r - 如何向闪亮的应用程序添加多个图表？

Question

我试图弄清楚如何将多个图表添加到我闪亮的应用程序中。下面是我在主页上的闪亮应用程序的代码。

library(shiny)
library(markdown)
library(DT)
library(ggplot2)
library(dplyr)
library(plotly)
library(shinythemes)

happiness2015 <- read.csv("2015.csv", stringsAsFactors = TRUE)
happiness2016 <- read.csv("2016.csv", stringsAsFactors = TRUE)
happiness2017 <- read.csv("2017.csv", stringsAsFactors = TRUE)
happiness2018 <- read.csv("2018.csv", stringsAsFactors = TRUE)
happiness2019 <- read.csv("2019.csv", stringsAsFactors = TRUE)
countries_all <- read.csv("countries.csv", stringsAsFactors = TRUE)



# Define UI for application that draws a histogram
ui <- navbarPage(
    theme = shinytheme("readable"),
    title = "World Happiness",
    tabPanel("Plot",
             sidebarPanel(width = 3,
                          br(),
                          span("Data from ", 
                               tags$a("World Happiness Report.", href = "http://worldhappiness.report")),
                          br(), hr(),
                          helpText("Select year"),
                          actionButton("button2015", "2015"),
                          actionButton("button2016", "2016"),
                          actionButton("button2017", "2017"),
                          actionButton("button2018", "2018"),
                          actionButton("button2019", "2019"),
                          br(), br(), 
                          helpText("Choose variables"),
                          uiOutput("variable_1"),
                          uiOutput("variable_2"),
                          br(),
                          helpText("Press command to see multiple countries"),
                          uiOutput("country"),
                          br(), hr(),
                          span("Data source:", 
                               tags$a("Kaggle",
                                      href = "https://www.kaggle.com/unsdsn/world-happiness")),
                          br(), br(),
                          em(

                              span("Code", a(href = "https://github.com/raishamdahya/INFO281", "on GitHub"))
                          )),

             mainPanel(
                 tabsetPanel(
                     tabPanel("Plot",
                              br(),
                              h2(textOutput("year_name_plot")),
                              plotlyOutput("scatterplot", 
                                           height = 800)
                     ),

                     tabPanel("Table", 
                              br(),
                              DT::dataTableOutput("results_table")
                     ),

                     tabPanel(textOutput("tab_name_rankings"),
                              h1(textOutput("year_name")),
                              h2("Top 10"),
                              wellPanel( 
                                  dataTableOutput("rank_table_top")),
                              br(), 
                              h2("Bottom 10"),
                              wellPanel(
                                  dataTableOutput("rank_table_bottom"))
                     )
                 )
             )),

    tabPanel("About"))





##############################################
### SERVER STARTS HERE #######################
##############################################

server <- function(input, output, session) {

    output$variable_1 <- renderUI({
        selectInput("variable_1", "Y-variable:", 
                    choices = c("Happiness.Rank", "Happiness.Score", "Economy", 
                                "Family", "Health", "Freedom", "Government.Corruption", 
                                "Generosity", "Dystopia.Residual"), selected = "Happiness.Score")
    })


    output$variable_2 <- renderUI({
        selectInput("variable_2", "X-variable:", 
                    choices = c("Happiness.Rank", "Happiness.Score", "Economy", 
                                "Family", "Health", "Freedom", "Government.Corruption", 
                                "Generosity", "Dystopia.Residual"), selected = "Economy")
    })


    data_year <- reactiveValues(data = happiness2015, year = "2015")


    observeEvent(input$button2015, {
        data_year$data <- happiness2015
        year <- "2015"
    })


    observeEvent(input$button2016, {
        data_year$data <- happiness2016
        data_year$year <- "2016"
    })

    observeEvent(input$button2017, {
        data_year$data <- happiness2017
        data_year$year <- "2017"
    })

    observeEvent(input$button2018, {
        data_year$data <- happiness2018
        data_year$year <- "2018"
    })

    observeEvent(input$button2019, {
        data_year$data <- happiness2019
        data_year$year <-  "2019"
    })


    filtered_data <- reactive({
        data_year$data %>% 
            filter(Country %in% c(input$country)) %>% 
            arrange(Country)
    })


    output$year_name_plot <- renderText({ 
        paste("Data for ", data_year$year) 
    })


    countries <- reactive({ 
        df_small <- 
            countries_all %>% 
            select(Country) %>% 
            droplevels()

        c("Select All", levels(df_small$Country))

    })


    output$country <- renderUI ({

        selectInput("country", "Countries:", 
                    multiple = TRUE,
                    choices = countries(), 
                    selected = "Select All",
                    selectize = FALSE,
                    size = 10)
    })


    observe({
        if ("Select All" %in% input$country) {
            # choose all the choices _except_ "Select All"
            selected_choices <- setdiff(countries(), "Select All")
            updateSelectInput(session, "country", selected = selected_choices)
        }
    })


    output$scatterplot <- renderPlotly({
        if (is.null(data_year$data)) return()

        p <- ggplot(filtered_data()) +
            geom_point(aes_string(x = input$variable_2, y = input$variable_1, 
                                  colour = "Region", label = "Country"), size = 3) +
            ggtitle(paste0(input$variable_1, " vs. ", input$variable_2)) +
            theme_bw() +
            theme(legend.position = "bottom")

        ggplotly(p, tooltip = c("label", "x", "y"), height = 500) 
    })


    output$results_table <- DT::renderDataTable({
        if (is.null(data_year$data)) {
            return()
        } else {
            filtered_data()
        }
    },
    options = list(lengthChange = FALSE, 
                   scrollCollapse = TRUE,
                   scrollX = "100%"),
    selection = "single"
    )


    output$tab_name_rankings <- renderText({ 
        paste("Happiness Ranking: ", data_year$year) 
    })


    output$year_name <- renderText({ 
        paste("Happiness Ranking in ", data_year$year) 
    })


    output$rank_table_top <- DT::renderDataTable({
        if (is.null(data_year$data)) {
            return()
        } else {
            data_year$data %>% 
                mutate(Rank = Happiness.Rank) %>% 
                arrange(Rank) %>% 
                top_n(10, desc(Rank))
        }
    },
    options = list(lengthChange = FALSE,
                   scrollX = "100%")
    )


    output$rank_table_bottom <- DT::renderDataTable({
        if (is.null(data_year$data)) {
            return()
        } else {
            data_year$data %>% 
                mutate(Rank = Happiness.Rank) %>% 
                arrange(Rank) %>% 
                top_n(10, Rank)
        }
    },

    options = list(lengthChange = FALSE, 
                   scrollX = "100%")
    )

}

# Run the application 
shinyApp(ui = ui, server = server)

我正在尝试将以下情节图添加到页面：

这是 2 个图表的代码：

#read files
worklife<-read.csv('satisfaction-with-job-and-work-life-balance-(%)-by-usual-hours-worked,-2018.csv')
wellbeingmeasure<-read.csv('-average-rating-of-selected-wellbeing-measures-for-new-zealanders,-2018_19.csv')

colnames(worklife)
colnames(wellbeingmeasure)

ggplot(worklife, aes(x = Work.life.balance, y = Job.satisfaction)) +
  geom_point(aes(color = factor(Usual.hours.worked.in.main.job)))

ggplot(wellbeingmeasure, aes(x = Average.Rating, y = Selected.wellbeing.measures)) + geom_point()

library(plotly)

p1 <- plot_ly(data = worklife, x = ~Work.life.balance, y = ~Job.satisfaction, color = ~Usual.hours.worked.in.main.job)
p1

p2 <- plot_ly(data = wellbeingmeasure, x = ~Average.Rating, y = ~Selected.wellbeing.measures)
p2

对此的任何帮助表示赞赏。如何将上述代码添加到我的闪亮应用程序中？

标签： rshinyshinydashboardshinyapps