R: ggplot2 с geom_map возвращает «x и единицы должны иметь длину> 0», несмотря на значения, преобразованные в факторы

Question

Я работаю над примитивным блестящим приложением, которое отображает некоторые данные из проекта Open Data for Scotland. Я разработал запросы SPARQL, которые производят кадр данных, напоминающий экстракт представленного ниже

dz_label overall.quantiles 
S010001 8 
S010002 9 

У меня есть укрепленный шейп, и я пытаюсь их отобразить с помощью следующего кода:

ggplot() + 
     geom_map(data = dta.simd, aes(map_id = dz_label, 
            fill = as.factor(dta.simd$overall.quantiles)), 
       map = shps.dzs2001) + 
     geom_path(data = shps.dzs2001, aes(x=long, y=lat, group=group), 
       colour="black", size=0.25) 

код возвращает ошибку

Error: 'x' and 'units' must have length > 0 

Если я понимаю, подобное обсуждение (1, 2), проблема связана с классами значений. Тем не менее, я понимаю, что as.factor() должен рассмотреть это, но, очевидно, это не так. Полный код для приложения приведен ниже. Естественно, я буду благодарен за любую помощь.

Сервер

# Libs 
require(shiny); require(SPARQL); require(ggplot2); require(rgeos); require(maptools); 
require(RCurl) 

# Server function 
shinyServer(function(input, output) { 

    # Source the data 

    ## Source the SPARQL data 
    ### Define endpoint URL. 
    endpoint <- "http://data.opendatascotland.org/sparql.csv" 

    ### Create Query and download table for the SIMD rank 
    query.simd <- "PREFIX stats: <http://statistics.data.gov.uk/id/statistical-geography/> 
     PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#> 
     PREFIX simd: <http://data.opendatascotland.org/def/simd/> 
     PREFIX cube: <http://purl.org/linked-data/cube#> 
     PREFIX stats_dim: <http://data.opendatascotland.org/def/statistical-dimensions/> 
     PREFIX year: <http://reference.data.gov.uk/id/year/> 

     SELECT DISTINCT 
     ?dz_label 
     ?overall_rank 
     ?income_deprivation_rank 
     ?employment_deprivation_rank 
     ?health_deprivation_rank 
     ?education_deprivation_rank 
     ?access_deprivation_rank 
     ?housing_deprivation_rank 
     ?crime_deprivation_rank 

     WHERE { 

     GRAPH <http://data.opendatascotland.org/graph/simd/rank> { 
     ?overall_rank_observation stats_dim:refArea ?dz . 
     ?overall_rank_observation stats_dim:refPeriod year:2012 . 
     ?overall_rank_observation simd:rank ?overall_rank . 
     } 

     GRAPH <http://data.opendatascotland.org/graph/simd/income-rank> { 
     ?income_rank_observation stats_dim:refArea ?dz . 
     ?income_rank_observation stats_dim:refPeriod year:2012 . 
     ?income_rank_observation simd:incomeRank ?income_deprivation_rank . 
     } 

     GRAPH <http://data.opendatascotland.org/graph/simd/employment-rank> { 
     ?employment_rank_observation stats_dim:refArea ?dz . 
     ?employment_rank_observation stats_dim:refPeriod year:2012 . 
     ?employment_rank_observation simd:employmentRank ?employment_deprivation_rank . 
     } 

     GRAPH <http://data.opendatascotland.org/graph/simd/health-rank> { 
     ?health_rank_observation stats_dim:refArea ?dz . 
     ?health_rank_observation stats_dim:refPeriod year:2012 . 
     ?health_rank_observation simd:healthRank ?health_deprivation_rank . 
     } 

     GRAPH <http://data.opendatascotland.org/graph/simd/education-rank> { 
     ?education_rank_observation stats_dim:refArea ?dz . 
     ?education_rank_observation stats_dim:refPeriod year:2012 . 
     ?education_rank_observation simd:educationRank ?education_deprivation_rank . 
     } 

     GRAPH <http://data.opendatascotland.org/graph/simd/geographic-access-rank> { 
     ?access_rank_observation stats_dim:refArea ?dz . 
     ?access_rank_observation stats_dim:refPeriod year:2012 . 
     ?access_rank_observation simd:geographicAccessRank ?access_deprivation_rank . 
     } 

     GRAPH <http://data.opendatascotland.org/graph/simd/housing-rank> { 
     ?housing_rank_observation stats_dim:refArea ?dz . 
     ?housing_rank_observation stats_dim:refPeriod year:2012 . 
     ?housing_rank_observation simd:housingRank ?housing_deprivation_rank . 
     } 

     GRAPH <http://data.opendatascotland.org/graph/simd/crime-rank> { 
     ?crime_rank_observation stats_dim:refArea ?dz . 
     ?crime_rank_observation stats_dim:refPeriod year:2012 . 
     ?crime_rank_observation simd:crimeRank ?crime_deprivation_rank . 
     } 

    { 
     SELECT ?dz ?dz_label WHERE 
    { 
     ?dz a <http://data.opendatascotland.org/def/geography/DataZone> . 
     ?dz rdfs:label ?dz_label . 
    } 
    } 
    }" 

    ## Make the data table for SIMD 
    dta.simd <- SPARQL(url = endpoint, query = query.simd, format = "csv")$results 
    ### Clean the data frame 
    dta.simd$dz_label <- gsub("Data Zone","", dta.simd$dz_label) 

    # Readings shapefiles (pass only file that ends with shp) 
    shps.dzs2001 <- readShapeSpatial("data/SG_DataZone_Bdry_2001.shp") 

    ## Read shapefiles 
    shps.dzs2001 <- fortify(shps.dzs2001, region= "DZ_CODE") 

    # Switch on the gclibpermit 
    gpclibPermit() 

    # Make the plot 
    output$distPlot <- renderPlot({ 

    ### Get the column index fumber 
    col.ind <- match(input$firstvar, colnames(dta.simd)) 


    #### Calculate the breaks 
    ##### Take tha quantilies value from the UI 
    ##### Obtain the breaks 
    dta.simd$column <- as.numeric(as.character(dta.simd[,col.ind])) 
    dta.simd$overall.quantiles <- ceiling(sapply(dta.simd$column,function(x) 
     sum(x-dta.simd$column>=0))/(length(dta.simd$column)/input$quannum)) 

    #### Graph the chart 
    ggplot() + 
     geom_map(data = dta.simd, aes(map_id = dz_label, 
            fill = as.factor(dta.simd$overall.quantiles)), 
       map = shps.dzs2001) + 
     geom_path(data = shps.dzs2001, aes(x=long, y=lat, group=group), 
       colour="black", size=0.25) 

    ### Re-calculate summary stats 
    summary.data <- head(dta.simd) 

    }) 
    ### Do the summary tables 
    output$summary.table <- renderDataTable({summary.data}) 
}) 

UI

require(shiny) 

# Define list of options 
choices.list <- list("Overall Rank" = "overall_rank", 
        "Income" = "income_deprivation_rank", 
        "Employment" = "employment_deprivation_rank", 
        "Health" = "health_deprivation_rank", 
        "Education" = "education_deprivation_rank", 
        "Access to Services" = "access_deprivation_rank", 
        "Housing" = "housing_deprivation_rank", 
        "Crime" = "crime_deprivation_rank" 
        ) 

# Define UI for application that draws a histogram 
shinyUI(fluidPage(

    # Application title 
    titlePanel("Scottish Index of Multiple Deprivation 2012"), 

    # Sidebar with a slider input for the number of bins 
    sidebarLayout(
    sidebarPanel(
     selectInput(inputId = "firstvar", 
        label = "Index domain to map", 
        choices = choices.list, 
        selected = "income_deprivation_rank"), 
     sliderInput("quannum", label = "Number of quantiles", 
        min = 0, 
        max = 100, 
        value = 10)), 

    # Show a plot of the generated distribution 
    mainPanel(
     plotOutput("distPlot", height = "700px"), 
     dataTableOutput("summary.data"), 
     h5("Notes"), 
     p("The data is sourced live from the Open Data for Scotland Project. The shapefiles are sourced from the Scottish Neighbourhood Statistics.") 
    ) 
) 
)) 

Answer 1

fill=factor(overall.quantiles) 

я столкнулся с подобной проблемой и был в состоянии исправить это следующим образом.