## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----setup, warning = FALSE, message = FALSE----------------------------------
library(PieGlyph)
library(ggplot2)
library(ggiraph)
library(dplyr)
library(cowplot)
## -----------------------------------------------------------------------------
set.seed(737)
plot_data <- data.frame(response = rnorm(15, 100, 30),
system = 1:15,
group = sample(size = 15, x = c('G1', 'G2', 'G3'), replace = T),
A = round(runif(15, 3, 9), 2),
B = round(runif(15, 1, 5), 2),
C = round(runif(15, 3, 7), 2),
D = round(runif(15, 1, 9), 2))
## ----data_subset--------------------------------------------------------------
head(plot_data)
## ----basic_plot, fig.align='center', fig.width=6, fig.height=5----------------
# Same ggplot call as the static version
gg_obj <- ggplot(data = plot_data, aes(x = system, y = response)) +
# geom_pie_interactive instead of geom_pie_glyph
geom_pie_interactive(slices = c("A", "B", "C", "D"),
colour = "black") +
scale_fill_brewer(palette = "Dark2") +
theme_classic(base_size = 16)
# Pass the ggplot object to the girafe function to create the interactive plot
girafe(ggobj = gg_obj)
## ----custom_tooltip, fig.align='center', fig.width=6, fig.height=5------------
gg_obj <- ggplot(data = plot_data, aes(x = system, y = response)) +
# specify tooltip aesthetic
# wrapped in paste0 to add more descriptive text to the tooltip
geom_pie_interactive(aes(tooltip = paste0("Group: ", group)),
slices = c("A", "B", "C", "D"),
colour = "black") +
scale_fill_brewer(palette = "Dark2") +
theme_classic(base_size = 16)
# Pass the ggplot object to the girafe function to create the interactive plot
girafe(ggobj = gg_obj)
## ----onclick, fig.align='center', fig.width=6, fig.height=5-------------------
gg_obj <- ggplot(data = plot_data, aes(x = system, y = response)) +
# specify onclick aesthetic
geom_pie_interactive(aes(
onclick = "alert(\"This observation belongs to group \" +
this.getAttribute(\"data-id\"))"),
slices = c("A", "B", "C", "D"),
colour = "black") +
scale_fill_brewer(palette = "Dark2") +
theme_classic(base_size = 16)
# Pass the ggplot object to the girafe function to create the interactive plot
girafe(ggobj = gg_obj)
## ----data_id, fig.align='center', fig.width=6, fig.height=5-------------------
gg_obj <- ggplot(data = plot_data, aes(x = system, y = response)) +
# specify data_id aesthetic
geom_pie_interactive(aes(data_id = group),
slices = c("A", "B", "C", "D"),
colour = "black") +
scale_fill_brewer(palette = "Dark2") +
theme_classic(base_size = 16)
# Pass the ggplot object to the girafe function to create the interactive plot
girafe(ggobj = gg_obj)
## ----customisation, fig.align='center', fig.width=6, fig.height=5-------------
# Reuse the previous gg_obj
girafe(ggobj = gg_obj,
options = list(
# Options for formatting the appearance of the tooltip
# The tooltip will have a blue background with white text
opts_tooltip = opts_tooltip(css = "background-color:blue;color:white;padding:5px"),
# Options for changing animation of observations which are hovered
# Hovered pie-glyph will be highlighted yellow with dark grey border
opts_hover(css = "fill:yellow;stroke:darkgrey;"),
# Options for changing properties of the pie-glyphs not selected
# Make non-selected pie-glyphs fade into background
opts_hover_inv(css = "opacity:0.25;"),
# Options for panning and zooming
# Set max to a number greater than 1 and tooltip will appear on
# top right giving options for panning and zooming across the plot
opts_zoom(max = 3)
))
## ----single-selection, fig.align='center', fig.width=6, fig.height=5----------
# Add a unique identifier for each observertion
plot_data$id <- 1:nrow(plot_data)
gg_obj <- ggplot(data = plot_data, aes(x = system, y = response)) +
# specify data_id as a unique identifier for each observation
geom_pie_interactive(aes(data_id = id),
slices = c("A", "B", "C", "D"),
colour = "black") +
scale_fill_brewer(palette = "Dark2") +
theme_classic(base_size = 16)
girafe(ggobj = gg_obj,
options = list(
# Options for selecting observations
# only_shiny = FALSE is needed to see selections in page
opts_selection(type = "multiple",
only_shiny = FALSE),
# Panning and zooming
opts_zoom(max = 3)
))
## ----multi-selection, fig.align='center', fig.width=9, fig.height=5-----------
# Lets first add two more variables to our data
set.seed(373)
plot_data <- plot_data %>%
mutate(response2 = round(rnorm(15, 100, 30), 2),
system2 = round(runif(15, 5, 20), 2))
gg_obj1 <- ggplot(data = plot_data, aes(x = system, y = response)) +
# specify data_id as a unique identifier for each observation
geom_pie_interactive(aes(data_id = id),
slices = c("A", "B", "C", "D"),
colour = "black") +
scale_fill_brewer(palette = "Dark2") +
theme_classic(base_size = 16) +
theme(legend.position = "top")
gg_obj2 <- ggplot(data = plot_data, aes(x = system2, y = response2)) +
# specify data_id as a unique identifier for each observation
geom_pie_interactive(aes(data_id = id),
slices = c("A", "B", "C", "D"),
colour = "black") +
scale_fill_brewer(palette = "Dark2") +
labs(x = "Another system", y = "Another response") +
theme_classic(base_size = 16) +
theme(legend.position = "top")
girafe(ggobj = cowplot::plot_grid(gg_obj1, gg_obj2,
nrow = 1),
options = list(
# Options for selecting observations
# only_shiny = FALSE is needed to see selections in page
opts_selection(type = "multiple",
only_shiny = FALSE)
))
## ----interactive-geoms, fig.align='center', fig.width=8, fig.height=5---------
gg_obj <- ggplot(data = plot_data, aes(x = system, y = response)) +
# Simple theme for plot
theme_classic(base_size = 16) +
# Title for plot
labs(title = "This is a plot with each component being interactive") +
# Interactive pie-glyphs
geom_pie_interactive(aes(data_id = id),
slices = c("A", "B", "C", "D"),
colour = "black") +
# Interactive version of facet_wrap.
# Use labeller_interactive for the interactive strips
facet_wrap_interactive(vars(group), nrow = 1,
labeller = labeller_interactive(
aes(tooltip = paste0("Group: ", group),
data_id = group)
)
) +
# Interactive version of scale_fill_manual
# Specify he tooltip and data_id attributes for the legend keys
# Use labeller_interactive for making legend title interactive
scale_fill_manual_interactive(values = c("#1B9E77", "#D95F02",
"#7570B3", "#E7298A"),
name = label_interactive(
"Attributes",
tooltip = "Interactive legend title",
data_id = "legend.title",
onclick = "alert(\"You clicked the legend title.\")"
),
tooltip = function(x) paste0("Attribute: ", x),
data_id = function(x) x) +
# Interactive elements in the theme
# Use element_text_interactive for the axis title, axis text and plot title
theme(legend.position = "top",
axis.title = element_text_interactive(
data_id = "axis.title",
tooltip = "Axis title",
onclick = "alert(\"You clicked the axis title.\")",
hover_css = "fill:red;stroke:none;"
),
axis.text = element_text_interactive(
data_id = "axis.text",
tooltip = "Axis text",
onclick = "alert(\"You clicked the axis text\")",
hover_css = "fill:red;stroke:none;"
),
plot.title = element_text_interactive(
data_id = "plot.title",
tooltip = "Plot title",
onclick = "alert(\"You clicked the plot title\")",
hover_css = "fill:blue;stroke:black;"
))
girafe(ggobj = gg_obj)