Saving editable DT table values to reactivevalue() in Shiny

Hello,

I have been working on having editable DT tables in my shiny app and I have been making use of the following code to achieve that.

I want to be able to pass the table that gets edited as a final dataframe to a reactivevalues or some other object that I can then finally manipulate and use. I am not entirely sure how to do it as assigning the callModule function to an object does not actually give me a new object with which to work. Any help would be appreciated!


### Libraries
library(shiny)
library(dplyr)
library(DT)

### Data
input_data <- data.frame(Brand = c("Brand1", "Brand2","Brand3"),
                         ratio = c (.5, .5, .5),
                         cost = c(2000, 3000, 4000),
                         stringsAsFactors = FALSE) %>% 
  mutate(updated_price = cost * ratio)




### Module
modFunction <- function(input, output, session, data,reset) {
  
  v <- reactiveValues(data = data)
  
  proxy = dataTableProxy("mod_table")
  
  observeEvent(input$mod_table_cell_edit, {
    print(names(v$data))
    info = input$mod_table_cell_edit
    str(info)
    i = info$row
    j = info$col
    k = info$value
    str(info)
    
    isolate(
      if (j %in% match(c("ratio","cost","updated_price"), names(v$data))) {
        print(match(c("ratio","cost", "updated_price"), names(v$data)))
        v$data[i, j] <<- DT::coerceValue(k, v$data[i, j])
        print(v$data)
        
        if (j %in% match("cost", names(v$data))) {
          v$data$updated_price <<- v$data$cost * v$data$ratio
        }
        if (j %in% match("ratio", names(v$data))) {
          v$data$updated_price <<- v$data$cost * v$data$ratio
        }
      } else {
        stop("You are not supposed to change this column.") # check to stop the user from editing only few columns
      }
    )
    replaceData(proxy, v$data, resetPaging = FALSE)  # replaces data displayed by the updated table
  })
  
  ### Reset Table
  observeEvent(reset(), {
    v$data <- data # your default data
  })
  
  print(isolate(colnames(v$data)))
  output$mod_table <- DT::renderDataTable({
    DT::datatable(v$data, editable = TRUE)
    
  })
}

modFunctionUI <- function(id) {
  ns <- NS(id)
  DT::dataTableOutput(ns("mod_table"))
  
}

### Shiny App
shinyApp(
  ui = basicPage(
    mainPanel(
      
      actionButton("reset", "Reset"),
      tags$hr(),
      modFunctionUI("editable")
    )
  ),
  server = function(input, output) {
    demodata<-input_data
    callModule(modFunction,"editable", demodata,
               reset = reactive(input$reset))
    
  }
)

Hi @GreyMerchant. I can't get what's your problem. But I guess you want to return variable from module back to the main server function. If yes, just return the reactiveValues and assign it the a variable in main server function as follow.

### Libraries
library(shiny)
library(dplyr)
library(DT)

### Data
input_data <- data.frame(Brand = c("Brand1", "Brand2","Brand3"),
                         ratio = c (.5, .5, .5),
                         cost = c(2000, 3000, 4000),
                         stringsAsFactors = FALSE) %>% 
  mutate(updated_price = cost * ratio)




### Module
modFunction <- function(input, output, session, data,reset) {
  
  v <- reactiveValues(data = data)
  
  proxy = dataTableProxy("mod_table")
  
  observeEvent(input$mod_table_cell_edit, {
    print(names(v$data))
    info = input$mod_table_cell_edit
    str(info)
    i = info$row
    j = info$col
    k = info$value
    str(info)
    
    isolate(
      if (j %in% match(c("ratio","cost","updated_price"), names(v$data))) {
        print(match(c("ratio","cost", "updated_price"), names(v$data)))
        v$data[i, j] <<- DT::coerceValue(k, v$data[i, j])
        print(v$data)
        
        if (j %in% match("cost", names(v$data))) {
          v$data$updated_price <<- v$data$cost * v$data$ratio
        }
        if (j %in% match("ratio", names(v$data))) {
          v$data$updated_price <<- v$data$cost * v$data$ratio
        }
      } else {
        stop("You are not supposed to change this column.") # check to stop the user from editing only few columns
      }
    )
    replaceData(proxy, v$data, resetPaging = FALSE)  # replaces data displayed by the updated table
  })
  
  ### Reset Table
  observeEvent(reset(), {
    v$data <- data # your default data
  })
  
  print(isolate(colnames(v$data)))
  output$mod_table <- DT::renderDataTable({
    DT::datatable(v$data, editable = TRUE)
    
  })
  
  return(v)
}

modFunctionUI <- function(id) {
  ns <- NS(id)
  DT::dataTableOutput(ns("mod_table"))
  
}

### Shiny App
shinyApp(
  ui = basicPage(
    mainPanel(
      
      actionButton("reset", "Reset"),
      tags$hr(),
      modFunctionUI("editable")
    )
  ),
  server = function(input, output) {
    demodata<-input_data
    edited <- callModule(modFunction,"editable", demodata,
               reset = reactive(input$reset))
    observe(print(edited$data))
  }
)

Thanks for the reply. This is not doing exactly what I want. Essentially, I would like to be able to save the edited$data to a new object but through reactiveValues() so I can use that as a new input to makes changes to on the server side before providing the final output.

when I try data_df_final <- reactiveValues({edited$data}) I just get an error which says: "Error in tag("div", list(...)) : argument is missing, with no default." I have tried to do it with the other function calls you used as well but no luck.

Does it make more sense what I am trying to accomplish?

@GreyMerchant. I still can't get your question. Your code data_df_final <- reactiveValues({edited$data}) is not work because reactive value edited must be used within observer. I change the code like this and it can assign the value to the data_df_final.

### Libraries
library(shiny)
library(dplyr)
library(DT)

### Data
input_data <- data.frame(Brand = c("Brand1", "Brand2","Brand3"),
                         ratio = c (.5, .5, .5),
                         cost = c(2000, 3000, 4000),
                         stringsAsFactors = FALSE) %>% 
  mutate(updated_price = cost * ratio)




### Module
modFunction <- function(input, output, session, data,reset) {
  
  v <- reactiveValues(data = data)
  
  proxy = dataTableProxy("mod_table")
  
  observeEvent(input$mod_table_cell_edit, {
    print(names(v$data))
    info = input$mod_table_cell_edit
    str(info)
    i = info$row
    j = info$col
    k = info$value
    str(info)
    
    isolate(
      if (j %in% match(c("ratio","cost","updated_price"), names(v$data))) {
        print(match(c("ratio","cost", "updated_price"), names(v$data)))
        v$data[i, j] <<- DT::coerceValue(k, v$data[i, j])
        print(v$data)
        
        if (j %in% match("cost", names(v$data))) {
          v$data$updated_price <<- v$data$cost * v$data$ratio
        }
        if (j %in% match("ratio", names(v$data))) {
          v$data$updated_price <<- v$data$cost * v$data$ratio
        }
      } else {
        stop("You are not supposed to change this column.") # check to stop the user from editing only few columns
      }
    )
    replaceData(proxy, v$data, resetPaging = FALSE)  # replaces data displayed by the updated table
  })
  
  ### Reset Table
  observeEvent(reset(), {
    v$data <- data # your default data
  })
  
  print(isolate(colnames(v$data)))
  output$mod_table <- DT::renderDataTable({
    DT::datatable(v$data, editable = TRUE)
    
  })
  
  return(v)
}

modFunctionUI <- function(id) {
  ns <- NS(id)
  DT::dataTableOutput(ns("mod_table"))
  
}

### Shiny App
shinyApp(
  ui = basicPage(
    mainPanel(
      
      actionButton("reset", "Reset"),
      tags$hr(),
      modFunctionUI("editable")
    )
  ),
  server = function(input, output) {
    demodata<-input_data
    edited <- callModule(modFunction,"editable", demodata,
                         reset = reactive(input$reset))
    data_df_final <- reactiveValues()
    observe(
      {data_df_final$data <- edited$data}
    )
    observe(print(data_df_final$data))
  }
)

1 Like

Apologies that my question was not as clear.

This is doing what I wanted it to do - thanks so much! I thought there would have been an easier way to work with data_df_final$data instead of having to keep it in this format.

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