警告：错误：美学必须是长度 1 或与数据 (1) 相同：x、组和颜色

Question

I can get this to work without using Shiny but I am getting this error. Basically I am trying to add lines to the graph based on a checkbox. I do this by creating the vector of values using the checkbox input and then filter the dataframe. I am only trying to get covidplot to work at the moment. This is a MWE.

UI

# Define UI for random distribution app ----
ui <- fluidPage(

# App title ----
titlePanel("PM-272 Covid Dashboard"),

# Sidebar layout with input and output definitions ----
sidebarLayout(
    
    # Sidebar panel for inputs ----
    sidebarPanel(
        
        # Input: Select the columns ----
        radioButtons("var", "Plot Type:",
                     c("Raw" = "raw",
                       "Rolling Average" = "avg")),
        
        # br() element to introduce extra vertical spacing ----
        br(),
        
        checkboxGroupInput("region", "Regions to show:",
                           c("East Midlands" = "East Midlands",
                             "East of England" = "East of England",
                             "London" = "London",
                             "North East" = "North East",
                             "North West" = "North West",
                             "South East" = "South West",
                             "South West" = "South West",
                             "West Midlands" = "West Midlands",
                             "Yorkshire and The Humber" = "Yorkshire and The Humber"))
        
    ),
    
    # Main panel for displaying outputs ----
    mainPanel(
        
        # Output: Tabset w/ plot, summary, and table ----
        tabsetPanel(type = "tabs",
                    tabPanel("Cases", plotOutput("covidplot")),
                    tabPanel("Deaths", plotOutput("deathsplot"))
        )
        
    )
)
)

Server

library(httr)
library(tidyverse)

url <- 'https://api.coronavirus.data.gov.uk/v2/data?areaType=region&metric=covidOccupiedMVBeds&metric=newCasesByPublishDate&metric=newDeaths28DaysByDeathDate&metric=newDeaths60DaysByDeathDate&metric=newCasesByPublishDateRollingRate&format=json'

response <- httr::GET(url,timeout(10))

json_text <- content(response, "text")
df <- jsonlite::fromJSON(json_text)
df<-df$body
df[,c(2,3,4)] <- lapply(df[,c(2,3,4)], as.factor)

# isolate the table 
df$date = as.Date(df$date, "%Y-%m-%d")

df <- df %>% filter(date >= '2020-07-13')

# Define server logic for random distribution app ----
server <- function(input, output) {
    
    # Reactive expression to generate the requested distribution ----
    # This is called whenever the inputs change. The output functions
    # defined below then use the value computed from this expression
    d <- reactive({
        var <- switch(input$var,
                       raw = newCasesByPublishDate,
                       avg = newCasesByPublishDateRollingRate,
                       newCasesByPublishDate)
    })
    
    # Generate a plot of the data ----
    # Also uses the inputs to build the plot label. Note that the
    # dependencies on the inputs and the data reactive expression are
    # both tracked, and all expressions are called in the sequence
    # implied by the dependency graph.
    output$covidplot <- renderPlot({
        input$region
        ycol <- input$var
        grp <- input$region
        
        df2 <- df %>% filter(areaName %in% grp)
        
        covidplot <- df2 %>% ggplot(aes(x=date,y=ycol,group=areaName,color=areaName)) +
            geom_line() +
            geom_point() +
            xlab("Date") +
            ylab("Cases") +
            ggtitle("Covid Cases Over Time By Region")
        ggplotly(covidplot)
    })
    
}

Answer 1

Initially, input$region is null and you have not addressed that situation. Try this

output$covidplot <- renderPlot({
    if (is.null(input$region)) return(NULL)
    ycol <- input$var
    grp <- input$region
    
    df2 <- df %>% filter(areaName %in% grp)
    
    covidplot <- df2 %>% ggplot(aes(x=date,y=ycol,group=areaName,color=areaName)) +
      geom_line() +
      geom_point() +
      xlab("Date") +
      ylab("Cases") +
      ggtitle("Covid Cases Over Time By Region")
    ggplotly(covidplot)
  })