I have a couple of ggplot plots that I want to merge using grid.arrange()
When I merge the plots there's a large white area around each plot making them far away from each other.
Is there a way to adjust the distance between the plots? and the size of the white area around the plots?
You can use theme(plot.margin) function in ggplot2 to reduce the spacing.
A simple working example here :
library(grid)
library(gridExtra)
library(ggplot2)
x <- seq(1,10,1)
y <- dnorm(x,mean=10,sd=0.5)
# Create p1
p1 <- qplot(x,y) + theme(plot.margin=unit(c(1,1,-0.5,1),"cm"))
# Create p2
p2 <- qplot(x,y) + theme(plot.margin=unit(c(-0.5,1,1,1),"cm"))
grid.arrange(p1,p2)
Edit
The four numbers are c(bottom,left,top,right)
Sample output
Related
I build a model with the lmer-fuction (m1). Now I want to plot the predicting values. I used this code:
p1 <- ggpredict(m1, "variable1")
p2 <- ggpredict(m1, "variable2")
p3 <- ggpredict(m1, "variable3")
With plot(p1) I would get the single plot as output. But I want that all three plots are visualized in one. Is there a way to overlay/combine them?
We can use patchwork to arrange multiple plots
library(patchwork)
p1|p2|p3
I'm trying to create a picture with points (actually bars, but whatever) in two distinct colours with parallel saturated-to-unsaturated colour scales, with corresponding colourbar legends. I'm most of the way there, but there are a few minor points I can't handle yet.
tl;dr the color scales I get from a red-to-white gradient and a saturated-red-to-completely-unsaturated gradient are not identical.
Set up data: y will determine both y-axis position and degree of saturation, w will determine binary colour choice.
set.seed(101)
dd <- data.frame(x=1:100,y=rnorm(100))
dd$w <- as.logical(sample(0:1,size=nrow(dd),
replace=TRUE))
Get packages:
library(ggplot2)
library(cowplot)
library(gridExtra)
I can get the plot I want by allowing alpha (transparency) to vary with y, but the legend is ugly:
g0 <- ggplot(dd,aes(x,y))+
geom_point(size=8,aes(alpha=y,colour=w))+
scale_colour_manual(values=c("red","blue"))
## + scale_alpha(guide="colourbar") ## doesn't work
I can draw each half of the points by themselves to get a legend similar to what I want:
g1 <- ggplot(dd[!dd$w,],aes(x,y))+
geom_point(size=8,aes(colour=y))+
scale_colour_gradient(low="white",high="red",name="not w")+
expand_limits(x=range(dd$x),y=range(dd$y))
g2 <- ggplot(dd[dd$w,],aes(x,y))+
geom_point(size=8,aes(colour=y))+
scale_colour_gradient(low="white",high="blue",name="w")+
expand_limits(x=range(dd$x),y=range(dd$y))
Now I can use tools from cowplot to pick off the legends and combine them with the original plot:
g1_leg <- get_legend(g1)
g2_leg <- get_legend(g2)
g0_noleg <- g0 + theme(legend.position='none')
ggdraw(plot_grid(g0_noleg,g1_leg,g2_leg,nrow=1,rel_widths=c(1,0.2,0.2)))
This is most of the way there, but:
ideally I'd like to squash the two colourbars together (I know I can probably do that with sufficient grid-hacking ...)
the colours don't quite match; the legend colours are slightly warmer than the point colours ...
Ideas? Or other ways of achieving the same goal?
What I really want to do is plot a histogram, with the y-axis on a log-scale. Obviously this i a problem with the ggplot2 geom_histogram, since the bottom os the bar is at zero, and the log of that gives you trouble.
My workaround is to use the freqpoly geom, and that more-or less does the job. The following code works just fine:
ggplot(zcoorddist) +
geom_freqpoly(aes(x=zcoord,y=..density..),binwidth = 0.001) +
scale_y_continuous(trans = 'log10')
The issue is that at the edges of my data, I get a couple of garish vertical lines that really thro you off visually when combining a bunch of these freqpoly curves in one plot. What I'd like to be able to do is use points at every vertex of the freqpoly curve, and no lines connecting them. Is there a way to to this easily?
The easiest way to get the desired plot is to just recast your data. Then you can use geom_point. Since you don't provide an example, I used the standard example for geom_histogram to show this:
# load packages
require(ggplot2)
require(reshape)
# get data
data(movies)
movies <- movies[, c("title", "rating")]
# here's the equivalent of your plot
ggplot(movies) + geom_freqpoly(aes(x=rating, y=..density..), binwidth=.001) +
scale_y_continuous(trans = 'log10')
# recast the data
df1 <- recast(movies, value~., measure.var="rating")
names(df1) <- c("rating", "number")
# alternative way to recast data
df2 <- as.data.frame(table(movies$rating))
names(df2) <- c("rating", "number")
df2$rating <- as.numeric(as.character(df$rating))
# plot
p <- ggplot(df1, aes(x=rating)) + scale_y_continuous(trans="log10", name="density")
# with lines
p + geom_linerange(aes(ymax=number, ymin=.9))
# only points
p + geom_point(aes(y=number))
What I want is as the following sketchy figure:
I'm assuming you want two intersecting lines, you can do this with geom_vline() and geom_hline()
Here's an example:
df <- data.frame(x=seq(-5,10), y=seq(-5,10))
qplot(x=x,y=y,data=df) + geom_vline(xintercept=1) + geom_hline(yintercept=1)
This makes:
You can hide the original axes from plot and draw you own with abline()
x <- rnorm(100,1)
y <- rnorm(100,1)
plot(x,y,axes=F)
abline(h=1)
abline(v=1)
I am trying to make a map with two legends denoting shape and colour ("Type" and "Org" in the example below), and have the legends inset. I can place the legends, but I would like them to be left justified so that their left edges line up. I can't make them anything other than centred with respect to each other:
require(ggplot2)
require(ggmap)
require(grid)
require(mapproj)
data <- data.frame(Org=rep(c("ABCDEFG","HIJKLMNOP","QRSTUVWX"),4)
, Type=rep(c("Y","Z"),6), Lat=runif(12,48,54.5)
, Long=runif(12,-133.5,-122.5))
osmMap <- get_map(location=c(-134,47.5,-122,55), source = 'osm')
points <- geom_jitter(data=data, aes(Long, Lat, shape=Type
, colour=Org))
legend <- theme(legend.justification=c(0,0), legend.position=c(0,0)
, legend.margin=unit(0,"lines"), legend.box="vertical"
, legend.key.size=unit(1,"lines"), legend.text.align=0
, legend.title.align=0)
ggmap(osmMap) + points + legend
This option is now available in ggplot2 0.9.3.1, use
ggmap(osmMap) + points + legend + theme(legend.box.just = "left")
Old, manual solution:
Here is a solution:
require(gtable)
require(ggplot2)
require(ggmap)
require(grid)
require(mapproj)
# Original data
data <- data.frame(Org=rep(c("ABCDEFG","HIJKLMNOP","QRSTUVWX"),4),
Type=rep(c("Y","Z"),6), Lat=runif(12,48,54.5),
Long=runif(12,-133.5,-122.5))
osmMap <- get_map(location=c(-134,47.5,-122,55), source = 'google')
points <- geom_jitter(data=data, aes(Long, Lat, shape=Type, colour=Org))
legend <- theme(legend.justification=c(0,0), legend.position=c(0,0),
legend.margin=unit(0,"lines"), legend.box="vertical",
legend.key.size=unit(1,"lines"), legend.text.align=0,
legend.title.align=0)
# Data transformation
p <- ggmap(osmMap) + points + legend
data <- ggplot_build(p)
gtable <- ggplot_gtable(data)
# Determining index of legends table
lbox <- which(sapply(gtable$grobs, paste) == "gtable[guide-box]")
# Each legend has several parts, wdth contains total widths for each legend
wdth <- with(gtable$grobs[[lbox]], c(sum(as.vector(grobs[[1]]$widths)),
sum(as.vector(grobs[[2]]$widths))))
# Determining narrower legend
id <- which.min(wdth)
# Adding a new empty column of abs(diff(wdth)) mm width on the right of
# the smaller legend box
gtable$grobs[[lbox]]$grobs[[id]] <- gtable_add_cols(
gtable$grobs[[lbox]]$grobs[[id]],
unit(abs(diff(wdth)), "mm"))
# Plotting
grid.draw(gtable)
This does not depend on Type or Org. However, this would not be enough having more than two legends. Also, in case you do some changes so that list of grobs (graphical objects) is altered, you might need to change grobs[[8]] to grobs[[i]] where i is the position of your legends, see gtable$grobs and look for TableGrob (5 x 3) "guide-box": 2 grobs.
Edit: 1. Automatically detecting which grob is legends table, i.e. no need to change anything after modifying other parts of plot. 2. Changed calculation of width differences, now code should work when having any two legends, i.e. in more complex cases as well, for example: