1. Interactive Data Visualizations using R and ggvis
6 April 2018
McGill Library Research Commons
Presented by Zia D. and Mike G.

2. Outline Loading data into RStudio Introduction and basics of ggvis
Lines & Syntax
Interactivity and Layers
Customizing Axes, Legends, Scales
Mapping

3. Required R Libraries > install.packages("ggvis")
> library(ggvis)
> library(dplyr)

4. Loading your data set #set working directory > setwd(“c:/r_data”)
#verify working directory
> getwd()
#load the .csv into a variable named hospital_data
> hospital_data <- read.csv(“quebec_hospital_data_subset.csv”)
#if problems loading CSV
hospital_data <- read.csv(“quebec_hospital_data_subset.csv”, fileEncoding="latin1")

5. Verify that the data has loaded correctly
#view data headers
> names(hospital_data)
This should reproduce the following:

6. Convert textual data to numeric
This code converts the data in each column from textual to numeric
#as.numeric for columns 1, 6, 7, 8
> hospital_data[, 1] <- as.numeric(hospital_data[, 1])
> hospital_data[, 6] <- as.numeric(hospital_data[, 6])
> hospital_data[, 7] <- as.numeric(hospital_data[, 7])
> hospital_data[, 8] <- as.numeric(hospital_data[, 8])

7. Grammar of Graphics + + + Underlying structure of ggvis Data
Coordinate
System
Marks
Properties + + +

8. Basics
#formula
<data> %>% ggvis(~x, ~y, properties) %>% layer_<marks>(properties)
#pipe operator (from library dpylr)
%>%

9. Lines & Syntax
#graph hospitals against proportion of series as a scatterplot
> hospital_data %>%
ggvis(~Proportion, ~Installation) %>%
layer_points()
#change mark
layer_lines()
layer_bars()
layer_ribbons()
layer_smooths()

10. Visual Properties #change properties >hospital_data %>%
ggvis(~Proportion, ~Installation,
fill := “blue”, size := 100, shape := “square”) %>%
layer_points()
ggvis(~Proportion, ~Installation) %>%
layer_points(fill := “red”, size := 50, shape := “diamond”)
#some other properties: stroke, strokeWidth, opacity, fillOpacity, strokeOpacity, fill.hover

11. Visual Properties #map property to a variable >hospital_data %>%
ggvis(~Proportion, ~Installation, fill = ~Région) %>%
layer_points()
ggvis(~Proportion, ~Installation) %>%
layer_points(fill = ~Région)

12. Interactivity #adding sliders >hospital_data %>%
ggvis(~Proportion, ~Installation,
size := input_slider(10, 100),
opacity := input_slider(0, 1)) %>%
layer_points()

13. Layers Two layer types: simple and compound
Simple represent basic geometric shapes like lines, points and triangles
Compound represent data transformations along with one or more simple layers

14. Simple layer #scatter plot > hospital_data %>%
ggvis(~Proportion, ~Installation,
stroke = “red”) %>%
layer_points()

15. Compound layers layer_lines() - order by the x variable
layer_smooths() - fits a smooth model to the data, and displays predictions in a line

16. Layer_smooths example
#highlights the trend in noisy data
> hospital_data %>%
ggvis(~Région, ~Nombre.de.visites.totales) %>%
layer_smooths()
#interactive version
> span <- input_slider(1, 5, value=1)
hospital_data %>%
layer_smooths(span = span)

17. Customizing axes #create a simple scatter plot and rename x-axis
>hospital_data %>%
ggvis(~Installation, ~Proportion) %>%
layer_points() %>%
add_axis("x", title = "Hospital names")

18. Other axis options > add_axis("x", title = "Hospital Names",
ticks = 40,
properties = axis_props(ticks = list(stroke = "red"),
majorTicks = list(strokeWidth = 2),
grid = list(stroke = "red"),
labels = list(fill = "steelblue", angle = 50,
fontSize = 14, align = "left"),
title = list(fontSize = 16)))
> add_axis “x”, title = “Title Name”, title_offset = 50

19. Customizing legends #add_legend
> add_legend(vis, scales = NULL, orient = "right", title = NULL, format = NULL, values = NULL, properties = NULL) hide_legend(vis, scales)
#legend_props
> legend_props(title = NULL, labels = NULL, symbols = NULL, gradient = NULL, legend = NULL)

20. add_legend examples #add_legend one variable > hospital_data %>%
ggvis(~Nombre.de.visites.totales, ~Proportion, fill = ~Installation) %>%
layer_points() %>%
add_legend("fill", title="Custom name")
#add_legend two variables
>hospital_data %>%
ggvis(~Nombre.de.visites.totales, ~Proportion, fill = ~Installation, size = “Nombre.de.visites.P4.et.P5) %>%
add_legend(c( "fill", "size"))

21. Further legend customization
>hospital_data %>%
ggvis(~Nombre.de.visites.totales, ~Proportion, fill = ~Installation) %>%
layer_points() %>%
add_legend("fill", title = "Cylinders", properties = legend_props(title = list(fontSize = 16), labels = list(fontSize = 12, fill = "#00F"), gradient = list(stroke = "red", strokeWidth = 2), legend = list(x = 500, y = 50)))

22. Mapping data - Quebec Admin Boundaries Shapefile
Libraries: rgdal, rgeos
> montreal_map <- readOGR("c:/r_data", "DistrictElect")
> montreal_wgs84 <- spTransform(montreal_map, CRS
("+proj=longlat +datum=WGS84"))
> plot(montreal_wgs84, axes=TRUE)

23. Plot data onto shapefile
>plot(montreal_wgs84)
>points(hospital_data$Longitude, hospital_data$Latitude, col="blue", pch=19)

24. Further documentation
RStudio ggvis 0.4 overview
CPAN documentation