loon –> ggplot via loon2ggplot()
Basic
Plot the cars ‘horsepower’ versus ‘lp100km’ (100 km per liter) on
data mtcars.
library(dplyr)
library(loon)
mt <- mtcars %>%
rename(transmission = am, weight = wt, horsepower = hp) %>%
mutate(lp100km = (100 * 3.785411784) / (1.609344 * mpg))
p <- mt %>%
with(
l_plot(horsepower, lp100km,
color = gear)
)Turn p (a loon widget) to a
ggplot object via a simple function
loon2ggplot().
The object g1 is a ggplot graphic.
Comparing with the original loon widget, the
gg one provides a legend that is helpful to decode the
mapping systems. However, since loon widgets do not store
the original data information, the labels of each legend are the
hex-codes of the color. To better convey the graphics from aesthetics to
data, we can edit the legend with more reasonable labels and add titles
on top to emphasize the variables.
g1 +
scale_fill_manual(values = c("#999999", "#A6CEE3", "#FFC0CB"),
name = "gear",
labels = c("4", "3", "5")) +
ggtitle(label = "horsepower versus lp100km",
subtitle = "loon --> ggplot") +
theme(
plot.title = element_text(color = "red", size = 12, face = "bold"),
plot.subtitle = element_text(color = "blue")
)
Comparing with static grid (via
loonGrob()), modification of ggplot (via
loon2ggplot) is simpler and more creative. Moreover,
ggplot has over 100 extended packages. After transforming
from loon to ggplot, users can continually
take advantage of these extensions.
Turn an l_compound Object to a patchwork
Object
Considering the following loon pairs plot (an
l_compound widget) with three variables ‘lp100km’ (100 km
per liter), ‘weight’ (car weight) and transmission (automatic or
manual).
mt %>%
select(lp100km, weight, transmission) %>%
# and pass the built plot on
l_pairs(showHistograms = TRUE,
linkingGroup = "Motor Trend 1974") -> # and assign the result.
l_ppIt produces an interactive pairs plot with histograms on the margins
(see ?l_pairs) and assigns the result to l_pp
(which could have been assigned at the beginning with <-
as well). Now, turn this pair plot to a gg object. Note
that the compound loon widget like l_pairs
(the shown one), l_ts or l_facet, etc, are
created by patchwork.
Features like theme, labels can be set by the
patchwork rule.
The object g2 is a patchwork object. We can
fit a smooth line on the lp100km vs weight scatterplot and
draw a density curve on the weight histogram. Additionally,
a title is added.
# Add a regression line on the `lp100km vs weight` scatterplot
g2$patches$plots[[1]] <- g2$patches$plots[[1]] +
geom_smooth(method = "lm")
# Add a density curve on the `weight` histogram
g2$patches$plots[[4]] <- g2$patches$plots[[4]] +
geom_density()
# Add a title
g2 <- g2 +
patchwork::plot_annotation(title = "Mtcars Pairs Plot")
g2