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次の光沢のあるコードを設定しました。

グローバル.R:

library(shiny)
library(gapminder)
library(tidyverse)
library(scales)

ui.R:

fluidPage(
titlePanel("Gapminder Hierarchical Clustering of Countries"),
sidebarLayout(
    sidebarPanel(
        sliderInput("numCluster", "Choose number of clusters:", 2, 6, 2),
        checkboxGroupInput("ContinentSelect", "Select which continents to include in the cluster analysis:", 
                                             choices = levels(gapminder$continent), selected = levels(gapminder$continent)),
        sliderInput("numYear", "Select years to include in the cluster analysis:", min(gapminder$year), max(gapminder$year), 
                                c(min(gapminder$year), max(gapminder$year)), step = 5, ticks = FALSE, sep = "")
),
mainPanel(
plotOutput("Chart"),
br(),br(),
tableOutput("SummaryClusters")
)
)
)

そしてserver.R:

function(input, output){

gapcluster <- function(df, numCluster){
    df_scaled <- df %>% mutate(scale_lifeExp = scale(lifeExp),
                                                         scale_pop = scale(pop),
                                                         scale_gdpPercap = scale(gdpPercap))
    gapclusters <- df_scaled[,c("scale_lifeExp", "scale_pop", "scale_gdpPercap")] %>% dist() %>% hclust()
    Clustercut <- cutree(gapclusters, numCluster)
    return(Clustercut)
}

#Creating a data frame based on inputs
filtered_gap <- reactive({ #If no continents are selected
    if (is.null(input$ContinentSelect)) {
        return(NULL)
    }    

    gapminder %>%
        filter(year >= input$numYear[1],
                 year <= input$numYear[2],
                     continent == input$ContinentSelect)
})

filtered_gap2 <- reactive({ 
    filtered_gap() %>% mutate(cluster_group = gapcluster(filtered_gap(), input$numCluster),
                                                                     country = reorder(country, -1 * pop)) %>%
        arrange(year, country)
})

SummaryTable <- reactive({
    if (is.null(input$ContinentSelect)) {
        return(NULL)
    } 

    filtered_gap2() %>% group_by(cluster_group) %>% summarise(`Number of countries` = n(),
                                                                                                                        `Life expectancy` = mean(lifeExp),
                                                                                                                        `Population size` = prettyNum(mean(pop), big.mark = ","),
                                                                                                                        `GDP per capita` = prettyNum(mean(gdpPercap), big.mark = ",")) %>% 
        rename(`Cluster Group` = cluster_group)
})

output$Chart <- renderPlot({
    if (is.null(filtered_gap2())) {
        return()
    }

    filtered_gap2() %>% ggplot(aes(x = gdpPercap, y = lifeExp, fill = country)) +
        scale_fill_manual(values = country_colors) +
        facet_wrap(~ cluster_group) +
        geom_point(aes(size = pop), pch = 21, show.legend = FALSE) +
        scale_x_log10(limits = c(230, 115000), labels = comma) +
        scale_size_continuous(range = c(1,40)) + ylim(c(20, 87)) + 
        labs(x = "GDP per capita", y = "Life Expectancy")
})

output$SummaryClusters <- renderTable({
    SummaryTable()
})
}

大陸のフィルタリング方法に問題があります。デフォルト設定では、合計 344 か国がテーブルに表示されていることがわかります。しかし、オセアニアのチェックを外すと、その数は 420 か国に増えます (?)。何が起こっている?問題がfilter(continent == input$ContinentSelect)server.R ファイルの行に関係していることは確かですが、修正方法がわかりません。

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