This question is an extension of the question I posted: this question
I created a dataframe with 3 columns: num, id and val. I want my shiny app to do the following:
a dataframe dat is filtered by num column
select an value from id column from dat (selectInput).
add text comment in a text box (textInput)
click on an action button
A new column called comment is created in the data table, text comments are added to the comment column in the row where id equals the value selected.
The code is below. I cannot figure out why it's not working.
Thank a lot in advance!
library(shiny)
library(DT)
dat = data.frame(num=rep(1:2, each=5), id=rep(LETTERS[1:5],2), val=rnorm(10))
ui = fluidPage(
fluidRow(
column(12, selectInput('selectNum', label='Select Num',
choices=1:10, selected='')),
column(2, selectInput(inputId = 'selectID',
label = 'Select ID2',
choices = LETTERS[1:10],
selected='',
multiple=TRUE)),
column(6, textInput(inputId = 'comment',
label ='Please add comment in the text box:',
value = "", width = NULL,
placeholder = NULL)),
column(2, actionButton(inputId = "button",
label = "Add Comment"))
),
fluidRow (
column(12, DT::dataTableOutput('data') )
)
)
server <- function(input, output, session) {
## make df reactive
df = reactive ({ dat %>% filter(num %in% input$selectNum) })
df_current <- reactiveVal(df())
observeEvent(input$button, {
req(df_current())
## update df by adding comments
df_new <- df_current()
df_new[df_current()$id %in% input$selectID, "Comment"] <- input$comment
df_current(df_new)
})
output$data <- DT::renderDataTable({
req(df_current())
DT::datatable(df_current(),
options = list(orderClasses = TRUE,
lengthMenu = c(5, 10, 20), pageLength = 5))
})
shinyApp(ui=ui, server=server)
Instead of using a reactive/eventReactive statement for df, it might be more natural to keep track of previously inputted comments in the Comment column using a reactiveVal object for df. See also the responses to this question: R Shiny: reactiveValues vs reactive. If you prefer to use a reactive/eventReactive statement for df it is probably better to work with a separate object to store previous input comments (instead of incorporating it into the reactive statement for df).
library(shiny)
library(DT)
dat = data.frame(num=1:10, id=LETTERS[1:10], val=rnorm(10))
ui = fluidPage(
fluidRow(
column(12, selectInput('selectNum', label='Select Num',
choices=1:10)),
column(2, selectInput(inputId = 'selectID',
label = 'Select ID2',
choices = LETTERS[1:10],
selected='',
multiple=TRUE)),
column(6, textInput(inputId = 'comment',
label ='Please add comment in the text box:',
value = "", width = NULL,
placeholder = NULL)),
column(2, actionButton(inputId = "button",
label = "Add Comment"))
),
fluidRow (
column(12, DT::dataTableOutput('data') )
)
)
server <- function(input, output, session) {
## make df reactive
df_current <- reactiveVal(dat)
observeEvent(input$button, {
req(df_current(), input$selectID %in% dat$id)
## update df by adding comments
df_new <- df_current()
df_new[df_current()$id %in% input$selectID, "Comment"] <- input$comment
df_current(df_new)
})
output$data <- DT::renderDataTable({
req(df_current())
## filter df_current by 'selectNum'
df_filtered <- df_current()[df_current()$num %in% input$selectNum, ]
## show comments if non-empty
showComments <- is.null(df_filtered$Comment) || !all(is.na(df_filtered$Comment))
DT::datatable(df_filtered,
options = list(orderClasses = TRUE,
lengthMenu = c(5, 10, 20), pageLength = 5,
columnDefs = list(
list(targets = ncol(df_filtered), visible = showComments)
)
)
)
})
}
shinyApp(ui=ui, server=server)
Edit: below an edited server function that using df_current <- reactive({...}) instead of df_current <- reactiveVal({...}) and defining a separate reactiveVal object to keep track of the comments.
server <- function(input, output, session) {
## initialize separate reactive object for comments
df_comments <- reactiveVal({
data.frame(
id = character(0),
Comment = character(0),
stringsAsFactors = FALSE
)
})
## reactive object df
df_current <- reactive({
## reactivity that df depends on
## currently df = dat does not change
df <- dat
## merge with current comments
if(nrow(df_comments()) > 0)
df <- merge(df, df_comments(), by = "id", all.x = TRUE)
return(df)
})
observeEvent(input$button, {
req(input$selectID)
## update df_comments by adding comments
df_comments_new <- rbind(df_comments(),
data.frame(id = input$selectID, Comment = input$comment)
)
## if duplicated id's keep only most recent rows
df_comments_new <- df_comments_new[!duplicated(df_comments_new$id, fromLast = TRUE), , drop = FALSE]
df_comments(df_comments_new)
})
output$data <- DT::renderDataTable({
req(df_current())
## filter df_current by 'selectNum'
df_filtered <- df_current()[df_current()$num %in% input$selectNum, ]
## show comments if non-empty
showComments <- is.null(df_filtered$Comment) || !all(is.na(df_filtered$Comment))
DT::datatable(df_filtered,
options = list(orderClasses = TRUE,
lengthMenu = c(5, 10, 20), pageLength = 5,
columnDefs = list(
list(targets = ncol(df_filtered), visible = showComments)
)
)
)
})
}
There you have got a working example.
I think the thing is that you are trying to update a value through an observeEvent which is not good according to the documentation. ?observeEvent
Use observeEvent whenever you want to perform an action in response to an event. (Note that "recalculate a value" does not generally count as performing an action–see eventReactive for that.)
library(shiny)
library(DT)
dat = data.frame(num=1:10, id=LETTERS[1:10], val=rnorm(10))
ui = fluidPage(
fluidRow(
column(12, selectInput('selectNum', label='Select Num',
choices=1:10, selected='')),
column(2, selectInput(inputId = 'selectID',
label = 'Select ID2',
choices = LETTERS[1:10],
selected='',
multiple=TRUE)),
column(6, textInput(inputId = 'comment',
label ='Please add comment in the text box:',
value = "", width = NULL,
placeholder = NULL)),
column(2, actionButton(inputId = "button",
label = "Add Comment"))
),
fluidRow (
column(12, DT::dataTableOutput('data') )
)
)
server <- function(input, output, session) {
## make df reactive
df_current = reactive({
df = dat %>% filter(num %in% input$selectNum)
if(input$button != 0) {
input$button
df[df$id %in% input$selectID, "Comment"] <- isolate(input$comment)
}
return(df)
})
output$data <- DT::renderDataTable({
req(df_current())
DT::datatable(df_current(),
options = list(orderClasses = TRUE,
lengthMenu = c(5, 10, 20), pageLength = 5))
})
}
shinyApp(ui=ui, server=server)
So you can either go with your reactive value or using eventReactive as stated in the doc.
Related
The user interface of the Shiny app I'm working on is supposed to work in the following manner:
User finds the desired observation(s) after applying a set of filters.
User clicks "Add" action button, so selected observation(s) are added to a running list/vector/etc of observations to be analyzed.
User modifies filters to find other observations which are to be included as well.
Loop back to step 1 as many times as user desires.
I cannot seem to find a way to save this list of observations to be analyzed. In the example I attached, the "observation ID" is the name of the model of the car (mtcars is used). I also did not include any data analysis, since I do not think that's necessary. In essence, the entire dataset (mtcars) should be filtered using dplyr in a reactive environment to only include the running list of selected observations.
Here's the code:
data("mtcars")
mtcars$model <- rownames(mtcars)
ui <- fluidPage(
titlePanel("sample"),
sidebarLayout(
sidebarPanel(
uiOutput("disp"),
uiOutput("qsec"),
uiOutput("model"),
actionButton("add", "Add"),
uiOutput("selectedModel")
),
mainPanel(
plotOutput("data_analysis")
)
)
)
server <- function(input, output) {
output$disp <- renderUI({
selectInput(
"disp_sel",
"Select disp:",
unique(mtcars$disp),
selected = NULL,
multiple = T,
selectize = T
)
})
output$qsec <- renderUI({
temp = mtcars
if (!is.null(input$disp_sel)){temp = temp %>% filter(disp %in% input$disp_sel)}
selectInput(
"qsec_sel",
"Select qsec:",
unique(temp$qsec),
selected = NULL,
multiple = T,
selectize = T
)
})
output$model <- renderUI({
temp = mtcars
if (!is.null(input$disp_sel)){temp = temp %>% filter(disp %in% input$disp_sel)}
if (!is.null(input$qsec_sel)){temp = temp %>% filter(qsec %in% input$qsec_sel)}
selectInput(
"model_sel",
"Select model:",
unique(temp$model),
selected = NULL,
multiple = T,
selectize = T
)
})
output$selectedModel <- renderUI({
req(input$add)
selectInput(
"list_of_selections",
"Selected models:",
unique(mtcars$model),
selected = NULL, # this should change when "Add" is pressed
multiple = T,
selectize = T
)
})
r_data = eventReactive(input$add,{
mtcars %>% filter(model %in% input$list_of_selections)
})
output$data_analysis <- renderPlot({
# do something with r_data (filtered data)
})
}
# Run the application
shinyApp(ui = ui, server = server)
I've looked into modular code, reactive lists, and other stuff I don't even remember... Any help is greatly appreciated.
Try this
data("mtcars")
mtcars$model <- rownames(mtcars)
df1 <- mtcars
ui <- fluidPage(
titlePanel("sample"),
sidebarLayout(
sidebarPanel(
uiOutput("disp"),
uiOutput("qsec"),
uiOutput("model"),
actionButton("add", "Add"),
uiOutput("selectedModel")
),
mainPanel(
DTOutput("selecteddata"),
plotOutput("data_analysis")
)
)
)
server <- function(input, output) {
output$disp <- renderUI({
selectInput(
"disp_sel",
"Select disp:",
unique(mtcars$disp),
selected = NULL,
multiple = T,
selectize = T
)
})
output$qsec <- renderUI({
temp = mtcars
if (!is.null(input$disp_sel)){temp = temp %>% filter(disp %in% input$disp_sel)}
selectInput(
"qsec_sel",
"Select qsec:",
unique(temp$qsec),
selected = NULL,
multiple = T,
selectize = T
)
})
output$model <- renderUI({
temp = mtcars
if (!is.null(input$disp_sel)){temp = temp %>% filter(disp %in% input$disp_sel)}
if (!is.null(input$qsec_sel)){temp = temp %>% filter(qsec %in% input$qsec_sel)}
selectInput(
"model_sel",
"Select model:",
unique(temp$model),
selected = NULL,
multiple = T,
selectize = T
)
})
selected_data <- eventReactive(input$add,{
df1 %>% filter(model %in% input$model_sel)
})
output$selecteddata <- renderDT(
selected_data(), # reactive data
class = "display nowrap compact", # style
filter = "top", # location of column filters
options = list( # options
scrollX = TRUE # allow user to scroll wide tables horizontally
)
)
output$selectedModel <- renderUI({
req(input$add)
selectInput(
"list_of_selections",
"Selected models:",
choices = unique(selected_data()$model),
selected = unique(selected_data()$model), # this should change when "Add" is pressed
multiple = T,
selectize = T
)
})
r_data = eventReactive(input$add,{
mtcars %>% filter(model %in% input$list_of_selections)
})
output$data_analysis <- renderPlot({
ggplot(data=selected_data(), aes(x=disp, y=qsec)) + geom_point()
# do something with r_data (filtered data)
})
}
# Run the application
shinyApp(ui = ui, server = server)
Found the answer. I included
selected <- reactiveValues(s = NULL)
observeEvent(input$add,{selected$s = c(selected$s, input$model})
into the server part. Then the selected models are stored in selected$s.
I have the dataframe below:
DF2 = data.frame(agency_postcode = factor(rep(c(12345,45678,24124,32525,32325),2)),
car_group=factor(rep(c("Microcar","City car","Supermini","Compact","SUV"),2)),
transmission=factor(rep(c("automatic","manual"),5)))
which I use and display as rhandsontable in order to create a second table. First you are supposed to select one or more options from filter by input and then a level from the selected filter(s). Then you press search. What I basically want to do is subset the second table based on the first row of every selected column of the first table. The issue is in line 30 of server.r in which I should give the input$sel
#ui.r
library(shiny)
library(rhandsontable)
ui <- fluidPage(
sidebarLayout(
sidebarPanel(width=2,
selectInput("sel","Filter by:",
choices = c("agency_postcode","date_start","days","car_group","transmission","driver_age"),
multiple=T,selected = "agency_postcode"),
actionButton("sr","Search")
),
mainPanel(
fluidRow(
column(4,offset = 0, style='padding:0px;',rHandsontableOutput("hot")),
column(8,offset = 0, style='padding:0px;',rHandsontableOutput("hot2"))
)
)
)
)
#server.r
#server.r
library(shiny)
library(rhandsontable)
library(jsonlite)
server <- function(input, output) {
#Create rhandsontable as a reactive expression
DFR2<-reactive({
rhandsontable(DF2[1,1:2], rowHeaders = NULL,height = 200)%>%
hot_col(colnames(DF2)[1:2])
})
#Display the rhandsontable
output$hot <- renderRHandsontable({
DFR2()
})
#Convert the rhandsontable to a daraframe
DFR3<-reactive({
req(input$hot)
hot_to_r(input$hot)
})
#Subset the initial dataframe by value of the 1st row-1st column cell of DF3
DFR4 <- reactive({
req(DFR3())
D<-DF2[ which(DF2[,1] %in% DFR3()[1, 1]), ] #input$sel is supposed to be used here instead of 1
for(i in 1:ncol(D)){
D[,i] <- factor(D[,i])
}
D
})
#Display the new rhandsontable
output$hot2 <- renderRHandsontable({
input$sr
isolate(rhandsontable(DFR4()[1,], rowHeaders = NULL,height = 200)%>%
hot_col(colnames(DFR4())) )
})
}
OK. Here is an app that uses a small table to filter a larger one using inner_join. I am not sure this will match the design you had in mind. It is still unclear to me where the filter levels are coming from, or what the hands on tables are for. But you should be able to adapt this approach to your design. Note also that I am not using hands on tables. A direct replacement of the calls to renderTable with renderRHandsontable should work too.
library(shiny)
library(dplyr)
library(purrr)
sub_cars <- mtcars[, c("cyl", "gear", "am")]
ui <- fluidPage(
column(width=3,
selectInput(
inputId = "sel_col",
label = "Select variables",
multiple = TRUE,
choices = c("cyl", "gear", "am"),
selectize = TRUE),
uiOutput("cyl"),
uiOutput("gear"),
uiOutput("am")
),
column(width = 3,
tableOutput("filter_table")),
column(width = 6,
tableOutput("large_table"))
)
server <- function(input, output) {
output$cyl <- renderUI({
if ("cyl" %in% input$sel_col) {
selectInput(
inputId = "sel_cyl",
label = "Select cylinders",
choices = unique(sub_cars$cyl),
multiple = TRUE,
selectize = TRUE
)
}
})
output$gear <- renderUI({
if ("gear" %in% input$sel_col) {
selectInput(
inputId = "sel_gear",
label = "Select gears",
choices = unique(sub_cars$gear),
multiple = TRUE,
selectize = TRUE
)
}
})
output$am <- renderUI({
if ("am" %in% input$sel_col) {
selectInput(
inputId = "sel_am",
label = "Select am",
choices = unique(sub_cars$am),
multiple = TRUE,
selectize = TRUE
)
}
})
# make a small filter table
filter_df <- reactive({
validate(
need(!is_null(input$sel_col),
message = "Please select a column"))
cols <- input$sel_col
cols_vals <- map(cols, function(x) input[[paste0("sel_", x, collapse="")]])
df <- map2_dfr(cols, cols_vals, function(x, y)
filter(sub_cars,!!as.name(x) %in% y)) %>%
select(one_of(cols)) %>%
distinct()
return(df)
})
output$filter_table <- renderTable({
validate(
need(nrow(filter_df()) > 0,
message = "Please select filter values"))
filter_df()
})
# inner join the larger table
large_df <- reactive({
validate(
need(nrow(filter_df()) > 0,
message = "Please select filter values"))
cols <- input$sel_col
inner_join(x=filter_df(), y=mtcars, by = cols)
})
output$large_table <- renderTable({large_df()})
}
shinyApp(ui, server)
Here is a gif of what it does.
I'm trying to create a shiny app where user is able to add text comment to a table.
I created a dataframe with 3 columns: num, id and val. I want my shiny app to do the following:
select an value from id column (selectInput).
add text comment in a text box (textInput)
click on an action button
A new column called comment is created in the data table, text comments are added to the comment column in the row where id equals the value selected.
My shiny app code is below. When I select an value from selectinput, add some comment in the text box and click on `add comment' button, my shiny app window shut down by itself.
Does anyone know why that happens?
Thanks a lot in advance!
library(shiny)
library(DT)
df = data.frame(num=1:10, id=LETTERS[1:10], val=rnorm(10))
ui = fluidPage(
fluidRow(
column(2, selectInput(inputId = 'selectID',
label = 'Select ID2',
choices = LETTERS[1:10],
selected='',
multiple=TRUE)),
column(6, textInput(inputId = 'comment',
label ='Please add comment in the text box:',
value = "", width = NULL,
placeholder = NULL)),
column(2, actionButton(inputId = "button",
label = "Add Comment"))
),
fluidRow (
column(12, DT::dataTableOutput('data') )
)
)
server <- function(input, output, session) {
observeEvent(input$button, {
df[id==input$selectID, 'Comment']=input$comment
})
output$data <- DT::renderDataTable({
DT::datatable(df,
options = list(orderClasses = TRUE,
lengthMenu = c(5, 10, 20), pageLength = 5))
})
}
shinyApp(ui=ui, server=server)
The column id is not recognized as a column of the data.frame df in df[id == input$selectId, "Comment], replacing id by df$id fixes the error.
In order to rerender the datatable after updating df, df should be a reactive object.
To handle multiple selected id's in the selectInput selectId, you might want to replace df$id == input$selectId by df$id %in% input$selectId
This updated server function should help you with these issues:
server <- function(input, output, session) {
## make df reactive
df_current <- reactiveVal(df)
observeEvent(input$button, {
req(df_current())
## update df by adding comments
df_new <- df_current()
df_new[df_current()$id %in% input$selectID, "Comment"] <- input$comment
df_current(df_new)
})
output$data <- DT::renderDataTable({
req(df_current())
DT::datatable(df_current(),
options = list(orderClasses = TRUE,
lengthMenu = c(5, 10, 20), pageLength = 5))
})
}
I'm building a R Shiny app with a dynamic datatable, using the DT package. Users are able to select two columns within a data.frame that contains more columns.
When users select a column, the datatable is updated and all filters/sorting are reset to default within the datatable object. How can I let the application remember filters and sorting when the given column is not replaced by the user?
Minimal working example below:
library(shiny)
library(DT)
library(data.table)
server <- function(input, output) {
df <- data.frame(
name = rep('a',20),
dimA = 1:20,
dimB = 21:40,
dimC = 41:60
)
observe({
columns <- c('name', input$dim1ID, input$dim2ID)
dfDt <- df[names(df) %in% columns]
output$dtDataTable = DT::renderDataTable(
server = FALSE,
expr = datatable(
dfDt,
filter = 'top',
rownames = FALSE,
selection = 'none',
options = list(sDom = '<"top">rt<"bottom">ip')
)
)
})
}
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
## Dimension 1
selectInput(
inputId = "dim1ID",
label = "Dimensie 1",
choices = c('dimA', 'dimB', 'dimC'),
selected = 'dimA'
),
## Dimension 2
selectInput(
inputId = "dim2ID",
label = "Dimensie 2",
choices = c('dimA', 'dimB', 'dimC'),
selected = 'dimB'
)
),
mainPanel(DT::dataTableOutput('dtDataTable'))
)
)
shinyApp(ui = ui, server = server)
This can be done using the DataTables Information, in particular the "state" information (input$tableId_state) which contains the order information of the current table, and input$tableId_search_columns which contains the filtering information by columns. If the columns are fixed (ie in the example above "Dimensie 1" and "Dimensie 2" would always be at the same place), it is much simpler to "remember" which one was ordered (unlike the original example where they are alphabetically reordered when the table is created). For instance based on the above example, the following will work if you sort the "A" column and change the right column from "B" to "C" and back:
library(shiny)
library(DT)
library(data.table)
server <- function(input, output) {
df <- data.frame(
name = rep('a',20),
dimA = 1:20,
dimB = 21:40,
dimC = 41:60
)
values <- reactiveValues(
prevDim1 = "",
prevDim2 = "",
options = list(sDom = '<"top">rt<"bottom">ip',
stateSave = TRUE,
order = list())
)
observeEvent(input$dtDataTable_state$order, {
values$options$order <- input$dtDataTable_state$order
})
observeEvent({
input$dim1ID
input$dim2ID
},{
columns <- c('name', input$dim1ID, input$dim2ID)
dfDt <- df[names(df) %in% columns]
if(length(values$options$order) != 0 && ((values$prevDim1 != input$dim1ID && values$options$order[[1]][[1]] == 1) | (values$prevDim2 != input$dim2ID && values$options$order[[1]][[1]] == 2)) ){
values$options$order = list()
}
values$prevDim1 <- input$dim1ID
values$prevDim2 <- input$dim2ID
output$dtDataTable = DT::renderDataTable(
server = FALSE,
expr = datatable(
dfDt,
filter = 'top',
rownames = FALSE,
selection = 'none',
options = values$options
)
)
})
}
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
## Dimension 1
selectInput(
inputId = "dim1ID",
label = "Dimensie 1",
choices = c('dimA', 'dimB', 'dimC'),
selected = 'dimA'
),
## Dimension 2
selectInput(
inputId = "dim2ID",
label = "Dimensie 2",
choices = c('dimA', 'dimB', 'dimC'),
selected = 'dimB'
)
),
mainPanel(DT::dataTableOutput('dtDataTable'))
)
)
shinyApp(ui = ui, server = server)
I am trying to create a shiny-app that load data-set, present the variable list and their classes and allow the user to modify the class of a selected variable. All the functions in the following code are working except to the last function in the server- observeEvent which not working when trying to modify the variable class. Any suggestions?
Thank you in advance,
Rami
`
rm(list = ls())
library(shiny)
library(shinydashboard)
library(DT)
ui <- dashboardPage(
dashboardHeader(title = "Shiny Example"),
#--------------------------------------------------------------------
dashboardSidebar(
sidebarMenu(
menuItem("Data", tabName = "data", icon = icon("th"))
)
),
#--------------------------------------------------------------------
dashboardBody(
#--------------------------------------------------------------------
tabItem(tabName = "data",
fluidPage(
fluidRow(
box(
selectInput('dataset', 'Select Dataset', list(GermanCredit = "GermanCredit",
cars = "cars",
iris = "iris")),
title = "Datasets",width = 4, status = "primary",
checkboxInput("select_all", "Select All Variable", value = TRUE),
conditionalPanel(condition = "input.select_all == false",
uiOutput("show.var"))
),
box(
title = "Variable Summary", width = 4, status = "primary",
DT::dataTableOutput('summary.data')
),
box(
title = "Modify the Variable Class", width = 4, status = "primary",
radioButtons("choose_class", label = "Modify the Variable Class",
choices = list(Numeric = "numeric", Factor = "factor",
Character = "character"),
selected = "numeric"),
actionButton("var_modify", "Modify")
)
)
)
)
)
)
#--------------------------------------------------------------------
# Server Function
#--------------------------------------------------------------------
server <- function(input, output,session) {
#--------------------------------------------------------------------
# loading the data
get.df <- reactive({
if(input$dataset == "GermanCredit"){
data("GermanCredit")
GermanCredit
}else if(input$dataset == "cars"){
data(cars)
cars
}else if(input$dataset == "iris"){
data("iris")
iris
}
})
# Getting the list of variable from the loaded dataset
var_list <- reactive(names(get.df()))
# Choosing the variable - checkbox option
output$show.var <- renderUI({
checkboxGroupInput('show_var', 'Select Variables', var_list(), selected = var_list())
})
# Setting the data frame based on the variable selction
df <- reactive({
if(input$select_all){
df <- get.df()
} else if(!input$select_all){
df <- get.df()[, input$show_var, drop = FALSE]
}
return(df)
})
# create list of variables
col.name <- reactive({
d <- data.frame(names(df()), sapply(df(),class))
names(d) <- c("Name", "Class")
return(d)
})
# render the variable list into table
output$summary.data <- DT::renderDataTable(col.name(), server = FALSE, rownames = FALSE,
selection = list(selected = 1, mode = 'single'),
options = list(lengthMenu = c(5, 10, 15, 20), pageLength = 20, dom = 'p'))
# storing the selected variable from the variables list table
table.sel <- reactive({
df()[,which(colnames(df()) == col.name()[input$summary.data_rows_selected,1])]
})
# Trying to modify the variable class
observeEvent(input$var_modify,{
modify.row <- which(colnames(df()) == col.name()[input$summary.data_rows_selected,1])
if( input$choose_class == "numeric"){
df()[, modify.row] <- as.numeric(df()[, modify.row])
} else if( input$choose_class == "factor"){
df()[, modify.row] <- as.factor(df()[, modify.row])
} else if( input$choose_class == "character"){
df()[, modify.row] <- as.character(df()[, modify.row])
}
})
}
shinyApp(ui = ui, server = server)
`
I would use reactiveValues() instead.
library(shiny)
# Define UI for application that draws a histogram
ui <- shinyUI(fluidPage(
sidebarLayout(
sidebarPanel(
selectInput("classType", "Class Type:", c("as.numeric", "as.character"))
),
mainPanel(
textOutput("class")
)
)
))
server <- shinyServer(function(input, output) {
global <- reactiveValues(sample = 1:9)
observe({
global$sample <- get(input$classType)(global$sample)
})
output$class <- renderText({
print(class(global$sample))
})
})
shinyApp(ui = ui, server = server)
In case you are interested:
Concerning your attempt: reactive() is a function and you called the output of the function by df()[, modify.row]. So in your code you try to change the output of the function, but that does not change the output of futures calls of that function.
Maybe it is easier to see in a simplified version:
mean(1:3) <- 1
The code can not change the mean function to output 1 in future. So thats what reactiveValues() help with :). Hope that helps!