Introduction

In this module we will explore several ways to generate dynamic and interactive data displays. These include making maps and graphs that you can pan/zoom, select features for more information, and interact with in other ways. The most common output format is HTML, which can easily be embedded in a website (such as your final project!).

library(dplyr)
library(ggplot2)
library(ggmap)
library(htmlwidgets)
library(widgetframe)

If you don’t have the packages above, install them in the package manager or by running install.packages("doParallel").

DataTables

DataTables display R data frames as interactive HTML tables (with filtering, pagination, sorting, and search). This is a great way to make your raw data browsable without using too much space.

library(DT)
datatable(iris, options = list(pageLength = 5))

rbokeh

Interface to the Bokeh library for making interactive graphics.

library(rbokeh)
figure(width = 400, height=400) %>%
  ly_points(Sepal.Length, Sepal.Width, data = iris,
    color = Species, glyph = Species,
    hover = list(Sepal.Length, Sepal.Width))

Leaflet

Leaflet is a really powerful JavaScript library for creating dynamic maps that support panning and zooming along with various annotations like markers, polygons, and popups. The example below were adapted from the leaflet vignettes.

library(leaflet)
geocode("Buffalo, NY")

##         lon      lat
## 1 -78.87837 42.88645

m <- leaflet() %>% setView(lng = -78.87837, lat = 42.88645, zoom = 12) %>% 
  addTiles()
frameWidget(m,height =500)

dygraphs

An R interface to the ‘dygraphs’ JavaScript charting library. Provides rich facilities for charting time-series data in R, including highly configurable series- and axis-display and interactive features like zoom/pan and series/point highlighting.

library(dygraphs)
dygraph(nhtemp, main = "New Haven Temperatures",height = 100) %>% 
  dyRangeSelector(dateWindow = c("1920-01-01", "1960-01-01"))%>%
  frameWidget(height =500)

library(rnoaa)
library(xts)

d=meteo_tidy_ghcnd("USW00014733",
                   date_min = "2016-01-01", 
                   var = c("TMAX"),
                   keep_flags=T)
d$date=as.Date(d$date)

# Convert to a xts time series object as required by dygraph
dt=xts(d$tmax,order.by=d$date)

dygraph(dt, main = "Daily Maximum Temperature in Buffalo, NY") %>% 
  dyRangeSelector(dateWindow = c("2017-01-01", "2017-12-31"))%>%
  frameWidget(height =500)

rthreejs

Create interactive 3D scatter plots, network plots, and globes using the ‘three.js’ visualization library.

#devtools::install_github("bwlewis/rthreejs")
library(threejs)
z <- seq(-10, 10, 0.1)
x <- cos(z)
y <- sin(z)
scatterplot3js(x, y, z, color=rainbow(length(z)))

networkD3

Creates ‘D3’ ‘JavaScript’ network, tree, dendrogram, and Sankey graphs from ‘R’.

library(igraph)
library(networkD3)

karate <- make_graph("Zachary")
wc <- cluster_walktrap(karate)
members <- membership(wc)

# Convert to object suitable for networkD3
karate_d3 <- igraph_to_networkD3(karate, group = members)

forceNetwork(Links = karate_d3$links, Nodes = karate_d3$nodes,
             Source = 'source', Target = 'target', NodeID = 'name',
             Group = 'group')%>%
  frameWidget(height =500)

# Load energy projection data
library(jsonlite)
URL <- paste0(
        "https://cdn.rawgit.com/christophergandrud/networkD3/",
        "master/JSONdata/energy.json")
Energy <- fromJSON(URL)

sankeyNetwork(Links = Energy$links, Nodes = Energy$nodes, Source = "source",
             Target = "target", Value = "value", NodeID = "name",
             units = "TWh", fontSize = 12, nodeWidth = 30)%>%
  frameWidget(height =500)

URL <- paste0(
        "https://cdn.rawgit.com/christophergandrud/networkD3/",
        "master/JSONdata//flare.json")

## Convert to list format
Flare <- jsonlite::fromJSON(URL, simplifyDataFrame = FALSE)

# Use subset of data for more readable diagram
Flare$children = Flare$children[1:3]

radialNetwork(List = Flare, fontSize = 10, opacity = 0.9, height = 400, width=400)

Diagonal Network

diagonalNetwork(List = Flare, fontSize = 10, opacity = 0.9, height = 400, width=400)

rglwidget

RGL provides 3D interactive graphics, including functions modelled on base graphics (plot3d(), etc.) as well as functions for constructing representations of geometric objects (cube3d(), etc.). You may need to install XQuartz.

library(rgl)
library(rglwidget)
library(htmltools)

# Load a low-resolution elevation dataset of a volcano
data(volcano)

persp3d(volcano, type="s",col="green3")
rglwidget(elementId = "example", width = 500, height = 400)%>%
  frameWidget()