Just another ggplot2 and knitr extension package.
This package contains functions primarily in these domains of ggplot2:
As well as some functions in knitr.
# install.packages("devtools")
# Install release from GitHub:
devtools::install_github("stefanedwards/lemon", ref='v0.3.1')
# Or get the lastest development version from GitHub:
devtools::install_github("stefanedwards/lemon")
We can display a limit on the axes range.
library(lemon)
ggplot(mtcars, aes(x=cyl, y=mpg)) +
geom_point() +
coord_capped_cart(bottom='both', left='none') +
theme_light() + theme(panel.border=element_blank(), axis.line = element_line())
NB: Disable panel.border
and enable axis.line
in theme
, otherwise you will not see an effect!
We could also show that the x-axis is categorical (or ordinal):
(p <- ggplot(mtcars, aes(x=as.factor(cyl), y=mpg)) +
geom_point(position=position_jitter(width=0.1)) +
coord_flex_cart(bottom=brackets_horisontal(), left=capped_vertical('both')) +
theme_light() + theme(panel.border=element_blank(), axis.line = element_line())
)
When capping the axis lines, they are never capped further inwards than the ticks! Look up
coord_capped_cart
,coord_capped_flip
coord_flex_cart
,coord_flex_flip
,coord_flex_fixed
brackets_horisontal
,brackets_vertical
capped_horisontal
,capped_vertical
Having produced such wonderous axes, it is a pity they are not plotted around all panels when using faceting. We have extended both facet_grid
and facet_wrap
to produce axis, ticks, and labels on all panels:
p + facet_rep_wrap(~gear, ncol=2, label=label_both)
They work just like the normal ones; look up facet_rep_grid
and facet_rep_wrap
.
A geom that combines both points and lines. While possible by using both geom_point
and geom_line
, position adjustments are not preserved between the two layers. geom_pointline
and geom_pointpath
combines geom_point
with geom_line
and geom_path
, respectively, while preserving position adjustments.
Left:
geom_point
and geom_line
as two separate geoms. Right: The two geoms combined into geom_pointline
. Both produced with ggplot(mtcars, aes(wt, mpg, colour=factor(cyl))) + geom_point(col='grey')
, where the grey points indicate the true location of the datapoint.
An added visual effect is seen as the lines do not touch the points, leaving a small gap (set by argument distance
).
Reposition the legend onto the plot. Exactly where you want it:
dsamp <- diamonds[sample(nrow(diamonds), 1000), ]
d <- ggplot(dsamp, aes(carat, price)) +
geom_point(aes(colour = clarity))
reposition_legend(d, 'top left')
The legend repositioned onto the top left corner of the panel.
Scavenging the Internet, we have found some functions that help work with legends.
Frequently appearing on Stack Overflow, we bring you g_legend
:
library(grid)
legend <- g_legend(d)
grid.newpage()
grid.draw(legend)
Originally brought to you by (Baptiste Auguiรฉ)[http://baptiste.github.io/] (https://github.com/tidyverse/ggplot2/wiki/Share-a-legend-between-two-ggplot2-graphs) and (Shaun Jackman)[http://rpubs.com/sjackman] (http://rpubs.com/sjackman/grid_arrange_shared_legend). We put it in a package.
dsamp <- diamonds[sample(nrow(diamonds), 1000), ]
p1 <- qplot(carat, price, data = dsamp, colour = clarity)
p2 <- qplot(cut, price, data = dsamp, colour = clarity)
p3 <- qplot(color, price, data = dsamp, colour = clarity)
p4 <- qplot(depth, price, data = dsamp, colour = clarity)
grid_arrange_shared_legend(p1, p2, p3, p4, ncol = 2, nrow = 2)
Four plots that share the same legend.
knitr
allows S3 methods for knit_print
for specialised printing of objects. We provide lemon_print
for data frames, dplyr tables, and summary objects, that can be used to render the output, without mucking up the code source. An added benefit is that we can use RStudio's inline data frame viewer:
Using knitr
for computations that use external binaries and/or write temporary files, setting the root directory for knitr
's knitting saves the user from a file mess. E.g.
knitr::opts_knit$set(root.dir=TMPDIR)
But we want to keep our file paths relative for the scripts / document to be transferable. We introduce the .dot
functions:
TMPDIR=tempdir()
.data <- .dot('data')
knitr_opts_knit$set(root.dir=TMPDIR)
We can then load our data file using the created .data
function, even though the chunk is executed from TMPDIR.
dat <- read.table(.data('mydata.tab'))