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。