I have a shiny app pulling data from a gsheet and displaying it in graphs inside individual tabs. The app works but:

• the code inside the server section repeats itself too much => i was looking for suggestions to optimize it: could i use a loop to avoid all the renderPlotly repetitions? Perhaps the ui section could use some optimization too to organize the different tabs
• it takes too long to load (about 50 secs), maybe because of the above or maybe because it retrieves too much information from the gsheet (11k rows) => any idea why? how could i improve this?

Here is the code, any help is appreciated:

# EIA

#library(httr)
#library(jsonlite)
library(dplyr)
#library(data.table)
library(googlesheets4)
#library(zoo)
library(shiny)
library(ggplot2)
library(shinyWidgets)
library(shinydashboard) # colours info here: https://www.w3schools.com/colors/colors_hex.asp
library(lubridate)
library(hrbrthemes)
library(ggthemes)
library(plotly)
#library(ggrepel)
library(tidyverse)
library(gargle)

gs4_auth(cache = ".secrets", email = "xxxxxxxxxxxx@gmail.com")

df_petroleum_lease <- read_sheet("https://docs.google.com/spreadsheets/d/1PUdqrOx__J34-sRYoHKcqI3H8iEjdMCFcVTOX0fqgPQ/edit#gid=0",
                                 sheet = 'crude_condensate') |>
  select(response.data.period, response.data.countryRegionId,response.data.countryRegionName, response.data.value, movmean)

colnames(df_petroleum_lease) <- c('month', 'countryId', 'countryName', 'volume', 'movmean')

df_petroleum_lease <- df_petroleum_lease |>
  mutate(month = as.Date(as.yearmon(month)))

shale_oil_us <- read_sheet("https://docs.google.com/spreadsheets/d/1PUdqrOx__J34-sRYoHKcqI3H8iEjdMCFcVTOX0fqgPQ/edit#gid=0",
                           sheet = 'us_shale_oil_plays') |>
  pivot_longer(-Date, names_to = "Region", values_to = "production_kbpd") |>
  mutate(production_kbpd = round(production_kbpd, 0),
         Date = as.Date(as.yearmon(Date)))

# Define UI
ui <- fluidPage(
  
  # Application title & background colors
  titlePanel("EIA crude oil + condensate stats top 20 producers - kb/d"),
  setBackgroundColor("Whitesmoke"),
  
  # Sidebar with a date range 
  sidebarLayout(
    sidebarPanel(
      dateRangeInput("dates",
                     label = h4("Date range",br(),"(pick 1st day of month)"),
                     format = "yyyy-mm",
                     start = '1973-01-01',
                     end = Sys.Date() %m-% months(4)),
      HTML(paste(tags$div(tags$a(href = "https://www.eia.gov/opendata/", 'Source country data')),"
")),
      HTML(paste(tags$div(tags$a(href = "https://www.eia.gov/energyexplained/oil-and-petroleum-products/data/US-tight-oil-production.xlsx",'Source US Shale')),"
")),
      fluidRow(column(6,downloadButton('downloadData', 'Download crude oil data')),column(6,downloadButton('downloadData2', 'Download US Shale data')))
    ),
    
    # Show plots in different tabs
    mainPanel(
      tabsetPanel(type = "tabs",
                  tabPanel(p(code("WORLD")),plotlyOutput("WorldOil", height = 575)),
                  tabPanel("USA",
                           br(), 
                           tabsetPanel(type = "tabs",
                                       tabPanel("USA total",plotlyOutput("USAOil", height = 575)),
                                       tabPanel(p(code("Focus on US Shale")), plotlyOutput("USAOilShale", height = 575)))),
                  tabPanel("Saudi Arabia", plotlyOutput("SAOil", height = 575)),
                  tabPanel("Russia", plotlyOutput("RussiaOil", height = 575)),
                  tabPanel("Irak", plotlyOutput("IrakOil", height = 575)),
                  tabPanel("Iran", plotlyOutput("IranOil", height = 575)),
                  tabPanel("China", plotlyOutput("ChinaOil", height = 575)),
                  tabPanel("Canada", plotlyOutput("CanadaOil", height = 575)),
                  tabPanel("UAE", plotlyOutput("UAEOil", height = 575)),
                  tabPanel("Kuwait", plotlyOutput("KuwaitOil", height = 575)),
                  tabPanel("Brazil", plotlyOutput("BrazilOil", height = 575)),
                  tabPanel("Colombia", plotlyOutput("ColombiaOil", height = 575)),
                  tabPanel("Mexico", plotlyOutput("MexicoOil", height = 575)),
                  tabPanel("Nigeria", plotlyOutput("NigeriaOil", height = 575)),
                  tabPanel("Angola", plotlyOutput("AngolaOil", height = 575)),
                  tabPanel("Norway", plotlyOutput("NorwayOil", height = 575)),
                  tabPanel("Kazakhstan", plotlyOutput("KazakhstanOil", height = 575)),
                  tabPanel("Qatar", plotlyOutput("QatarOil", height = 575)),
                  tabPanel("Algeria", plotlyOutput("AlgeriaOil", height = 575)),
                  tabPanel("Oman", plotlyOutput("OmanOil", height = 575)),
                  tabPanel("Libya", plotlyOutput("LibyaOil", height = 575)),
                  tabPanel(p(code("FACETS")), plotOutput("FACETSOil", height = 575))
                  
      )
    )
  )
)

# Define server
server <- function(input, output) {
  
  output$downloadData <- downloadHandler(
      filename = function() {
        'crude_oil.csv'
      },
      content = function(file) {
        write.csv(df_petroleum_lease, file)
      }
    )
    
  output$downloadData2 <- downloadHandler(
    filename = function() {
      'us_shale.csv'
    },
    content = function(file) {
      write.csv(shale_oil_us, file)
    }
  )
  
  data_crude_cond <- reactive({
    df_petroleum_lease |> filter(countryId == 'WORL' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$WorldOil <- renderPlotly({
    
    viz <- ggplot(data_crude_cond(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.7, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "World oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz)
    
  })
  
  data_crude_cond_USA <- reactive({
    df_petroleum_lease |> filter(countryId == 'USA' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$USAOil <- renderPlotly({
    
    viz2 <- ggplot(data_crude_cond_USA(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "USA oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz2)
    
  })
  
  data_crude_cond_USAShale <- reactive({
    shale_oil_us |> filter(Date >= input$dates[[1]] & Date <= input$dates[[2]])
  })
  
  output$USAOilShale <- renderPlotly({
    
    viz23 <- ggplot(data_crude_cond_USAShale(), aes(x = Date, y = production_kbpd)) +
      geom_line(aes(colour = Region), linewidth = 0.5) + # geom_point(size = 0.3) +
      theme_ft_rc(strip_text_size = 10, axis_text_size = 10) +
      labs(title = "US Shale oil production by region - kbpd", x = "year", y = "production volume - kbpd")
    ggplotly(viz23)
    
  })
  
  data_crude_cond_SA <- reactive({
    df_petroleum_lease |> filter(countryId == 'SAU' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$SAOil <- renderPlotly({
    
    viz3 <- ggplot(data_crude_cond_SA(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Saudi Arabia oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz3)
  })
  
  data_crude_cond_Russia <- reactive({
    df_petroleum_lease |> filter(countryId == 'RUS' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$RussiaOil <- renderPlotly({
    
    viz4 <- ggplot(data_crude_cond_Russia(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Russia oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz4)
  })
  
  data_crude_cond_Irak <- reactive({
    df_petroleum_lease |> filter(countryId == 'IRQ' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$IrakOil <- renderPlotly({
    
    viz5 <- ggplot(data_crude_cond_Irak(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = " (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz5)
  })
  
  data_crude_cond_Iran <- reactive({
    df_petroleum_lease |> filter(countryId == 'IRN' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$IranOil <- renderPlotly({
    
    viz6 <- ggplot(data_crude_cond_Iran(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Iran oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz6)
  })
  
  data_crude_cond_China <- reactive({
    df_petroleum_lease |> filter(countryId == 'CHN' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$ChinaOil <- renderPlotly({
    
    viz7 <- ggplot(data_crude_cond_China(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "China oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz7)
  })
  
  data_crude_cond_Canada <- reactive({
    df_petroleum_lease |> filter(countryId == 'CAN' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$CanadaOil <- renderPlotly({
    
    viz8 <- ggplot(data_crude_cond_Canada(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Canada oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz8)
  })
  
  data_crude_cond_UAE <- reactive({
    df_petroleum_lease |> filter(countryId == 'ARE' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$UAEOil <- renderPlotly({
    
    viz9 <- ggplot(data_crude_cond_UAE(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "UAE oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz9)
  })
  
  data_crude_cond_Kuwait <- reactive({
    df_petroleum_lease |> filter(countryId == 'KWT' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$KuwaitOil <- renderPlotly({
    
    viz10 <- ggplot(data_crude_cond_Kuwait(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Kuwait oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz10)
  })
  
  data_crude_cond_Brazil <- reactive({
    df_petroleum_lease |> filter(countryId == 'BRA' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$BrazilOil <- renderPlotly({
    
    viz11 <- ggplot(data_crude_cond_Brazil(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Brazil oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz11)
  })
  
  data_crude_cond_Colombia <- reactive({
    df_petroleum_lease |> filter(countryId == 'COL' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$ColombiaOil <- renderPlotly({
    
    viz12 <- ggplot(data_crude_cond_Colombia(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Colombia oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz12)
  })
  
  data_crude_cond_Mexico <- reactive({
    df_petroleum_lease |> filter(countryId == 'MEX' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$MexicoOil <- renderPlotly({
    
    viz13 <- ggplot(data_crude_cond_Mexico(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Mexico oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz13)
  })
  
  data_crude_cond_Nigeria <- reactive({
    df_petroleum_lease |> filter(countryId == 'NGA' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$NigeriaOil <- renderPlotly({
    
    viz14 <- ggplot(data_crude_cond_Nigeria(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Nigeria oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz14)
  })
  
  data_crude_cond_Angola <- reactive({
    df_petroleum_lease |> filter(countryId == 'AGO' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$AngolaOil <- renderPlotly({
    
    viz15 <- ggplot(data_crude_cond_Angola(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Angola oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz15)
  })
  
  data_crude_cond_Norway <- reactive({
    df_petroleum_lease |> filter(countryId == 'NOR' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$NorwayOil <- renderPlotly({
    
    viz16 <- ggplot(data_crude_cond_Norway(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Norway oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz16)
  })
  
  data_crude_cond_Kazakhstan <- reactive({
    df_petroleum_lease |> filter(countryId == 'KAZ' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$KazakhstanOil <- renderPlotly({
    
    viz17 <- ggplot(data_crude_cond_Kazakhstan(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Kazakhstan oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz17)
  })
  
  data_crude_cond_Qatar <- reactive({
    df_petroleum_lease |> filter(countryId == 'QAT' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$QatarOil <- renderPlotly({
    
    viz18 <- ggplot(data_crude_cond_Qatar(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Qatar oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz18)
  })
  
  data_crude_cond_Algeria <- reactive({
    df_petroleum_lease |> filter(countryId == 'DZA' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$AlgeriaOil <- renderPlotly({
    
    viz19 <- ggplot(data_crude_cond_Algeria(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Algeria oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz19)
  })
  
  data_crude_cond_Oman <- reactive({
    df_petroleum_lease |> filter(countryId == 'OMN' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$OmanOil <- renderPlotly({
    
    viz20 <- ggplot(data_crude_cond_Oman(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Oman oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz20)
  })
  
  data_crude_cond_Libya <- reactive({
    df_petroleum_lease |> filter(countryId == 'LBY' & month >= input$dates[[1]] & month <= input$dates[[2]])
  })
  
  output$LibyaOil <- renderPlotly({
    
    viz21 <- ggplot(data_crude_cond_Libya(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      geom_line(aes(y = movmean), colour = "white", alpha = 0.8, linetype = "twodash") +
      theme_ft_rc() +
      labs(title = "Libya oil (crude + cond) production - kbpd + 12 month moving average", x = "month-year", y = "production volume - kbpd")
    ggplotly(viz21)
  })
  
  data_facets <- reactive({
    df_petroleum_lease |> filter(month >= input$dates[[1]] & month <= input$dates[[2]] & countryId != 'WORL' )
  })
  
  output$FACETSOil <- renderPlot({
    
    viz22 <- ggplot(data_facets(), aes(x = month, y = volume)) +
      geom_line(colour = "red", linewidth = 0.2) + # geom_point(size = 0.3) +
      facet_wrap(~ countryName, scales = "free_y") +
      theme_ft_rc(strip_text_size = 10, axis_text_size = 10) +
      labs(title = "oil (crude + condensate) production by country - kbpd", x = "month-year", y = "production volume - kbpd")
    viz22
  })
}

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