我已经构建了一个闪亮的小型应用程序来执行您的大多数要求.根据您预定义的大型数据框 df ，用户可以定义以下内容:

I have built a small shiny app to perform most of your requirements. Based on your pre-defined large dataframe df, user can define the following:

1. 选择变量 var1 和 var2 的最小值和最大值.
2. 选择标准来定义变量 var3 ，该变量用于显示不同颜色的数据点.这是一个范围.
3. 将图另存为HTML文件.
4. 汇总统计信息显示为表格.

1. Choose the minimum and maximum value for variables var1 and var2.
2. Choose criteria to define the variable var3, which is used to display different colors of data points. This is a range now.
3. Save plot as a HTML file.
4. Summary stats displayed as a table.

您可以定义其他选项，以向用户提供选择颜色的选项，依此类推.为此，也许您应该在Google上找到如何使用 scale_color_manual().

You can define further options to provide the user the option to choose color and so on. For that perhaps you should google on how to use scale_color_manual().

更新:添加了用户选项，可根据var1和var2范围值选择红色和绿色.

Update: Added user option to choose red and green color based on var1 and var2 range values.

library(shiny)
library(plotly)
library(dplyr)
library(DT)

### define a large df
set.seed(123)
df <- data.frame(var1 = rnorm(1000,10,10),
                 var2 = rnorm(1000,15,15))

ui <- fluidPage(
  titlePanel(p("My First Test App", style = "color:red")),
  sidebarLayout(
    sidebarPanel(
      p("Choose Variable limits"),

      # Horizontal line ----
      tags$hr(),
      uiOutput("var1a"), uiOutput("var1b"),
      uiOutput("var2a"), uiOutput("var2b"),
      uiOutput("criteria")

    ),
    mainPanel(
      DTOutput("summary"), br(),
      plotlyOutput("plot"),
      br(), br(), br(),
      uiOutput("saveplotbtn")
    )
  )
)

server <- function(input, output, session){
  
  output$var1a <- renderUI({
    tagList(
      numericInput("var11", "Variable 1 min",
                  min = min(df$var1), max = max(df$var1), value = min(df$var1))
    )
  })
  output$var1b <- renderUI({
    if (is.null(input$var11)){
      low1 <- min(df$var1)
    }else low1 <- max(min(df$var1),input$var11)  ## cannot be lower than var 1 minimum
    tagList(
      numericInput("var12", "Variable 1 max", min = low1, max = max(df$var1), value = max(df$var1))
    )
  })
  
  output$var2a <- renderUI({
    tagList(
      numericInput("var21", "Variable 2 min",
                   min = min(df$var2), max = max(df$var2), value = min(df$var2))
    )
  })
  output$var2b <- renderUI({
    if (is.null(input$var21)){
      low2 <- min(df$var2)
    }else low2 <- max(min(df$var2),input$var21)  ## cannot be lower than var 2 minimum
    tagList(
      numericInput("var22", "Variable 2 max", min = low2, max = max(df$var2), value = max(df$var2))
    )
  })
  
  output$criteria <- renderUI({
    req(input$var11,input$var12,input$var21,input$var22)
        
    tagList(
      sliderInput("crit11", "Variable 1 red color range:",
                  min = -10, max = 0, value = c(-10,0)),
      sliderInput("crit12", "Variable 2 red color range:",
                  min = -25, max = 0, value = c(-25,0)),
      sliderInput("crit21", "Variable 1 green color range:",
                  min = 0.1, max = 10, value = c(0.1,10)),
      sliderInput("crit22", "Variable 2 green color range:",
                  min = 0.1, max = 20, value = c(0.1,20))
    )

  })
  
  dat <- reactive({
    req(input$crit11,input$crit12,input$crit21,input$crit22)
    
    df <- df %>% filter(between(var1, input$var11, input$var12)) %>% 
                 filter(between(var2, input$var21, input$var22))
    
    # df1 <- df %>% mutate(var3 = ifelse(var1 <= i & var2 <= i, "a", ifelse(var1 <= j & var2 <= j , "b", "c")))
    
    df1 <- df %>% mutate(var3 = ifelse(between(var1, input$crit11[1], input$crit11[2]) & between(var2, input$crit12[1], input$crit12[2]), "a",
                                       ifelse(between(var1, input$crit21[1], input$crit21[2]) & between(var2, input$crit22[1], input$crit22[2]), "b", "c")))
    
  })
  
  summari <- reactive({
    req(dat())
    df1 <- dat()
    df1$var3 = as.factor(df1$var3)
    summary = df1 %>%
      group_by(var3) %>%
      dplyr::summarize(Mean_var1 = mean(var1), Mean_var2 = mean(var2), count=n())
  })
  
  output$summary <- renderDT(summari())
  
  rv <- reactiveValues()
  
  observe({
    req(dat())
    p <- ggplot(data=dat()) + geom_point(aes(x=var1, y= var2, color= var3))
    pp <- ggplotly(p)
    rv$plot <- pp
  })
  
  output$plot <- renderPlotly({
    rv$plot
  })
  
  output$saveplotbtn <-  renderUI({
    div(style="display: block; padding: 5px 350px 5px 50px;",
        downloadBttn("saveHTML",
                     HTML("HTML"),
                     style = "fill",
                     color = "default",
                     size = "lg",
                     block = TRUE,
                     no_outline = TRUE
        ) )
  })
  
  output$saveHTML <- downloadHandler(
    filename = function() {
      paste("myplot", Sys.Date(), ".html", sep = "")
    },
    content = function(file) {
      htmlwidgets::saveWidget(as_widget(rv$plot), file, selfcontained = TRUE)  ## self-contained
    }
  )

}

shinyApp(ui, server)