Question

我已设置以下闪亮代码：

global.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")
)
)
)

和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()
})
}

大陆的过滤方式存在问题。在默认设置中，我们可以在表中看到总共344个国家/地区。但如果我取消选中大洋洲，这个数字会上升到（420）个国家。到底是怎么回事？我确定该问题与server.R文件中的行filter(continent == input$ContinentSelect)有关，但我无法确定如何修复它。

Answer 1

当我将filter(continent == input$ContinentSelect)更改为filter(continent %in% input$ContinentSelect)时，它可以正常工作。菜鸟错误。

R Shiny - 如何按checkboxGroupInput过滤

1 个答案: