Using reactive data to form data frame in shiny.

I want to write an app and input different csv file when using the app in different time. There should be many row inside my file and I want to select specific row for comparison, eg to get the mean, standard deviation of row. I name the row as 'Numerical Variable' in the code. I want to put the specific row in to a data frame for comparison. However, when I run the code, error message 'Warning: Error in as.data.frame.default: cannot coerce class ‘c("reactive.event", "reactiveExpr", "reactive", "function")’ to a data.frame' would be seen.

library(shiny)
library(data.table)
library(dplyr)
library(matrixStats)

# Define UI for application that draws a histogram


not_sel <- 'Not Selected'

main_page <- tabPanel(
  title = 'Analysis',
  titlePanel('Analysis'),
  sidebarLayout(
    sidebarPanel(
      title = 'Inputs',
      fileInput("csv_input","Select CSV File to Import",accept=".csv"),
      selectInput("num_var_1","Numerical Variable 1",choices=not_sel),
      selectInput('num_var_2','Numerical Variable 2',choices = not_sel),
      selectInput('num_var_3','Numerical Variable 3',choices = not_sel),
      actionButton("run_button","Run Analysis",icon=icon("play"))
    ),
    mainPanel(
      tabsetPanel(
        tabPanel(
          title = 'Statistics',
          fluidRow(
            column(width = 4, strong(textOutput('combine_data')))
          ),
          fluidRow(
            column(width = 4, tableOutput('combine_data_table'))
          ),
          fluidRow(
            column(width = 4, strong(textOutput('list_of_outlier_combine')))
          )
        )
      )
    )
  )
)

ui <- navbarPage(
  
  title = 'Data Analyser',
  main_page
  
  
)


# Define server logic required to draw a histogram
server <- function(input, output){
  output$book <- renderText(input$title)
  data_input <- reactive({
    req(input$csv_input)
    fread(input$csv_input$datapath)
  })
  observeEvent(data_input(),{
    choices <- c(not_sel, names(data_input()))
    updateSelectInput(inputId = 'num_var_1', choices = choices)
    updateSelectInput(inputId = 'num_var_2',choices = choices)
    updateSelectInput(inputId = 'num_var_3',choices = choices)
  })
  num_var_1 <- eventReactive(input$run_button,input$num_var_1)
  num_var_2 <- eventReactive(input$run_button,input$num_var_2)
  num_var_3 <- eventReactive(input$run_button,input$num_var_3)

  create_num_var_table <- function(data_input,num_var){
    if(num_var != not_sel){
      col <- data_input[,get(num_var)]
      if(length(col)>5000) col_norm<-sample(col,5000) else col_norm<-col
      statistic <- c('mean','median','standard deviation' )
      df <- as.data.frame(
        isolate(num_var_1),isolate(num_var_2),isolate(num_var_3)
        )
      mean = rowMeans(df)
      std=rowSds(df)
      Tmin=round(mean-3*std)
      Tmax=round(mean+3*std)
      
      value <- c(mean,std)
      
      data.table(statistic,value)
    }
  }
  output$combine_data <- renderText('Combine Data Table')
  combine_data_table <- eventReactive(input$run_button,{
    create_num_var_table(data_input(), num_var_1())
  })
  output$combine_data_table <-
    renderTable(combine_data_table(),colnames = FALSE)
  
  create_list_of_outlier <- function(data_input,num_var){
    if(num_var != not_sel){
      outlier <- data_input[,get(num_var)]
      outlier[which(outlier<Tmin | outlier>Tmax)]
    }
  }
  list_of_outlier <- eventReactive(input$run_button,{
    create_list_of_outlier(data_input(),num_var_1())
  })
  output$list_of_outlier <-
    renderText(paste('List of Outlier(s):',list_of_outlier()))
}

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