如何将文本传递给闪亮的 summarise()

Question

我正在构建一个闪亮的应用程序。我尝试将用户选择为 char 的函数保存到

data.frame()

中，然后使用

paste()

生成类似“n = n(), sum = sum(value), Mean = Mean(value)”或更短的内容，最后传递给 summarise()
我尝试了

quote()

和

eval(parse())

，都失败了。

library(shiny)
library(shinyjs)
library(tidyverse)

ui <- fluidPage(
  useShinyjs(),
  fluidRow(
    column(width = 3,
      wellPanel(
        selectInput("data_groupby", label = "group_by", choices = c(Choose = "", "group", "sameple", "var"), selected = c("group", "var"), multiple = TRUE),
        actionButton("data_groupby_ok", "click here to group_by"),
        selectInput("data_summarise_fun", "Function", choices = c(Choose = "", "n", "sum", "mean")),
        actionButton("data_summarise_add", "Summarise"),
        h4("paras to be passed to summarise():"),
        verbatimTextOutput("summarise_paras")
      )
    ),
    column(width = 3,
      h4("data:"),
      verbatimTextOutput("data")
    ),
    column(width = 3,
      h4("data_summarised:"),
      verbatimTextOutput("data_summarised")
    ),
    column(width = 3,
      h4("data_desired (if add 3 functions):"),
      verbatimTextOutput("data_desired")
    )
  )
)

server <- function(input, output, session) {

  aggr <- reactiveValues(
    data = NULL,
    summarise_paras = data.frame(column = character()),
    data_grouped = NULL,
    data_summarised = NULL,
    data_desired = NULL
  )

  set.seed(50)
  aggr$data <- data.frame(
    group = rep(LETTERS[1:3], each = 6),
    sample = rep(c(paste0("A_", 1:3), paste0("B_", 1:3), paste0("C_", 1:3)), each = 2),
    var = rep(c("height", "weight"), times = 9),
    value = runif(18, min = 0, max = 1)
  )

  aggr$data_desired <- data.frame(
    group = rep(LETTERS[1:3], each = 6),
    sample = rep(c(paste0("A_", 1:3), paste0("B_", 1:3), paste0("C_", 1:3)), each = 2),
    var = rep(c("height", "weight"), times = 9),
    value = runif(18, min = 0, max = 1)
  ) %>%
    group_by(group, var) %>% summarise(n = n(), sum = sum(value), mean = mean(value))

  observeEvent(input$data_groupby_ok, {
    groupby <- input$data_groupby
    aggr$data_grouped <- aggr$data %>% group_by(across(all_of(groupby)))
    disable("data_groupby")
  })

  observe({
    toggleState("data_summarise_add", nchar(input$data_summarise_fun) >0)
  })

  observeEvent(input$data_summarise_add, {

    tryCatch({
      fun <- input$data_summarise_fun

      if (fun == "n") {
        para <- "n = n()"
      } else if (fun == "sum") {
        para <- "sum = sum(value)"
      } else if (fun == "mean") {
        para <- "mean = mean(value)"
      }
      aggr$summarise_paras <- aggr$summarise_paras %>%
                              filter(column != para) %>%
                              bind_rows(data.frame(column = para))
      paras <- paste(aggr$summarise_paras$column, collapse = ",")
      aggr$data_summarised <- aggr$data_grouped %>% summarise(enquote(paras))

      reset("data_summarise_fun")
    }, error = function(e) {
      showNotification(paste(e$message), type = "error", duration = 5)
    })
  })

  output$data <- renderPrint({print(aggr$data)})
  output$summarise_paras <- renderPrint({print(aggr$summarise_paras)})
  output$data_summarised <- renderPrint({print(aggr$data_summarised)})
  output$data_desired <- renderPrint({print(aggr$data_desired)})
}

shinyApp(ui = ui, server = server)

我想要的输出是

aggr$data_desired

，它打印在我闪亮的示例中

Answer 1

问题是（大概）你希望这些值是“n = 10，sum = -0.369，mean = -0.036987”之类的东西，但你写的不是这样的 - 这很糟糕，因为它不是有效的 R 代码（在R中你不能只写

x = 1, y = 2

，你会得到错误

Error: unexpected ',' in "x = 1,"

，而且因为equals是用于赋值的，而你似乎不想将

n()

赋值给变量

n

。

一种选择是使用胶水：

data |> summarise(val = glue::glue("n = {n()}, sum = {sum(value)}, mean = {mean(value)}"), .by = c(group, var))

输出：

   group var                                                          val
1      A   a n = 10, sum = -0.369871614091487, mean = -0.0369871614091487
2      A   b   n = 10, sum = -4.90551745324375, mean = -0.490551745324375
3      A   c   n = 10, sum = -4.04729937846017, mean = -0.404729937846017
4      A   d   n = 10, sum = -2.54372850319173, mean = -0.254372850319173
5      B   c   n = 10, sum = 0.936866512219415, mean = 0.0936866512219415
6      B   d   n = 10, sum = -3.34912487194284, mean = -0.334912487194284
7      B   a n = 10, sum = -0.341116609361569, mean = -0.0341116609361569
8      B   b   n = 10, sum = -3.18225275070246, mean = -0.318225275070246
9      C   a   n = 10, sum = -4.74290766135976, mean = -0.474290766135976
10     C   b   n = 10, sum = 0.112798793892494, mean = 0.0112798793892494
11     C   c   n = 10, sum = -1.44746005504636, mean = -0.144746005504636
12     C   d   n = 10, sum = -1.31363366405953, mean = -0.131363366405953
13     D   c     n = 10, sum = -3.3104100896434, mean = -0.33104100896434
14     D   d     n = 10, sum = 1.38864716115738, mean = 0.138864716115738
15     D   a     n = 10, sum = 6.04682327356391, mean = 0.604682327356391
16     D   b   n = 10, sum = -2.40214704657337, mean = -0.240214704657337
17     E   a   n = 10, sum = -2.66630215861559, mean = -0.266630215861559
18     E   b n = 10, sum = -0.889225624753177, mean = -0.0889225624753177
19     E   c   n = 10, sum = -6.39670148391452, mean = -0.639670148391452
20     E   d   n = 10, sum = -4.79912286801664, mean = -0.479912286801664