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Make your plot interactive

plotly is a popular package for creating interactive plots in Shiny. There are several other packages for interactive visualizations, but we will use plotly largely because of its function ggplotly(), which converts a ggplot2 plot into an interactive one.

Diese Übung ist Teil des Kurses

Case Studies: Building Web Applications with Shiny in R

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Anleitung zur Übung

The code for the Shiny app from the last exercise is provided. Your task is to replace the ggplot2 plot with a plotly plot. Specifically:

  • Load the plotly package.
  • Replace the plot output function with plotlyOutput (line 20).
  • Replace the plot render function with renderPlotly (line 29).
  • Convert the existing ggplot2 plot to a plotly plot (line 31).

Interaktive Übung

Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.

# Load the plotly package
___

ui <- fluidPage(
  sidebarLayout(
    sidebarPanel(
      textInput("title", "Title", "GDP vs life exp"),
      numericInput("size", "Point size", 1, 1),
      checkboxInput("fit", "Add line of best fit", FALSE),
      colourInput("color", "Point color", value = "blue"),
      selectInput("continents", "Continents",
                  choices = levels(gapminder$continent),
                  multiple = TRUE,
                  selected = "Europe"),
      sliderInput("years", "Years",
                  min(gapminder$year), max(gapminder$year),
                  value = c(1977, 2002))
    ),
    mainPanel(
      # Replace the `plotOutput()` with the plotly version
      plotOutput("plot")
    )
  )
)

# Define the server logic
server <- function(input, output) {
  # Replace the `renderPlot()` with the plotly version
  output$plot <- renderPlot({
    # Convert the existing ggplot2 to a plotly plot
    ___({
      data <- subset(gapminder,
                     continent %in% input$continents &
                       year >= input$years[1] & year <= input$years[2])
      
      p <- ggplot(data, aes(gdpPercap, lifeExp)) +
        geom_point(size = input$size, col = input$color) +
        scale_x_log10() +
        ggtitle(input$title)
      
      if (input$fit) {
        p <- p + geom_smooth(method = "lm")
      }
      p
    })
  })
}

shinyApp(ui = ui, server = server)
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