sliderInput控制的随机样本和

唯一的问题是示例没有对excel文件中的净返回列求和，这会随着sliderInput而更改。我尝试使用sum和summary，但没有得到结果。事实上，如果没有scale_y_continuous breaks函数，它会绘制一系列值（这就是我知道它没有做我想要的事情的原因）。感谢您的帮助！谢谢

用户界面：

服务器：

server = function(input, output) {
  output$filter = renderPlot({
  mysample = filtered[sample(1:nrow(filtered), input$obs,
                            replace=FALSE),]
  mysample2 = unfiltered[sample(1:nrow(unfiltered), input$obs,
                                replace=FALSE),]
  tbl = bind_rows(Filtered = mysample, Unfiltered = mysample2,
                  .id="type")
  #sum(mysample)
  #sum(mysample2)
  #summarise(mysample = sum(mysample),
  #          mysample2 = sum(mysample2))

  ggplot(tbl, aes(x = type, fill = type)) +
    geom_col(aes(y = Net_Return)) +
    labs(x = "Type", y = "Net Return") +
    theme_bw() +
    theme(legend.position = "none") +
    scale_y_continuous(labels = scales::dollar, limits = c(0, 2500000))  
 })
}  

---

我们需要一个

分组依据

总和

即

library(ggplot2)
library(shiny)
library(dplyr)

ui = fluidPage(
  sliderInput("obs", "Number of Observations", value = 550, min = 1, max = 10),
  plotOutput("filter")
)    
filtered <- mtcars[1:15,]
unfiltered <- mtcars

server = function(input, output) {
  output$filter = renderPlot({
    mysample = filtered[sample(1:nrow(filtered), input$obs,
                               replace=FALSE),]
    mysample2 = unfiltered[sample(1:nrow(unfiltered), input$obs,
                                  replace=FALSE),]
    tbl = bind_rows(Filtered = mysample, Unfiltered = mysample2,
                    .id="type") %>%
                    group_by(type) %>%
                    summarise(wt = sum(wt))

    print(nrow(tbl))
    print(tbl)
    #sum(mysample)
    #sum(mysample2)
    #summarise(mysample = sum(mysample),
    #          mysample2 = sum(mysample2))

    ggplot(tbl, aes(x = type,  fill = type)) +
      geom_col(aes(y =wt)) +
      labs(x = "Type", y = "Weight") +
      theme_bw() +
      theme(legend.position = "none") 
  })
}  
shinyApp(ui, server)

库（ggplot2）
图书馆（闪亮）
图书馆（dplyr）
ui=fluidPage(
滑块输入（“obs”，“观察次数”，值=550，最小值=1，最大值=10），
打印输出（“过滤器”）
)    
过滤%
总结（wt=总和（wt））
打印（nrow（待定））
打印（待定）
#总和（我的样本）
#总和（样本2）
#总结（mysample=sum（mysample），
#mysample2=总和（mysample2））
ggplot（tbl，aes（x=类型，填充=类型））+
几何坐标（aes（y=wt））+
实验室（x=“类型”，y=“重量”）+
主题_bw（）+
主题（legend.position=“无”）
})
}  
shinyApp（用户界面、服务器）

-输出

---

谢谢！正是我需要的

library(ggplot2)
library(shiny)
library(dplyr)

ui = fluidPage(
  sliderInput("obs", "Number of Observations", value = 550, min = 1, max = 10),
  plotOutput("filter")
)    
filtered <- mtcars[1:15,]
unfiltered <- mtcars

server = function(input, output) {
  output$filter = renderPlot({
    mysample = filtered[sample(1:nrow(filtered), input$obs,
                               replace=FALSE),]
    mysample2 = unfiltered[sample(1:nrow(unfiltered), input$obs,
                                  replace=FALSE),]
    tbl = bind_rows(Filtered = mysample, Unfiltered = mysample2,
                    .id="type") %>%
                    group_by(type) %>%
                    summarise(wt = sum(wt))

    print(nrow(tbl))
    print(tbl)
    #sum(mysample)
    #sum(mysample2)
    #summarise(mysample = sum(mysample),
    #          mysample2 = sum(mysample2))

    ggplot(tbl, aes(x = type,  fill = type)) +
      geom_col(aes(y =wt)) +
      labs(x = "Type", y = "Weight") +
      theme_bw() +
      theme(legend.position = "none") 
  })
}  
shinyApp(ui, server)