedata()$competitor, server = TRUE)
output$myScores <- renderPrint({
df <- filedata()
subset(df, competitor==input$name)
})

R and Shiny: Using output of a reactive function

Currently I have a function [degtest] which is created in the shiny server, that returns a list,
return(list(datatable=datatable, predicttable=predicttable, esttable=esttable)
I want this list to be accessible after the function has run so that I can use different parts of the list to be rendered separately.
outlist <- reactive({
if(is.null(input$file2)){return(NULL)}
if(input$d2 == 0){return(NULL)}
with(data = reactdata$degdata, degtest(reactdata$degdata[,input$selectTemp], reactdata$degdata[,input$selectPot],reactdata$degdata[,input$selectWeight], reactdata$degdata[,input$selectTime], input$Temp0))
})
input$file2 is my reactdata (reactdata$degdata and input$d2 is an action button.
I thought i'd be able to reference outlist$datatable but R says ' object of type 'closure' is not subsettable'

When you are making an object reactive, you are actually making it into a sort of function (closure), so you have to use it as outlist() rather than outlist. See this similar question. It's hard to answer your question considering you did not provide a reproducible example, but I think your solution will be something like outlist()$ObjectYouAreTryingToAccess.

Receiving input from various actionbuttons in Shiny R

So this is somehow a follow up to my previous: Automatic GUI Generating in R Shiny wher I posted the solution to how to generate elements iteratively.
Now I am unable to recieve/check which actionbuttons have been pressed and perform some action upon press.
In general, there is a function that generates the buttons and sends it to the ui.R:
output$generateImages <- renderUI({
(...)
i <-1
for(dir in folders){
(...)
txt<-paste0("rep",i)
pp<-pathNameToImage
LL[[i]] <- list(actionButton(txt,icon=imageOutput(pp,width="100px",height="100px"),label=dir))
i<-i+1
}
return(LL)
}
in ui.R I have:
uiOutput('generateImages')
And it displays the buttons fine by accumulating them into the list called "LL".
I have tried looking for tutorials and examples but was not able to find how it is done with images, and how to later recieve input from buttons that were not created "by hand", but iteratively.
How do I access these buttons in "observe" so that I can perform a action? I have tried input$generateImages, input$LL and few others, but all of them had a value of NULL.

You'll need to access them by their unique ID. The first argument passed to actionButton is its ID. That's what you'll need to use to get it as input.
So:
LL[[i]] <- list(actionButton("SomeID"))
when you assign it, then
input[["SomeID"]]
when you want to reference it. Of course, you can use a variable instead of a hardcoded string for the ID.

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