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<title>Dynamic Visualization</title>

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<a href="01_Rintro.html">01 First Steps</a>

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<a href="04_Spatial_with_sf.html">04 Spatial Data with sf</a>

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<a href="11_ParallelProcessing.html">11 Parallel Processing</a>

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<a href="12_DynamicVisualization.html">12 Dynamic Visualization</a>

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<h1 class="title toc-ignore">Dynamic Visualization</h1>

</div>

<p><a href="scripts/12_DynamicVisualization.R"><i class="fa fa-file-code-o fa-3x" aria-hidden="true"></i> The R Script associated with this page is available here</a>. Download this file and open it (or copy-paste into a new script) with RStudio so you can follow along.</p>

<h1>Introduction</h1>

<p>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!).</p>

<pre class="r"><code>library(dplyr)

library(ggplot2)

library(ggmap)

library(htmlwidgets)

library(widgetframe)</code></pre>

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

</div>

<h1>DataTables</h1>

<p><a href="http://rstudio.github.io/DT/">DataTables</a> 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.</p>

<pre class="r"><code>library(DT)

datatable(iris, options = list(pageLength = 5))</code></pre>

</div>

<h1>rbokeh</h1>

<p>Interface to the <a href="http://hafen.github.io/rbokeh">Bokeh</a> library for making interactive graphics.</p>

<pre class="r"><code>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))</code></pre>

</div>

<h1>Leaflet</h1>

<p><a href="http://rstudio.github.io/leaflet/">Leaflet</a> 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 <a href="http://rstudio.github.io/leaflet">leaflet vignettes</a>.</p>

<pre class="r"><code>library(leaflet)

geocode("Buffalo, NY")</code></pre>

<pre><code>## lon lat

## 1 -78.87837 42.88645</code></pre>

<pre class="r"><code>m <- leaflet() %>% setView(lng = -78.87837, lat = 42.88645, zoom = 12) %>%

addTiles()

frameWidget(m,height =500)</code></pre>

<p>This example only scratches the surface of what is possible with leaflet. Consider whether you can use an leaflet maps in your project.</p>

<ul>

<li>Browse the <a href="http://rstudio.github.io/leaflet/">Leaflet website</a></li>

<li>What data could you use?</li>

<li>How would you display it?</li>

</ul>

</div>

<h1>dygraphs</h1>

<p>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.</p>

<pre class="r"><code>library(dygraphs)

dygraph(nhtemp, main = "New Haven Temperatures",height = 100) %>%

dyRangeSelector(dateWindow = c("1920-01-01", "1960-01-01"))%>%

frameWidget(height =500)</code></pre>

<p>Make a dygraph of recent daily maximum temperature data from Buffalo, NY.</p>

<p>Hints:</p>

<ul>

<li>Use the following code to download the daily weather data (if this is taking too long, you can use the nhtemps object loaded above)</li>

</ul>

<pre class="r"><code>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)</code></pre>

<ul>

<li>create a <code>xts</code> time series object as required by <code>dygraph()</code> using <code>xts()</code> and specify the vector of data and the date column (see <code>?xts</code> for help).</li>

<li>use <code>dygraph()</code> to draw the plot</li>

<li>add a <code>dyRangeSelector()</code> with a <code>dateWindow</code> of <code>c("2017-01-01", "2017-12-31")</code></li>

</ul>

Show Solution

</button>

<pre class="r"><code># 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)</code></pre>

</div>

<h1>rthreejs</h1>

<p>Create interactive 3D scatter plots, network plots, and globes using the <a href="https://threejs.org">‘three.js’ visualization library</a>.</p>

<pre class="r"><code>#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)))</code></pre>

</div>

<h1>networkD3</h1>

<p>Creates ‘D3’ ‘JavaScript’ network, tree, dendrogram, and Sankey graphs from ‘R’.</p>

<pre class="r"><code>library(igraph)

library(networkD3)</code></pre>

<h2>Load example network</h2>

<p>This loads an example social network of friendships between 34 members of a karate club at a US university in the 1970s. See W. W. Zachary, An information flow model for conflict and fission in small groups, Journal of Anthropological Research 33, 452-473 (1977).</p>

<pre class="r"><code>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)</code></pre>

</div>

<h2>Force directed network plot</h2>

<pre class="r"><code>forceNetwork(Links = karate_d3$links, Nodes = karate_d3$nodes,

Source = 'source', Target = 'target', NodeID = 'name',

Group = 'group')%>%

frameWidget(height =500)</code></pre>

</div>

<h2>Sankey Network graph</h2>

<p>Sankey diagrams are flow diagrams in which the width of the arrows is shown proportionally to the flow quantity.</p>

<pre class="r"><code># Load energy projection data

library(jsonlite)

URL <- paste0(

"https://cdn.rawgit.com/christophergandrud/networkD3/",

"master/JSONdata/energy.json")

Energy <- fromJSON(URL)</code></pre>

<pre class="r"><code>sankeyNetwork(Links = Energy$links, Nodes = Energy$nodes, Source = "source",

Target = "target", Value = "value", NodeID = "name",

units = "TWh", fontSize = 12, nodeWidth = 30)%>%

frameWidget(height =500)</code></pre>

</div>

<h2>Radial Network</h2>

<pre class="r"><code>URL <- paste0(

"https://cdn.rawgit.com/christophergandrud/networkD3/",

"master/JSONdata//flare.json")

## Convert to list format

Flare <- jsonlite::fromJSON(URL, simplifyDataFrame = FALSE)</code></pre>

<pre class="r"><code># 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)</code></pre>

</div>

<h1>Diagonal Network</h1>

<pre class="r"><code>diagonalNetwork(List = Flare, fontSize = 10, opacity = 0.9, height = 400, width=400)</code></pre>

</div>

<h1>rglwidget</h1>

<p>RGL provides 3D interactive graphics, including functions modelled on base graphics (<code>plot3d()</code>, etc.) as well as functions for constructing representations of geometric objects (<code>cube3d()</code>, etc.). You may need to install <a href="https://www.xquartz.org/">XQuartz</a>.</p>

<pre class="r"><code>library(rgl)

library(rglwidget)

library(htmltools)

# Load a low-resolution elevation dataset of a volcano

data(volcano)</code></pre>

<h2>Plot an interactive 3D <em>surface</em></h2>

<pre class="r"><code>persp3d(volcano, type="s",col="green3")

rglwidget(elementId = "example", width = 500, height = 400)%>%

frameWidget()</code></pre>

<p>Check out the <a href="http://gallery.htmlwidgets.org/">HTML Widgets page</a> for many more examples.</p>

<p>Which can you use in your project?</p>

</div>

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