Question

我真的需要你的帮助。我试图建立一个闪亮的应用程序，可以根据以前完成的项目的大小发布项目的大致时间。（见下面的df）

Df看起来像这样（样本）。

    Department Hours   SIZE
1         HVAC  1281  38000
7         HVAC   202  38000
13        HVAC    52  33000
19        HVAC   118  33000
25        HVAC  2069  22000
31        HVAC  1546  22000
37        HVAC   282    450
43        HVAC     1  17000
49        HVAC   725   7000
55        HVAC    50 250000
61        HVAC  1573  11000
67        HVAC   100  11000
73        HVAC   562    500
79        HVAC  1441   7900

我使用geom_smooth制作ggplot图，以根据SIZE查看每个部门的平均小时数。

这就是它的样子。

这是我正在努力的Shiny APP骨架。我希望表格根据ggplot蓝线更改值。因此，例如，如果在此示例中将SIZE输入设置为50.000，则表格将显示大约2000的值。

我真的希望它有意义，因为我知道这是令人困惑的。

有关如何进行的任何想法？我真的很感激。

这是Shiny APP代码

library(shiny)
hello <- data.frame(125)
colnames(hello) <- "VALUE"

ui <- fluidPage(titlePanel("Pricing Calculator", windowTitle = "app"),

                sidebarLayout(sidebarPanel(


                  sliderInput(inputId = "slideruno",label = "Size (m2)", min = 0, max = 250000,
                              value = 50000,step = 2500, ticks = T)

                )

                ,mainPanel(
                  tableOutput(outputId = "tableuno")
                )
                ))


server <- function(input, output) {

  output$tableuno <- renderTable(hello)  

}

shinyApp(ui, server)

用于制作ggplot的代码：

  ggplot(HVAC, aes(SIZE, Hours)) + geom_point(aes(color = Department)) + stat_smooth()

数据首次亮相

dput（HVAC）

structure(list(Department = c("HVAC", "HVAC", "HVAC", "HVAC", 
"HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", 
"HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", 
"HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", 
"HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", 
"HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", 
"HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", 
"HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC", 
"HVAC", "HVAC", "HVAC", "HVAC", "HVAC", "HVAC"), Hours = c(1281, 
202, 52, 118, 2069, 1546, 282, 1, 725, 50, 1573, 100, 562, 1441, 
475, 1415, 191, 1498, 33, 763, 1, 81, 1433, 305, 1561, 1960, 
6834, 274, 1465, 646, 3586, 77, 52, 395, 197, 10, 67, 33, 59, 
431, 4, 154, 665, 461, 35, 331, 401, 605, 26, 99, 3981, 598, 
47, 434, 39, 3578, 364, 124, 666, 58, 3086, 375, 7, 277, 29, 
47), SIZE = c(38000, 38000, 33000, 33000, 22000, 22000, 450, 
17000, 7000, 250000, 11000, 11000, 500, 7900, 7900, 7900, 77000, 
1e+05, 1000, 2250, 2250, 15000, 35000, 7000, 7000, 1000, 51000, 
51000, 15000, 29000, 23000, 23000, 23000, 3600, 27500, 2800, 
2800, 3500, 3500, 6500, 20000, 192000, 2200, 8000, 30000, 36000, 
6500, 6500, 11000, 70000, 55000, 3000, 1600, 36000, 36000, 17000, 
1800, 5800, 15000, 46000, 26000, 34000, 7500, 130000, 36000, 
15000)), .Names = c("Department", "Hours", "SIZE"), class = "data.frame", row.names = c(1L, 
7L, 13L, 19L, 25L, 31L, 37L, 43L, 49L, 55L, 61L, 67L, 73L, 79L, 
85L, 91L, 103L, 109L, 115L, 121L, 127L, 133L, 139L, 145L, 151L, 
157L, 163L, 169L, 175L, 181L, 187L, 193L, 199L, 205L, 211L, 217L, 
223L, 229L, 241L, 253L, 259L, 265L, 271L, 277L, 283L, 289L, 295L, 
301L, 307L, 313L, 319L, 325L, 331L, 337L, 343L, 349L, 355L, 361L, 
367L, 373L, 379L, 397L, 403L, 415L, 421L, 445L))

Answer 1

或者你可以从ggplot获得stat_smooth，如

p=ggplot(HVAC, aes(SIZE, Hours)) + geom_point(aes(color = Department)) + stat_smooth(aes(outfit=fit<<-..y..))
    ddd=ggplot_build(p)$data[[2]][,1:2]

并且完全闪亮将是

library(shiny)
library(ggplot2)

ui <- fluidPage(titlePanel("Pricing Calculator", windowTitle = "app"),

                sidebarLayout(sidebarPanel(


                  sliderInput(inputId = "slideruno",label = "Size (m2)", min = 0, max = 250000,
                              value = 50000,step = 2500, ticks = T)

                )

                ,mainPanel(
                  tableOutput(outputId = "tableuno")
                )
                ))



server <- function(input, output) {

  output$tableuno <- renderTable({
    p=ggplot(HVAC, aes(SIZE, Hours)) + geom_point(aes(color = Department)) + stat_smooth(aes(outfit=fit<<-..y..))
    ddd=ggplot_build(p)$data[[2]][,1:2]
    ddd=ddd[ddd[[2]]<=input$slideruno,]

    data.frame("Value"=ddd[nrow(ddd),1])


  })  

}

shinyApp(ui, server)

当然，如果我正确理解您希望如何从stat_smooth()

获取一个值

Answer 2

不确定完全理解，但您可能需要在服务器端构建模型，然后使用predict。 stat_smooth默认使用loess。有关iris数据集的示例，因为我无法重现您的示例：

mod <- loess(Sepal.Length ~ Sepal.Width, iris)
predict(mod, newdata = data.frame(Sepal.Width=3))

服务器端：在这里，您可能只需要使用您的值（Hours，SIZE，HVAC）更改它，并更改3的{{1}}。然后在input$slideruno内将predict的结果分配给output$predicted。

UI方面：只是renderText。

基于geom_smooth的光泽表适合

2 个答案: