找不到对象'输出'的ShinyApp问题

问题描述 投票:0回答:1

我在闪亮的应用程序中调试时遇到了一些麻烦。我添加了一些新内容后,它不起作用,但是它仍然可以打开闪亮的应用程序平台,尽管某些内容为空白且出现错误消息。桌子和散点图对我不起作用。以下是不断出现的错误。我的网站一直说我也已与服务器断开连接。

output $ plot1中的错误

输出$ table中的错误

找不到函数“ y”

警告:错误!:无效的参数类型54:installExprFunction53:renderText52:服务器[#16]!quoted错误:无效的参数类型

我不知道如何使表格和曲线图起作用。



# shape <- st_read("tl_2016_53_cousub.shp")
# sta <- read_csv("NOAA_SeattlePortageBay.csv") %>% #weather station
#   mutate(lon = Longitude, lat = Latitude) %>%
#   st_as_sf(coords = c("LONGITUDE", "LATITUDE"), crs=4326) %>%
#   st_join(shape)

trend_data <- read_csv("NOAA_SeattlePortageBay.csv")

y <- trend_data %>%
  sample_n(0) %>%       
  select("Total Liquid Content", "Extreme Max Precip", "Annual Mean Temp", "Mean Max Temp", "Mean Min Temp") 


ui <- fluidPage(title = "Seattle, Washington 40 Years Climate",
                navlistPanel(
                  tabPanel(title = "Introduction",
                           leafletOutput("map"),
                           textOutput("dis")),

                  tabPanel(title = "Climate Graphs",
                           plotOutput("plot1"),
                           # plotOutput("plot2"),
                           plotOutput("plot3"),
                           plotOutput("plot4"),
                           plotOutput("plot5")),

                  tabPanel(title = "Data Table",
                           tableOutput("table")),

                  tabPanel(title = "Plot Model",
                           plotOutput("scatterplot"),
                           varSelectInput("yvar", "Y Variable:", data=y, selected="Total Liquid Content"))
                )
)

server <- function(input, output) {
  # output$map <- renderLeaflet({   #doesn't work so I use another route
  #   leaflet(data = sta) %>%
  #     addTiles() %>%
  #     addMarkers(~lon, ~lat, label = ~Name)
  #     output$dis <- renderText("Seattle is a city located in the State of Washington.
  #                            Seattle Portage Bay Weather Station by NOAA.")

  output$map <- renderLeaflet({
    leaf <- leaflet() %>%
      addTiles() %>%  # Add default OpenStreetMap map tiles
      addMarkers(lng=-122.3, lat= 47.65,
               popup="Seattle Portage Bay, WA, USA, GHCND:USW00024281")
  })

  output$dis <- renderText("Seattle Portage Bay Weather Station by NOAA.","\r",
                           "Elevatioin: 5.8m", "\r",
                           "Period of Record: January 1, 1894 to January 1, 1997")

  output$plot1 <- renderPlot({                         #Error in output$plot1 <- renderPlot({ : object 'output' not found
    ggplot(trend_data) +                               #unexpected '}' in "}"
      geom_point(aes(Year, trend_data$`Total Liquid Content`),
                 size = 3, color = "dark blue") +
      geom_smooth(aes(Year, trend_data$`Total Liquid Content`), size = 1, color = "black", method = "lm") +
      labs(title = "Total Precipitation",
           x = "Year", y = "Precipitation in Inches") +
      theme(text= element_text(size=15,  family="Arial"), 
            plot.title = element_text(hjust = 0.5)) + ylim(15, 55) +
      scale_x_continuous(breaks = seq(from = 1940, to = 2000, by = 5))
  })

  # output$plot2 <- renderPlot({
  #   ggplot(trend_data) +
  #     geom_point(aes(Year, trend_data$`Extreme Max Precip`),
  #                size = 3, color = "red") +
  #     geom_smooth(aes(Year, trend_data$`Extreme Max Precip`), size = 1, color = "black", method = "lm") +
  #     labs(title = "Extreme Max Precipitation",
  #          x = "Year", y = "Precipitation in Inches") +
  #     theme(text= element_text(size=15,  family="Arial"),
  #           plot.title = element_text(hjust = 0.5)) + ylim(15, 55) +
  #     scale_x_continuous(breaks = seq(from = 1940, to = 2000, by = 5))
  # })

  output$plot3 <- renderPlot({
    ggplot(trend_data) + 
      geom_point(aes(Year, trend_data$`Annual Mean Temp`), 
                 size = 3, color = "brown") + 
      geom_smooth(aes(Year, trend_data$`Annual Mean Temp`), size = 1, color = "black", method = "lm") + 
      labs(title = "Average Temperature",
           x = "Year", y = "Temperature in Fahrenheit") +
      theme(text= element_text(size=15,  family="Arial"), 
            plot.title = element_text(hjust = 0.5)) + ylim(50, 56) +
      scale_x_continuous(breaks = seq(from = 1940, to = 2000, by = 5))
  })

  output$plot4 <- renderPlot({
    ggplot(trend_data) + 
      geom_point(aes(Year, trend_data$`Mean Max Temp`), 
                 size = 3, color = "red") + 
      geom_smooth(aes(Year, trend_data$`Mean Max Temp`), size = 1, color = "black", method = "lm") +
      labs(title = "Average Maximum Temperature",
           x = "Year", y = "Temperature in Fahrenheit") +
      theme(text= element_text(size=15,  family="Arial"), 
            plot.title = element_text(hjust = 0.5)) + ylim(57, 64) +
      scale_x_continuous(breaks = seq(from = 1940, to = 2000, by = 5))
  })

  output$plot5 <- renderPlot({
    ggplot(trend_data) + 
      geom_point(aes(Year, trend_data$`Mean Min Temp`), 
                 size = 3, color = "light blue") + 
      geom_smooth(aes(Year, trend_data$`Mean Min Temp`), size = 1, color = "black", method = "lm") + 
      labs(title = "Average Minimum Temperature",
           x = "Year", y = "Temperature in Fahrenheit") +
      theme(text= element_text(size=15,  family="Arial"), 
            plot.title = element_text(hjust = 0.5)) + ylim(43, 50) +
      scale_x_continuous(breaks = seq(from = 1940, to = 2000, by = 5))
  })

  output$table <- renderDataTable(trend_data())

  output$scatterplot <- renderPlot({
    ggplot(data = y()) +              #can't find function y
      geom_point(mapping = aes(x = Year, y = !!input$yvar)) +
      geom_smooth(mapping = aes(x = Year, y = !!input$yvar), method="lm")
  })

}

shinyApp(ui = ui, server = server)
r ggplot2 shiny shinyapps
1个回答
0
投票
output$table <- renderDataTable(trend_data())

在上面的代码中,您的trend_data不是反应性数据集。您可以

  1. 使trend_data为反应性数据集,该数据集将根据Shiny App中的某些反应性而变化。

    trend_data <- reactive({ #some code here })

  2. 或按原样使用趋势数据

    output$table <- renderDataTable(trend_data)

并且在plot1错误中删除trend_data$

output$plot1 <- renderPlot({                        
    ggplot(trend_data) +                       
      geom_point(aes(Year, `Total Liquid Content`),
                 size = 3, color = "dark blue") +
      geom_smooth(aes(Year, `Total Liquid Content`), size = 1, color = "black", method = "lm") +
      labs(title = "Total Precipitation",
           x = "Year", y = "Precipitation in Inches") +
      theme(text= element_text(size=15,  family="Arial"), 
            plot.title = element_text(hjust = 0.5)) + ylim(15, 55) +
      scale_x_continuous(breaks = seq(from = 1940, to = 2000, by = 5))
  })
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