More ways to view data: plot and download

Case Studies: Building Web Applications with Shiny in R

Dean Attali

Shiny Consultant

Plot data

Plots are common first step when exploring new dataset
- Plots are outputs
- Plot output placeholder function in UI:
```
plotOutput("my_plot")
```
- Plot render function in the server:

  output$my_plot <- renderPlot({
      # code for a plot
  })

Download data

Downloading is supported using download button
- Can create any type of file to download
- image files, text files, CSV files

CSV files

Comma Separated Values
Store small-medium datasets

CSV of gapminder:

country,continent,year,lifeExp,pop,gdpPercap  
Afghanistan,Asia,1952,28.801,8425333,779.4453145  
Afghanistan,Asia,1957,30.332,9240934,820.8530296  
Afghanistan,Asia,1962,31.997,10267083,853.10071  
Afghanistan,Asia,1967,34.02,11537966,836.1971382

Create CSV file:

write.csv(gapminder, "myfile.csv")

Download data in Shiny

Download button is treated as output

Add download button to UI: (similar to output functions)

downloadButton(outputId = "download_data", 
               label = "Download data")

Add download handler in server: (similar to render functions)

output$download_data <- downloadHandler(
    filename = "data.csv",
    content = function(file) {
        # Code that creates a file in the path <file>
        write.csv(gapminder, file)
    }
)

Download handler

  output$download_data <- downloadHandler(
      filename = "data.csv",
      content = function(file) {
          # code that creates a file in the path <file>
          write.csv(gapminder, file)
      }
  )

downloadHandler() has two arguments
- filename
  - Name of downloaded file
- content(file)
  - Function with 1 argument
  - Create the file to download, argument is file path

Let's practice!

Case Studies: Building Web Applications with Shiny in R