EDITE :
I added one more example that is same as my problem. I want to update the checkboxGroupInput as dataset changes. And also want to render the table with checked column in the checkboxGroupInput options.
SERVER
shinyServer( function(input, output, session) {
dataset_list <- list( "rock" = rock,
"pressure" = pressure,
"cars" = cars
)
observeEvent( input$n_select_input, {
selected_dataset <- reactive({
selected_list <- list()
for( i in 1:input$n_select_input ){
selected_list[[i]] <- dataset_list[[i]]
}
names(selected_list) <- names( dataset_list )[1:input$n_select_input]
selected_list
})
colname_indata_list <- reactive({
colname.indata.list <- list()
for( set in names( selected_dataset() ) ){
colname.indata.list[[set]] <- colnames( selected_dataset()[[set]] )
}
colname.indata.list
})
choice_cand <- reactive({ names(selected_dataset()) })
updateSelectInput( session,
"dataset",
choices = as.character( choice_cand() )
)
choices_cand <- reactive({ colname_indata_list()[[input$dataset]] })
updateCheckboxGroupInput( session,
"column",
choices = as.character( choices_cand() )
)
})
# observeEvent( input$dataset, {
#
# choices_cand <- reactive({ colname_indata_list()[[input$dataset]] })
# updateCheckboxGroupInput( session, "column",
# choices = as.character( choices_cand() ) )
#
# })
datasetInput <- reactive({
switch(input$dataset,
"rock" = rock,
"pressure" = pressure,
"cars" = cars)
})
output$table <- renderTable({
datasetInput()
})
} )
I tried the code above in the ## , it didn't work.
UI
shinyUI(
fluidPage( titlePanel('Downloading Data'),
sidebarLayout(
sidebarPanel( numericInput( "n_select_input", "n select inpur", 1,
min=1, max=3 ),
selectInput("dataset", "Choose a dataset:",
choices = "" ),
checkboxGroupInput( "column", "select column",
choices = "")
),
mainPanel(
tableOutput('table')
)
)
)
)
FIRST WRITE :
I simplified the code below. I want to use updated select input as a output for the updatedCheckboxGroupInput 's choices. But the updated select input, input$select_group is null. I tried varies solutions.. but couldn't solve it.
If you just run this code right away, it doesn't work..
fund_group <- reactive({ # this is the list of fund group including fund name
# for example,
"domestic" = c("a","b", "c"),
"global" = c( "aa", "bb", "cc")
# list name and fund name in the list are changable
})
I want to update selectInput choices as names(fund_group) changes.
So I used code below,
observe({
group_name <- reactive({ names(fund_group()) })
updateSelectInput( session,
"select_group",
choices = group_name() )
fund_list <- reactive({ fund_group()[[input$select_group]] })
updateCheckboxGroupInput( session,
"fund_in_group",
choices = fund_list(),
selected = fund_list() )
})
For the UI,
narvarPage( "narvarTitle",
tabPanel( "tab panel",
fluidRow( column( 3, wellPanel( textOutput( "fixed_anal_date" ),
br(),
br(),
selectInput( "select_group",
label = "Select group",
choices = "" ),
br(),
checkboxGroupInput( "fund_in_group",
label = "Select funds :",
choices = "" ),
br()
) )
) )
Thank you for reading the messy code...
I have edited the code an its working now. You should put the two input in two different observe.
Here is the server. R:
server <- function(input, output, session){
fund_group <- reactive({ # this is the list of fund group including fund name
# for example,
list("domestic" = c("a","b", "c"), "global" = c( "aa", "bb", "cc"))
# list name and fund name in the list are changable
})
observe({
group_name <- reactive({ names(fund_group()) })
updateSelectInput( session,
"select_group",
choices = group_name() )
})
observe({
fund_list <- reactive({ fund_group()[[input$select_group]] })
updateCheckboxGroupInput( session,
"fund_in_group",
choices = fund_list(),
selected = fund_list())
})
}
Here is the ui.R:
ui <- navbarPage( "narvarTitle",
tabPanel( "tab panel",
fluidRow( column( 3, wellPanel( textOutput( "fixed_anual_date" ),
br(),
br(),
selectInput( "select_group",
label = "Select group",
choices = "" ),
br(),
checkboxGroupInput( "fund_in_group",
label = "Select funds :",
choices = "" ),
br()
) )
) )
)
[EDIT]:
As per your latest update I have modified the server code so that checkboxGrouptInput is updated as dataset changes and also the table is rendered for the checked columns.
shinyServer( function(input, output, session) {
dataset_list <- list( "rock" = rock,
"pressure" = pressure,
"cars" = cars
)
observeEvent( input$n_select_input, {
selected_dataset <- reactive({
selected_list <- list()
for( i in 1:input$n_select_input ){
selected_list[[i]] <- dataset_list[[i]]
}
names(selected_list) <- names( dataset_list )[1:input$n_select_input]
selected_list
})
colname_indata_list <- reactive({
colname.indata.list <- list()
for( set in names( selected_dataset() ) ){
colname.indata.list[[set]] <- colnames( selected_dataset()[[set]] )
}
colname.indata.list
})
choice_cand <- reactive({
names(selected_dataset()) })
updateSelectInput( session,
"dataset",
choices = as.character( choice_cand() )
)
######################################Start: Modified#############################
observe({
input$dataset ##Added so that this observe is called when the input$dataset changes
choices_cand <- reactive({
colname_indata_list()[[input$dataset]] })
updateCheckboxGroupInput( session,
"column",
choices = as.character( choices_cand()) ,
selected = as.character( choices_cand())
)
})
})
######################################End: Modified#############################
datasetInput <- reactive({
switch(input$dataset,
"rock" = rock,
"pressure" = pressure,
"cars" = cars)
})
output$table <- renderTable({
datasetInput()[,input$column]##only selected columns are displayed
})
} )
Hope this helps!
Related
In this shiny App (code below), I need that the button labeled 'Customized' returns:
Select var X: disp
Select var Y: drat
Point size: 1.0
This necessity is a bit similar to the reset button available on the R package 'shinyjs', with the diference of that the reset button returns to the code's default.
library(shiny)
library(shinyjs)
shinyApp(
ui <- fluidPage(
sidebarPanel(
fluidRow(
shinyjs::useShinyjs(),
id = "panel_vars",
# Buttons
uiOutput("varx"),
uiOutput("vary"),
numericInput("ptSize", "Point size",
min=.1, max=5, value = 2),
actionButton("p1", 'Reset variables XY'),
helpText(""),
actionButton("p2", 'Customized')
)
),
mainPanel(
plotOutput("plot")
)
),
server <- function(input, output) {
getModel <- reactive({
names(mtcars)
})
output$varx <- renderUI({
selectInput("varsel.x", "Select var X",
choices = as.list(getModel()), multiple = F)
})
output$vary <- renderUI({
selectInput("varsel.y", "Select var Y",
choices = as.list(getModel()), multiple = F)
})
observeEvent(input$p1, {
shinyjs::reset("panel_vars")
})
output$plot <- renderPlot({
p <- mtcars %>% ggplot(aes_string(x=input$varsel.x, y=input$varsel.y))+
geom_point(size=input$ptSize)
p
})
}
)
You can simply use updateSelectInput and updateNumericInput to do so:
library(shiny)
library(shinyjs)
library(dplyr)
library(ggplot2)
shinyApp(
ui <- fluidPage(
sidebarPanel(
fluidRow(
shinyjs::useShinyjs(),
id = "panel_vars",
# Buttons
uiOutput("varx"),
uiOutput("vary"),
numericInput("ptSize", "Point size",
min=.1, max=5, value = 2),
actionButton("p1", 'Reset variables XY'),
helpText(""),
actionButton("p2", 'Customized')
)
),
mainPanel(
plotOutput("plot")
)
),
server <- function(input, output,session) {
getModel <- reactive({
names(mtcars)
})
output$varx <- renderUI({
selectInput("varsel.x", "Select var X",
choices = as.list(getModel()), multiple = F)
})
output$vary <- renderUI({
selectInput("varsel.y", "Select var Y",
choices = as.list(getModel()), multiple = F)
})
observeEvent(input$p1, {
shinyjs::reset("panel_vars")
})
output$plot <- renderPlot({
req(input$varsel.x,input$varsel.y,input$ptSize)
p <- mtcars %>% ggplot(aes_string(x=input$varsel.x, y=input$varsel.y))+
geom_point(size=input$ptSize)
p
})
observeEvent(input$p2, {
updateSelectInput(session,'varsel.x',selected = 'disp')
updateSelectInput(session,'varsel.y',selected = 'drat')
updateNumericInput(session, "ptSize", value = 1.0)
})
}
)
I have the following code that basically uploads the data and once you have clicked on the row of the dataset you have uploaded, it reads the file. If you go to the second page in the navbar called regression you can choose variables from the dataset and run linear model. That works with the summary table. I want to achieve is something like here: https://towardsdatascience.com/build-an-interactive-machine-learning-model-with-shiny-and-flexdashboard-6d76f59a37f9
I want the prediction table and plot visualisation based on what has been selected. Appreciate your understanding and helpfulness.
library(shiny)
library(magrittr)
library(shiny)
library(readxl)
library(tidyverse)
library(DT)
library(reactable)
ui <- navbarPage("Demo",
tabPanel("Data Manipulation",
sidebarLayout(
sidebarPanel(
fileInput("upload", "Upload your file", multiple = TRUE, accept = c(".csv", ".xlsx") ),
selectInput('mydropdown', label = 'Select', choices = 'No choices here yet'),
h2("Modify variable type"),
selectInput("var_name", "Select variable", choices = c()),
radioButtons("action", NULL,
choiceNames = c("Make factor", "Make numeric"),
choiceValues = c("factor", "numeric")),
actionButton("modify", "Do it!"),
verbatimTextOutput("str")
),
mainPanel(
DT::DTOutput("files"),
reactable::reactableOutput("uploaded_files")
)
)
),
tabPanel("Regression",
sidebarLayout(
sidebarPanel(
selectInput("dep_var", "Select dependent variable", choices = c()),
selectInput("ind_var", "Select independent variables", choices = c(), multiple = TRUE),
actionButton("submit_reg", "Do it!")),
mainPanel(
verbatimTextOutput(outputId = "regsum")
)
)
),
)
server <- function(input, output, session) {
output$files <- DT::renderDT({
DT::datatable(input$upload, selection = c("single"))
})
selected_file <- reactiveVal()
observe({
## when developing, use a sample file you have on your computer so that you
## can load it immediately instead of going through button clicks
# demofile <- "/path/to/your/file.csv"
# selected_file( read.csv(demofile) )
# return()
req(input$upload, input$files_rows_selected)
idx <- input$files_rows_selected
file_info <- input$upload[idx, ]
if (tools::file_ext(file_info$datapath) == "csv") {
selected_file(read.csv(file_info$datapath))
} else if (tools::file_ext(file_info$datapath) == "xlsx") {
selected_file(readxl::read_xlsx(file_info$datapath))
} else {
stop("Invalid file type")
}
})
output$uploaded_files <- reactable::renderReactable({
req(selected_file())
reactable::reactable(
selected_file(),
searchable = TRUE
)
})
observe({
req(input$upload)
file_names <- input$upload$name
updateSelectInput(
session,
"mydropdown",
choices = file_names
)
})
observe({
req(selected_file())
updateSelectInput(session, "var_name", choices = names(selected_file()))
})
output$str <- renderPrint({
req(selected_file())
str(selected_file())
})
observeEvent(input$modify, {
df <- selected_file()
if (input$action == "factor") {
df[[input$var_name]] <- as.factor(df[[input$var_name]])
} else if (input$action == "numeric") {
df[[input$var_name]] <- as.numeric(df[[input$var_name]])
} else {
stop("Invalid action")
}
selected_file(df)
})
# Second Page
observe({
req(selected_file())
Dependent <- updateSelectInput(session, "dep_var", choices = names(selected_file()))
})
observe({
req(selected_file())
Independent <- updateSelectInput(session, "ind_var", choices = names(selected_file()))
})
observeEvent(input$submit_reg, {
lm1 <- reactive({
req(selected_file())
Model1 <- lm(reformulate(input$ind_var, input$dep_var), data = selected_file())})
options(scipen=999)
output$regsum <- renderPrint({summary(lm1())})
DT::renderDataTable({
df <- req(selected_file())
DT::datatable(df %>% select(input$dep_var, input$ind_var) %>% mutate(predicted = predict(lm1()), residuals = residuals(lm1())) %>% select(input$dep_var, predicted, residuals),
rownames = FALSE, colnames = c('actual value', 'predicted value', 'residuals'), extensions = c('Buttons', 'Responsive'),
options = list(columnDefs = list(list(className = 'dt-center', targets = "_all")), dom = 'Blfrt',
buttons = c('copy', 'csv', 'excel', 'print'), searching = FALSE, lengthMenu = c(20, 100, 1000, nrow(housing)), scrollY = 300, scrollCollapse = TRUE))
})
})
}
shinyApp(ui, server)
I have tried this in different ways and achieved one task, either add or delete., but i couldn't get complete solution in one, i might be missing some small concept somewhere.. I am adding the code , please help me complete my basic app.
library(shiny)
library(DT)
x<- data.frame(v1 = NA,
v2 = NA
),
ui = shinyUI(
fluidPage(
sidebarLayout(
sidebarPanel(
textInput("v1","v1","a"),
numericInput("V2","V2","1"),
# Row selection
numericInput(inputId = "row.selection", label = "Select row to be
deleted", min = 1, max = 100, value = "")
# Add button
actionButton(inputId = "add.button", label = "Add", icon =
icon("plus")),
# Delete button
actionButton(inputId = "delete.button", label = "Delete", icon =
icon("minus")),
),
mainPanel(
dataTableOutput('table')
)
)
)
),
Server side code
server = function(input, output, session) {
values <- reactiveValues()
values$df <- x
newEntry <- observe({
cat("newEntry\n")
if(input$add.button > 0) {
newRow <- data.frame(input$v1, input$v2)
isolate(values$df <- rbind(values$df,newRow))
}
})
deleteEntry <- observe({
cat("deleteEntry\n")
if(input$delete.button > 0) {
if(is.na(isolate(input$row.selection))){
values$df <- isolate(values$df[-nrow(values$df), ])
} else {
values$df <- isolate(values$df[-input$row.selection, ])
}
}
})
output$table = renderDataTable({
values$df
})
}
Try to use observeEvent rather than obser with actionbutton
and also, you have uppercase and lowercase issue with input$v2 (should be input$V2)
Try this modified code:
library(shiny)
library(DT)
x<- data.frame(v1 = NA,
v2 = NA
)
ui = shinyUI(
fluidPage(
sidebarLayout(
sidebarPanel(
textInput("v1","v1","a"),
numericInput("V2","V2","1"),
# Row selection
numericInput(inputId = "row.selection", label = "Select row to be
deleted", min = 1, max = 100, value = ""),
# Add button
actionButton(inputId = "add.button", label = "Add", icon =
icon("plus")),
# Delete button
actionButton(inputId = "delete.button", label = "Delete", icon =
icon("minus"))
),
mainPanel(
dataTableOutput('table')
)
)
)
)
server = function(input, output, session) {
values <- reactiveValues()
values$df <- x
observeEvent(input$add.button,{
cat("addEntry\n")
print(input$v1)
print(input$V2)
newRow <- data.frame(input$v1, input$V2)
colnames(newRow)<-colnames(values$df)
values$df <- rbind(values$df,newRow)
print(nrow(values$df))
})
observeEvent(input$delete.button,{
cat("deleteEntry\n")
if(is.na(input$row.selection)){
values$df <- values$df[-nrow(values$df), ]
} else {
values$df <- values$df[-input$row.selection, ]
}
})
output$table = renderDataTable({
values$df
})
}
shinyApp(ui,server)
Just run all the code above, and it should work properly.
I have a data table with filter enabled and i want to read selected rows from this data table.
input$table_rows_selected works fine if the filter is not applied however once i apply filter on data then correct rowindex is not returned.
ui <- function(id) {
fluidPage(
title = "Job Tracker",
fluidRow(
column(width=6,
selectInput("pickvalue", label = "Pick a Value", choices = unique(iris$Species))
)
),
br(),
fluidRow(
column(12,
DT::dataTableOutput("job_data")
)
),
br(),
fluidRow(
column(12,DT::dataTableOutput("x4"))
)
)
}
server <- function(input, output, session)
{
output$job_data <- DT::renderDataTable({
datatable(iris[iris$Species==input$pickvalue,],selection = "single")
})
output$x4 <- DT::renderDataTable({
s <- input$job_data_rows_selected
datatable(iris[s,])
})
}
To return previously selected row index you can add some reactiveValues to track the index like so, please note that the index is subject to data so if you select index = 4 and switch the data, the index = 4 will be applied to new data:
library(shiny)
library(DT)
ui <- function(id) {
fluidPage(
title = "Job Tracker",
fluidRow(
column(width=6,
selectInput("pickvalue", label = "Pick a Value", choices = unique(iris$Species))
)
),
br(),
fluidRow(
column(12,
DT::dataTableOutput("job_data")
)
),
br(),
fluidRow(
column(12,DT::dataTableOutput("x4"))
)
)
}
server <- function(input, output, session){
v <- reactiveValues()
v$s <- NULL
data <- reactive({
iris[iris$Species==input$pickvalue,]
})
output$job_data <- DT::renderDataTable({
datatable(data(),selection = "single")
})
observe({
if(!is.null(input$job_data_rows_selected)){
v$s <- input$job_data_rows_selected
}
})
output$x4 <- DT::renderDataTable({
datatable(data()[v$s,])
})
}
shinyApp(ui, server)
If you want to keep the index correctly, remove rownames:
data <- reactive({
data <- (iris[iris$Species==input$pickvalue,])
rownames(data) <- NULL
data
})
This app is creating a vector of standardised names which I create given some user input (number of channels and replicates). An example of the standard names given the number of channels = 4 and and replicates = 1 is as follows:
c("rep1_C0","rep1_C1","rep1_C2","rep1_C3")
I would like to allow the user to replace the value of the selection with their own custom value. For example to change the input "rep1_C0" to "Control_rep1". And then for it to then update the reactive vector in question. Here is my code:
library(shiny)
ui <- shinyUI(fluidPage(
sidebarLayout(
sidebarPanel(
fluidRow(column(5, numericInput("chans","# Channels",value = 4, min = 1)),
column(5, numericInput("reps","# Replicates",value = 1,min = 1))
),
uiOutput("selectnames")
),
mainPanel(
tableOutput("testcols")
)
)
))
server <- shinyServer(function(input, output) {
standardNames <- reactive({
paste("rep",rep(1:input$reps,each = input$chans),"_",
rep(paste("C",0:(input$chans - 1), sep = ""),input$reps),sep = "")
})
output$selectnames <- renderUI({
selectizeInput("selectnames", "Change Names", choices = standardNames(),
options = list(maxOptions = input$reps * input$chans))
})
## output
output$testcols <- renderTable({
standardNames()
})
})
shinyApp(ui = ui, server = server)
Is there some kind of option I can pass in the options sections that will allow this?
With selectizeInput you can set options = list(create = TRUE) to allow the user to add levels to the selection list, but I don't think that is what you want.
Instead, here is code that generates a text input box for each of the standard names, and allows the user to enter a label for them. It uses lapply and sapply to loop over each value and generate/read the inputs.
library(shiny)
ui <- shinyUI(fluidPage(
sidebarLayout(
sidebarPanel(
fluidRow(column(5, numericInput("chans","# Channels",value = 4, min = 1)),
column(5, numericInput("reps","# Replicates",value = 1,min = 1))
),
uiOutput("setNames")
),
mainPanel(
tableOutput("testcols")
)
)
))
server <- shinyServer(function(input, output) {
standardNames <- reactive({
paste("rep",rep(1:input$reps,each = input$chans),"_",
rep(paste("C",0:(input$chans - 1), sep = ""),input$reps),sep = "")
})
output$setNames <- renderUI({
lapply(standardNames(), function(thisName){
textInput(paste0("stdName_", thisName)
, thisName
, thisName)
})
})
labelNames <- reactive({
sapply(standardNames()
, function(thisName){
input[[paste0("stdName_", thisName)]]
})
})
## output
output$testcols <- renderTable({
data.frame(
stdName = standardNames()
, label = labelNames()
)
})
})
shinyApp(ui = ui, server = server)
If you want to hide the list unless the user wants to add labels, you can use a simple checkbox, like this, which hides the label making list until the use checks the box to show it.
library(shiny)
ui <- shinyUI(fluidPage(
sidebarLayout(
sidebarPanel(
fluidRow(column(5, numericInput("chans","# Channels",value = 4, min = 1)),
column(5, numericInput("reps","# Replicates",value = 1,min = 1))
)
, checkboxInput("customNames", "Customize names?")
, uiOutput("setNames")
),
mainPanel(
tableOutput("testcols")
)
)
))
server <- shinyServer(function(input, output) {
standardNames <- reactive({
paste("rep",rep(1:input$reps,each = input$chans),"_",
rep(paste("C",0:(input$chans - 1), sep = ""),input$reps),sep = "")
})
output$setNames <- renderUI({
if(!input$customNames){
return(NULL)
}
lapply(standardNames(), function(thisName){
textInput(paste0("stdName_", thisName)
, thisName
, thisName)
})
})
labelNames <- reactive({
if(!input$customNames){
return(standardNames())
}
sapply(standardNames()
, function(thisName){
input[[paste0("stdName_", thisName)]]
})
})
## output
output$testcols <- renderTable({
data.frame(
stdName = standardNames()
, label = labelNames()
)
})
})
shinyApp(ui = ui, server = server)
Alternatively, if you think the user may want to only change one or a small number of labels, here is a way to allow them to choose which standard name they are applying a label to:
library(shiny)
ui <- shinyUI(fluidPage(
sidebarLayout(
sidebarPanel(
fluidRow(column(5, numericInput("chans","# Channels",value = 4, min = 1)),
column(5, numericInput("reps","# Replicates",value = 1,min = 1))
)
, uiOutput("setNames")
),
mainPanel(
tableOutput("testcols")
)
)
))
server <- shinyServer(function(input, output) {
vals <- reactiveValues(
labelNames = character()
)
standardNames <- reactive({
out <- paste("rep",rep(1:input$reps,each = input$chans),"_",
rep(paste("C",0:(input$chans - 1), sep = ""),input$reps),sep = "")
vals$labelNames = setNames(out, out)
return(out)
})
output$setNames <- renderUI({
list(
h4("Add labels")
, selectInput("nameToChange", "Standard name to label"
, names(vals$labelNames))
, textInput("labelToAdd", "Label to apply")
, actionButton("makeLabel", "Set label")
)
})
observeEvent(input$makeLabel, {
vals$labelNames[input$nameToChange] <- input$labelToAdd
})
## output
output$testcols <- renderTable({
data.frame(
stdName = standardNames()
, label = vals$labelNames
)
})
})
shinyApp(ui = ui, server = server)