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在 R Shiny 工作。我试图通过 selectInput() 小部件过滤一些数据，通过 textOutput 显示。当用户选择一个县时，贫困百分​​比应显示在 absolutePanel() 上。我最不擅长过滤数据。我无法弄清楚我做错了什么？我在 Shiny Gallery 中查看了一些 Shiny 应用程序示例，并浏览了 StackOverflow，但我无法查看我的函数有什么问题。我的整个方法是错误的，还是语法错误？如果您有任何线索，建议或资源，请按我的方式拍摄！（我看过的一些对我有帮助的页面：Filter data frame in Shiny app，https : //community.rstudio.com/t/reactive-filtering-and-adding-in-shiny/47739/2，https ://github。)

library(shiny)
library(shinydashboard)
library(tidyr)
library(dplyr)

用户界面

ui <- dashboardPage(
    dashboardHeader(),
    dashboardSidebar(
        selectInput("selectstate", "Select State", unique(df$Province_State)),
        selectInput("selectcounty", "Select County", choices = NULL)
    ),
    dashboardBody( 
            absolutePanel (id = "controls1",
                           class = "panel panel-default",
                           width = 330, height = 200,
                           textOutput("us_county_poverty")
            )
            
          ) )

服务器.R

 server <- function(session, input, output) {
        
        ########### SELECT STATES AND COUNTIES FUNCTIONS (SelectInput) 
        observeEvent(
            input$selectstate,
            updateSelectInput(session,"selectcounty", "Select County", 
                              choices = unique(df$Admin2[df$Province_State==input$selectstate]))
        )
        
        ##SHOW COUNTY POVERTY (renderText through selectcounty input)
        
        subset_county_poverty <-reactive({
            counties1 %>% filter(NAME==input$selectcounty)
        })
        
        output$us_county_poverty <- renderText({
            #render counties1$All.Ages.In.Poverty.Percent WHERE counties1$NAME==input$selectcounty
            paste0(subset_county_poverty()$All.Ages.In.Poverty.Percent)
        })  
}
########################################################################################
shinyApp(ui = ui, server = server)

为了使其可重现，这是我的数据：

##DATA:

##COUNTIES - polygons
#> dput(head(counties1))
structure(list(NAME = c("Abbeville-SC", "Accomack-VA", "Ada-ID", 
"Adair-IA", "Adair-KY", "Adair-MO"), Year = c(2018L, 2018L, 2018L, 
2018L, 2018L, 2018L), ID = c(45001L, 51001L, 16001L, 19001L, 
21001L, 29001L), STATE_NAME.x = c("SC", "VA", "ID", "IA", "KY", 
"MO"), All.Ages.in.Poverty.Percent = c("19.1", "17.3", "9.7", 
"9.7", "23.8", "23.9"), GEOID = c("45001", "51001", "16001", 
"19001", "21001", "29001"), ALAND = c("1270337025", "1163743170", 
"2724902770", "1474404199", "1049678094", "1469362052"), AWATER = c("53126680", 
"2229242744", "21961614", "2597996", "18430783", "5468507"), 
    INTPTLAT = c("+34.2138089", "+37.7659435", "+43.4514767", 
    "+41.3285283", "+37.1055589", "+40.1906655"), INTPTLON = c("-082.4604603", 
    "-075.7578073", "-116.2443760", "-094.4781643", "-085.2813796", 
    "-092.6035922"), X = c(-82.459, -75.757, -116.241, -94.471, 
    -85.281, -92.601), Y = c(34.223, 37.765, 43.451, 41.331, 
    37.104, 40.191)), row.names = c(NA, 6L), class = "data.frame")




##df - csv data
#> dput(head(df))
structure(list(FIPS = c(1001, 1001, 1001, 1001, 1001, 1001), 
    Admin2 = c("Autauga-AL", "Autauga-AL", "Autauga-AL", "Autauga-AL", 
    "Autauga-AL", "Autauga-AL"), Province_State = c("AL", "AL", 
    "AL", "AL", "AL", "AL"), Lat = c(32.53952745, 32.53952745, 
    32.53952745, 32.53952745, 32.53952745, 32.53952745), Long_ = c(-86.64408227, 
    -86.64408227, -86.64408227, -86.64408227, -86.64408227, -86.64408227
    ), Combined_Key = c("Autauga, Alabama, US", "Autauga, Alabama, US", 
    "Autauga, Alabama, US", "Autauga, Alabama, US", "Autauga, Alabama, US", 
    "Autauga, Alabama, US"), date = structure(c(18284, 18285, 
    18286, 18287, 18288, 18289), class = "Date"), value = c(0, 
    0, 0, 0, 0, 0)), row.names = 782:787, class = "data.frame")
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