Package loon
provides
the truly direct manipulation and package ggplot
provides a
unified data structure so that it is easy to be extended. Data analysts
who explore data interactively can at any time turn a snapshot of their
interactive loon
plots into ggplot
s by the
simple translation function loon2ggplot()
.
In loon
, the current view of any loon
plot
p
can be turned into a grid
plot in a variety
of ways:
plot(p)
grid.loon(p)
or
grid.loon(p, draw = FALSE)
loonGrob(p)
to create the grid object.The corresponding grid
object is a rich structure that
can be exported, printed, edited, and incorporated into other
grid
structures. However, adapting that structure to
slightly different presentations is a bit of a challenge compared to a
ggplot
(also ultimately a grid
structure).
In this section, we turn the current state of any loon
plot into a ggplot
plot which can then be modified
following the rules of the ggplot2
grammar.
loon2ggplot()
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.
l_compound
Object to a patchwork
ObjectConsidering 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_pp
It 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
loon.ggplot()
loon.ggplot()
function in loon.ggplot
package is an S3
method and gathers features of both
loon2ggplot()
and ggplot2loon()
. It can take
either a loon
widget or gg
object and
transform back and forth.
Loon
to ggplot
:
loon.ggplot(loon)
is equivalent to
loon2ggplot(loon)
.
See the vignette A Grammar of Interactive Graphics
for
more.