I have a shiny app with multiple tabs where I need to upload a data from a .xlsx file. After the file is uploaded, "n" number of tabs are displayed depending on the number of worksheets (n) in excel. In each tab, you can plot the x value and multiple y values depending on the worksheet you select Here is the sample app and the sample excel data (save_state_data.xlsx) to upload .xlsx

I opened the app in a browser, plotted the graphs and saved as complete html webpage, it still does not render the state properly. What is the best way to do it? Maybe bookmarks - but I am not sure how to use them for multi tabs and an excel file upload

Create a function for a stacked plot

plotly_stacked <- function(df, x_colName, cols){
      
      DF <- df[, cols] %>%
        tidyr::gather(variable, value, -x_colName ) %>%
        transform(id = as.integer(factor(variable)))
    
      DF$variable<- factor( DF$variable, levels = unique( DF$variable))
      
      p <- plot_ly(data = DF, x = ~get(names(DF[1])) , y = ~value, color = ~variable, colors = "Dark2",
                   yaxis = ~paste0( "y",sort(id, decreasing = F))) %>%
        
        add_lines() %>%
        layout(
         xaxis = list(
           title = ""), 
          legend = list(
                  orientation = "h",   
                  xanchor = "center",  
                  x = 0.5)) %>%
        plotly::subplot(nrows = length(unique(DF$variable)), shareX = TRUE)
      
      return(p)
    }

app.R

# Set maximum request size
options(shiny.maxRequestSize = 30 * 1024^2)

# Load required libraries
library(DT)
library(plotly)
library(shiny)
library(data.table)
library(readr)
library(openxlsx)
library(readxl)
library(tidyverse)
library(corrplot)
library(corrr)
library(psych)

# UI ------------------------------------------------------------
ui <- fluidPage(
  titlePanel(title = "Data"),
  fileInput("file", "Choose .xlsx file", accept = c(".xlsx")),
  mainPanel(
    tabsetPanel(id = "tabsetPanelID")
  )
)

# Server ------------------------------------------------------------
server <- function(input, output, session) {
  
  # UI Elements ------------------------------------------------------------
  ui_elementsUI <- function(x, y, data) {
    tagList(
      h4("Select X and Y datasets"),
      fluidRow(
        column(12, selectizeInput(inputId = x, label = "X data", choices = names(data)))
      ),
      fluidRow(
        column(12, selectizeInput(inputId = y, label = "Y data", choices = names(data), multiple = TRUE, selected = names(data)[3]))
      )
    )
  }

  # Sheet Elements ------------------------------------------------------------
  sheet_elementsUI <- function(sheet) {
    tagList(
      fluidRow(
        column(12, selectInput(inputId = sheet, label = "Sheet", choices = excel_sheets(input$file$datapath)))
      )
    )
  }

  # Render Sheet Elements after File Upload ------------------------------------
  n <- reactive({
    req(input$file)
    length(excel_sheets(input$file$datapath))
  })

  observe({
    lapply(1:n(), function(val) {
      output[[paste0("sheet_elements", val)]] <- renderUI({
        sheet_elementsUI(paste0("sheet", val))
      })

      output[[paste0("ui_elements", val)]] <- renderUI({
        ui_elementsUI(paste0("x", val), paste0("y", val), data_list()[[val]]())
      })

      output[[paste0("plot", val)]] <- renderPlotly({
        plot_render()(paste0("x", val), paste0("y", val), data_list()[[val]]())
      })
    })
  })

  # Plot Rendering ------------------------------------------------------------
  plot_render <- reactive({
    validate(
      need(input$file != "", "Plots will display after choosing the .xlsx file.")
    )
    function(x, y, data) {
      labels <- c("xy", paste0("xy", 2:length(input[[y]])))
      labels_json <- jsonlite::toJSON(labels)

      js_code <- sprintf(
        'function(el, x){el.on("plotly_hover", function(d) {
            Plotly.Fx.hover(el.id, {xval: d.xvals[0]}, %s);
          })}',
        labels_json
      )

      plotly_stacked(df = data, x_colName = input[[x]], cols = c(input[[x]], input[[y]])) %>%
        layout(hovermode = "x") %>%
        htmlwidgets::onRender(js_code)
    }
  })

  # Data Processing Function ---------------------------------------------------
  foo <- function(sheet) {
    df <- read_xlsx(input$file$datapath, sheet = input[[sheet]], na = "empty")
    n <- which(!is.na(as.numeric(df[[1]])))[1]
    df[is.na(df)] <- " "
    colnames(df) <- apply(df[1:(n - 1), ], 2, paste, collapse = ",")
    df <- df[-c(1:(n - 1)), ]
    names(df)[1] <- "Time"
    df[, 2:ncol(df)] <- apply(df[, 2:ncol(df)], 2, as.numeric)
    
    if (class(df[[1]])[1] != "POSIXct") {
      df$Time <- as.POSIXct(as.numeric(df$Time) * 86400, origin = "1899-12-30", tz = "UTC")
    }
    
    return(df)
  }

  # Generate Reactive Datasets -------------------------------------------------
  generate_data <- function(sheet_name) {
    reactive({
      req(input$file)
      foo(sheet_name)
    })
  }

  data_list <- reactive({
    lapply(paste0("sheet", 1:n()), generate_data)
  })

  # Generate Tabs --------------------------------------------------------------
  generateTabUI <- function(tab_id) {
    tab_name <- paste("Tab", tab_id)
    plot_output <- plotlyOutput(paste("plot", tab_id, sep = ""))
    ui_elements <- uiOutput(paste("ui_elements", tab_id, sep = ""))
    sheet_elements <- uiOutput(paste("sheet_elements", tab_id, sep = ""))

    tabPanel(tab_name, value = tab_id, sheet_elements, ui_elements, plot_output)
  }

  observe({
    for (i in 1:n()) {
      insertTab(
        inputId = "tabsetPanelID",
        tab = generateTabUI(i)
      )
    }
  })
}

# Run the Shiny App -----------------------------------------------------------
shinyApp(ui = ui, server = server)