Shiny

library(shiny)
runGitHub('ekstroem/ShinyLeastSquares')

The "role" of graphics is changing and expanding

CRANpackages <- c("MESS", "dplyr", "shiny", "plotly", "xts", "highcharter"
                  "DiagrammeR", "dygraphs", "ggplot2", "htmlwidgets",
                  "leaflet", "viridis")

install.packages(CRANpackages)

devtools::install_github('ramnathv/rCharts')

Or run

source("http://biostatistics.dk/useR2016pack.R")

HighCharter

Take the airquality dataset. Plot series of temperature and wind speed for June using for example highcharter or polychart.

data(airquality)
aq <- subset(airquality, Month==6)
head(aq)

library(highcharter)
hc <- highchart() %>%
  hc_chart(type = "column") %>%
  hc_title(text = "Denmark") %>%
  hc_xAxis(categories = aq$Day) %>% 
  hc_add_series(data = aq$Temp,
          name = "Temperature") %>%
 ...

dygraphs

Beautiful maps crated by adding layers on top of maps.

library(leaflet)

m <- leaflet() %>%
  addTiles() %>%  # Default OpenStreetMap map tiles
  addMarkers(lat=37.431106, lng=-122.164672, popup="useR 2016") 
m 

Main functions

library(leaflet)
library(MESS)

pal <- colorNumeric("RdYlBu", 
                    domain = NULL)
data(earthquakes)
m <- leaflet(subset(earthquakes,  mag>3)) %>%
  addProviderTiles("CartoDB.DarkMatter") %>%  
addCircleMarkers(
    radius = ~ mag*3,
    color  = ~ pal(depth),
    stroke = FALSE, fillOpacity = 0.4
  )
m

Create your own icon and pop-up on this map.

library(leaflet)
m <- leaflet() %>%
  addTiles() %>%  # Default OpenStreetMap map tiles
  addMarkers(lng=-122.164672, lat=37.431106, popup="useR 2016") 
m 

Add the R icon to the map: https://www.r-project.org/logo/Rlogo.png (Use icon instead of popup in addMarkers). Create simple icon:

greenLeafIcon <- makeIcon(
  iconUrl = "http://leafletjs.com/docs/images/leaf-green.png",
  iconWidth = 38, iconHeight = 95,
  iconAnchorX = 22, iconAnchorY = 94
)

Note: html/js output. Need javascript machinery to run (ie., html with js code embedded or online link).

library(htmlwidgets)
saveWidget(widget, file, selfcontained = TRUE, background="white")

Including in R markdown

htmlwidget widgets behave nicely in R markdown.

Otherwise

as.iframe to appear.

Use ggplot2 (and grammar of graphics) to render interactive graphics.

• ggplotly use the plot.ly service
• ggiraph uses it's own htmlwidget extensions.

plotly

Use legend to toggle traces, zoom, shift and click to pan. Super simple: p <- ggplot() ; ggplotly(p)

library(ggplot2)
library(plotly)

p <- ggplot(happiness, 
            aes(x=tax, y=happy, color=continent, size=population, 
                text = paste("country:", country))) + 
  geom_point( alpha = I(0.8)) + 
  scale_size_area(max_size = 30) + 
  geom_smooth(method="lm", se= F, size = 1, 
              aes(linetype = continent, group = continent))
ggplotly(p)

Works directly in R markdown / knitr

Just works (automatically embedded)

Post on plot.ly account

Embed the graph as an iframe

signup("username", "email", save=TRUE)
plotly_POST(p, "My Chart")

Extends ggplot2 with new geom functions.

• geom_point_interactive, geom_polygon_interactive, geom_map_interactive, geom_path_interactive, geom_rect_interactive, geom_segment_interactive, geom_text_interactive

Three arguments let you add interactivity:

• tooltip: mouse-over tooltips to be displayed when mouse is over elements.
• onclick: javascript function to be executed when elements are clicked.
• data_id: id to be associated with elements.

library(ggiraph)

happiness$tooltip <- paste0("<table><th>Welcome to</th><tr><td>", 
                            happiness$country, 
                            "</td></tr></table>")

p <- ggplot(happiness, 
            aes(x=tax, y=happy, color=continent, 
                size=population, tooltip=tooltip)) + 
  geom_point_interactive(alpha=I(.8)) + 
  scale_size_area(max_size = 30)

ggiraph(code = {print(p)}, height = "350px")

library(shiny)
runGitHub('ekstroem/ShinySampleMean')

"Standard" design layout with sidebar for input and main window for output.

library(shiny)

shinyUI(pageWithSidebar(
  
  titlePanel("My title"), # Application title

  sidebarLayout(          # Layout for this page
    sidebarPanel(         # Well a side bar panel
      selectInput()       # Input type
    ),  
    mainPanel(
      plotOutput()        # Types of output
    )                     # ... and main panel
  )
))

Communication through input and output lists.

library(shiny)

# Define server 
shinyServer(function(input, output) {
  
  output$something <- renderFunction( 
    v1 <- input$variable1 # Get input
    ... 
    )
})

runGitHub("ekstroem/useRapp")

Try to run the code from previous example. Add a slider to change the point size in the graph.

1. Look at the code
2. Add sliderInput (arguments: label, text, start value, min value, max value)
3. Change server function to accommodate the new input