auto populate the textInput based on the variable , value and condition selected from the dropdown

[jkatam]

I am trying to create a simple app where i would like to auto populate the textinput based on the variable, values and condition selected from the dropdown

for suppose if i want to filter the data based on mpg < 10.4 then i would like to select them from the variable, values and condition option and then auto populate the mpg < 10.4 in the filter option and then when i click the load this filter should subset the data

also this filter should auto populate the values as i continue to select another condition like mpg <= 10.4 & cyl==8

could you please let me know your thoughts on the same, here is the code

library(shiny)
library(DT)
library(haven)
library(shinythemes)
library(DataExplorer)
library(labelled)
library(tidyverse)
# Define UI for application that draws a histogram
ui <- fluidPage(theme = shinytheme("spacelab"),
                
                # Application title
                titlePanel("DataView App"),
                
                # Show a plot of the generated distribution
                sidebarLayout(
                  sidebarPanel(
                    # Sidebar with a slider input for number of bins 
                    fileInput("data",
                              "Upload the Data"),
                    
                    textInput('tdata', 'Filter', value = NULL),
                    varSelectInput("variables1", "Choose the Variable to subset", NULL, selected = NULL, multiple = FALSE),
                    selectInput('var1','Select Values:',choices = '', selected = NULL, multiple = TRUE),
                    selectInput('cond1','Coondition:',choices = c('%in%','<','>','<=','>=','!=','&'), selected = NULL, multiple = FALSE),
                    varSelectInput("variables", "Variables to View:", NULL, multiple = TRUE),
                    actionButton("load","Load"),
                    h5(''),
                    verbatimTextOutput("input_dict")
                  ), #sidebarPanel
                  
                  mainPanel(
                    tabsetPanel(id='dataset',
                                tabPanel('Basics',verbatimTextOutput("input_intro")),
                                tabPanel('Dataset',DTOutput("input_file")),
                                tabPanel('Summary',verbatimTextOutput("input_sum"))
                    ) #tabsetPanel
                  ) #mainPanel
                  
                ) #sidebarpanel    
)

# Define server logic required to draw a histogram
server <- function(input, output, session) {
  
  
  
  sampled <- reactive({
 mtcars
  })
  
  
  observeEvent(input$variables1, {
    updateSelectInput(session,inputId = "var1", 'Select Values:', choices = levels(as.factor(sampled()[[input$variables1]])),selected = NULL)
    
  })
  
  sampled2 <- reactive({
    # req(input$variables1, input$var1)
    if(input$variables1!='' & length(input$var1)>0){
      sampled() %>% filter(CESEQ %in% input$var1)
    } else if (input$variables1!='' & length(input$var1)==0){
      sampled()
    }
  })
  
  
  observe({
    req(sampled())
    updateVarSelectInput(session, "variables", "Variables to View:", sampled())
    updateVarSelectInput(session, "variables1", "Choose the Variable to subset", sampled())
  })
  
  
  
  nsampled <- reactive({
    # tdata2 <- unique(input$tdata)
    # input$saveFilterButton
    expre <- parse(text = input$tdata)
    if(input$tdata != ''){
      if (length(input$variables)==0) {
        sampled() %>% 
          filter(eval(expre)) 
      } else{
        sampled() %>% 
          filter(eval(expre)) %>% dplyr::select(!!!input$variables)
      }
    } else {
      if (length(input$variables)==0) {
        sampled() 
      } else {
        sampled() %>% dplyr::select(!!!input$variables)
      }
    }
  }) %>%  
    bindEvent(input$load)
  
  
  output$input_file <- renderDataTable({
    # tdata2 <- unique(input$tdata)
    # input$saveFilterButton
    expre <- parse(text = input$tdata)
    if(input$tdata != ''){
      if (length(input$variables)==0) {
        sampled() %>% 
          filter(eval(expre)) 
      } else{
        sampled() %>% 
          filter(eval(expre)) %>% dplyr::select(!!!input$variables)
      }
    } else {
      if (length(input$variables)==0) {
        sampled2() 
      } else {
        sampled() %>% dplyr::select(!!!input$variables)
      }
    }
  }) %>%  
    bindEvent(input$load)
  
  output$input_sum <- renderPrint({
    Hmisc::describe(nsampled())
  }) %>%  
    bindEvent(input$load)  
  
  output$input_dict <- renderPrint({
    labelled::generate_dictionary(nsampled()) %>% dplyr::select(variable, label, col_type)
  }) %>%  
    bindEvent(input$load)   
  
  
  output$input_intro <- renderPrint({
    nsampled2 <- DataExplorer::introduce(nsampled())
    nsampled3 <- nsampled2 %>% pivot_longer(everything(), names_to = 'name3', values_to = 'Value') %>% 
      mutate(name2=stringr::str_to_sentence(name3), Name=stringr::str_replace_all(name2,'\\_',' ')) %>%
      slice_head(n=5) %>% dplyr::select(Name, Value)
    nsampled3
  }) %>%  
    bindEvent(input$load)  
  
}

# Run the application 
shinyApp(ui = ui, server = server)

[nirgrahamuk]

sending a value to the filter text box is as simple as an updateTextInput ... you would just be pasting together the elements that you have. I suppose applying the filter to the data based on the filter text is what your are probably stuck with. consider this example

library(tidyverse)
input <- list()
input$varname <- "mpg"
input$value <- "10.5"
input$cond <- "<"

(together_string <- paste0(input$varname,
                          input$cond,
                          input$value))
together_expr <- parse(text=together_string)

filter(mtcars,
      eval(together_expr))