I want to incorporate a dateRangeInput() in my ui, for the user to select a range and the graph will filter accordingly. However, when I run this line, I get an error message.

data_filtered <- eventReactive(input$run_button,{
    filter(data_input_long(), Tag %in% input$y_axis & y >= input$date[1] & y <= input$date[2])

If I remove the input$date conditions, the graph will work fine, but I am not sure what is wrong with the conditions, since it is how other previous answers is written. The data I am using is below:

My full code is here:

library(shiny)#load and attach package shiny
library(shinythemes)
library(data.table)
library(ggplot2)
library(tidyverse)
library(DateTimeRangePicker)
library(tibbletime)
library(shinyTime)
library(DT)
library(plotly)
library(RColorBrewer)

not_sel <- "Not selected"

main_page <- tabPanel(#create a tab panel for main_page
  title = "Data Plotter",#main_page tab titled Plot
  titlePanel("Data Plotter"),#panel titled Plot
  sidebarLayout( #create a layout with a sidebar and main area
    sidebarPanel(#side panel = inputs
      title = "Inputs",
      fileInput("csv_input","Select CSV File",accept = ".csv"),#first parameter is ID to call in server, text that appears, condition to accept
      selectInput("x_axis","Select x-axis",choices = c(not_sel)),#creates input in Inputs
      selectInput("y_axis","Select y-axis",choices = c(not_sel), selected = not_sel, multiple = TRUE),
      dateRangeInput("date_range", "Input Range"),
      actionButton("run_button","Apply Changes",icon = icon("play")), #adds play icon
    ),
    mainPanel(#main panel are outputs
      tabsetPanel(#can divide output into separate viewable screens
        tabPanel(#first screen called Plot
          title = "Plot",
          plotlyOutput("plot_1"), #make Plot screen output image
          br(), br(), br(),
          DT::dataTableOutput(outputId = "table_1")
        )
      )
    )
  )
)
about_page <- tabPanel(
  title = "About",
  titlePanel("About"),#create a panel containing an application title
  "Created by NC",
  br(),#new line
  "June 2024"
)

ui <- navbarPage(#create a page with a top level navigation bar
  title = "Data Plotter",
  theme = shinytheme('sandstone'),
  main_page,
  about_page
)

server <- function(input, output){
  options(shiny.maxRequestSize=100*1024^2)
  
  data_input <- reactive({ #wraps following expression as reactive, meaning result changes over time
    req(input$csv_input)#req ensures there is csv input, otherwise does not run
    dt <- fread(input$csv_input$datapath, na.strings = c("NULL",""))#fast reads input$csv$data path, which is file pathway
    dt[is.na(dt)] <- 0
    dt
  })
  
  data_input_long <- reactive({
    pivot_longer(setDF(data_input()), cols = -c(y,sec), names_to = "Tag", values_to = "Values")
  })
  
  data_filtered <- eventReactive(input$run_button,{
    filter(data_input_long(), Tag %in% input$y_axis & y >= input$date[1] & y <= input$date[2])
  })
  
  observeEvent(data_input(),{#wraps code and allows it to run when specific reactive expression changes
    choices <- c(not_sel,names(data_input()))#create variable "choices", with not_sel at top and the names of data table next
    updateSelectInput(inputId = "x_axis", choices = choices)#updates the selectinput, which in turn changes the choices
    updateSelectInput(inputId = "y_axis", choices = choices)
  })
  
  output$plot_1 <- renderPlotly({
    ggplotly(ggplot(data_filtered(), aes(x = .data[[input$x_axis]], y = Values, color = Tag))+
      geom_point()
    )
  }) #assigns renderPlot to output, renders graph for plot_1
  
  output$table_1 <- DT::renderDataTable({
    data_filtered()
  })
}

shinyApp(ui = ui, server = server)#creates Shiny application, user interface is layout of app, server is connection between input and output