使用selectInput确定在计算中要使用的数据名中的哪一列

Question

一个用户从一个selectInput中选择一个列名，我想在一个将显示在传单地图中的计算中使用它。一般的想法是，在选择一栏时，我们会：

EduAtt_df$percent <- reactive({100*(EduAtt_df$COLUMNSELECTED/EduAtt_df$total)});

我试过：

EduAtt_df$percent <- reactive({100*(EduAtt_df$[input$x]/EduAtt_df$total)});

这会产生错误：

警告:rep中的错误:尝试复制一个类型为“闭包”堆栈跟踪(最内部第一)的对象: 39：$<-.data.frame 38：$<- C:\Users\lrichards\Documents\RShiny\ACSEduAttain\ACSEduAttain/app.R#128 37: C:\Users\lrichards\Documents\RShiny\ACSEduAttain\ACSEduAttain/app.R#128 1: rep中的runApp错误(值，length.out =nrow)：尝试复制一个类型为“闭包”的对象

如何使用selectInput选择来“选择”要在计算中使用的列？

这是我目前的密码。这需要一个普查API密钥才能使用。

# Load packages -----------------------------------------------------
library(rgdal)
library(sp)
library(leaflet)
library(dplyr)
library(ggplot2)
library(tigris)
library(acs)
library(stringr)

# Load data ---------------------------------------------------------
api.key.install(key="YourCensusKey");
counties <- c(103);
tracts <- tracts(state = 'FL', county = counties, cb=TRUE);
geo<-geo.make(state=c("FL"), county=counties, tract="*");

EduAtt<-acs.fetch(endyear = 2015, span = 5, geography = geo, table.number = "B15003", col.names = "pretty");

EduAtt_df <- data.frame(
    paste0(
        str_pad(EduAtt@geography$state, 2, "left", pad="0"),
        str_pad(EduAtt@geography$county, 3, "left", pad="0"),
        str_pad(EduAtt@geography$tract, 6, "left", pad="0")),
    EduAtt@estimate[,c(
        "Educational Attainment for the Population 25 Years and Over: Total:",
        "Educational Attainment for the Population 25 Years and Over: No schooling completed",
        "Educational Attainment for the Population 25 Years and Over: Nursery school",
        "Educational Attainment for the Population 25 Years and Over: Kindergarten",
        "Educational Attainment for the Population 25 Years and Over: 1st grade",
        "Educational Attainment for the Population 25 Years and Over: 2nd grade",
        "Educational Attainment for the Population 25 Years and Over: 3rd grade",
        "Educational Attainment for the Population 25 Years and Over: 4th grade",
        "Educational Attainment for the Population 25 Years and Over: 5th grade",
        "Educational Attainment for the Population 25 Years and Over: 6th grade",
        "Educational Attainment for the Population 25 Years and Over: 7th grade",
        "Educational Attainment for the Population 25 Years and Over: 8th grade",
        "Educational Attainment for the Population 25 Years and Over: 9th grade",
        "Educational Attainment for the Population 25 Years and Over: 10th grade",
        "Educational Attainment for the Population 25 Years and Over: 11th grade",
        "Educational Attainment for the Population 25 Years and Over: 12th grade, no diploma",
        "Educational Attainment for the Population 25 Years and Over: Regular high school diploma",
        "Educational Attainment for the Population 25 Years and Over: GED or alternative credential",
        "Educational Attainment for the Population 25 Years and Over: Some college, less than 1 year",
        "Educational Attainment for the Population 25 Years and Over: Some college, 1 or more years, no degree",
        "Educational Attainment for the Population 25 Years and Over: Associate's degree",
        "Educational Attainment for the Population 25 Years and Over: Bachelor's degree",
        "Educational Attainment for the Population 25 Years and Over: Master's degree",
        "Educational Attainment for the Population 25 Years and Over: Professional school degree",
        "Educational Attainment for the Population 25 Years and Over: Doctorate degree")
        ],
    stringsAsFactors = FALSE);

rownames(EduAtt_df) <- 1:nrow(EduAtt_df);
names(EduAtt_df)<-c("GEOID", "total", "no_school","Nursery", "Kindergarten", "g1st", "g2nd", "g3rd", "g4th", "g5th", "g6th", "g7th", "g8th", "g9th", "g10th", "g11th", "g12th", "HS", "GED", "col_less1", "col_1nodegree", "AS", "BA", "MA", "Prof", "PHd");

# Initial page load calculation
EduAtt_df$percent <- 100*(EduAtt_df$g12th/EduAtt_df$total);

EduAtt_merged<- geo_join(tracts, EduAtt_df, "GEOID", "GEOID");
EduAtt_merged <- EduAtt_merged[EduAtt_merged$ALAND>0,];

popup <- paste0("GEOID: ", EduAtt_merged$GEOID, "<br>", "Percent of Population With AS: ", round(EduAtt_merged$percent,2));
pal <- colorNumeric(palette = "RdPu", domain = EduAtt_merged$percent);
map3<-leaflet() %>%
    addProviderTiles("CartoDB.Positron") %>%
    addPolygons(data = EduAtt_merged, fillColor = ~pal(percent), color = "#b2aeae", fillOpacity = 0.7, weight = 1, smoothFactor = 0.2, popup = popup) %>%
    addLegend(pal = pal, values = EduAtt_merged$percent, position = "bottomright", title = "Percent of Population<br>With AS", labFormat = labelFormat(suffix = "%"));



# UI ----------------------------------------------------------------
ui <- fluidPage(

  # App title -------------------------------------------------------
  titlePanel("Educational Attainment By Population"),

  # Sidebar layout with a input and output definitions --------------
  sidebarLayout(

    # Inputs --------------------------------------------------------    
    sidebarPanel(
      selectInput('x', 'X', names(EduAtt_df))
    ),

    # Output --------------------------------------------------------    
    mainPanel(
      textOutput("testvar"),
      leafletOutput("map", height = "600px", width = "700px")
    )

  )
)


# SERVER ------------------------------------------------------------
server <- function(input, output) {
  output$testvar = renderText(input$x);
  EduAtt_df$percent <- reactive({100*(EduAtt_df[input$x]/EduAtt_df$total)});

  # Map -------------------------------------------------------
  output$map <- renderLeaflet({
    map3
    });
}

# Run app -----------------------------------------------------------
shinyApp(ui = ui, server = server);

Answer 1

您正在尝试将一个反应性函数分配给数据帧的一个列，这是不起作用的。一个很长的解释可以在这个闪亮的网站上找到。为您的案例提供了一个最小的可重现性示例：

library(shiny)

ui <- fluidPage(
   sidebarLayout(
      sidebarPanel(selectInput("x", "Pick a column", choices = names(mtcars))),
      mainPanel(tableOutput("result")))
)

mtcars$new_column <- reactive(100 * mtcars[[input$x]])

server <- function(input, output) {
   output$result <- renderTable({
     return(mtcars)
   })
}

shinyApp(ui = ui, server = server)

您可以将计算移到反应性上下文中，然后删除对reactive的调用。在您的例子中，可能是renderLeaflet函数，在上面的示例中，如下所示：

library(shiny)

ui <- fluidPage(
   sidebarLayout(
      sidebarPanel(selectInput("x", "Pick a column", choices = names(mtcars))),
      mainPanel(tableOutput("result")))
)

server <- function(input, output) {
   output$result <- renderTable({
     mtcars$new_column <- 100 * mtcars[[input$x]]
     return(mtcars)
   })
}

shinyApp(ui = ui, server = server)