Context
I want to plot two ggplot2 on the same page with the same legend. http://code.google.com/p/gridextra/wiki/arrangeGrob discribes, how to do this. This already looks good. But... In my example I have two plots with the same x-axis and different y-axis. When the range of the the y-axis is at least 10 times higher than of the other plot (e.g. 10000 instead of 1000), ggplot2 (or grid?) does not align the plots correct (see Output below).
Question
How do I also align the left side of the plot, using two different y-axis?
Example Code
x = c(1, 2)
y = c(10, 1000)
data1 = data.frame(x,y)
p1 <- ggplot(data1) + aes(x=x, y=y, colour=x) + geom_line()
y = c(10, 10000)
data2 = data.frame(x,y)
p2 <- ggplot(data2) + aes(x=x, y=y, colour=x) + geom_line()
# Source: http://code.google.com/p/gridextra/wiki/arrangeGrob
leg <- ggplotGrob(p1 + opts(keep="legend_box"))
legend=gTree(children=gList(leg), cl="legendGrob")
widthDetails.legendGrob <- function(x) unit(3, "cm")
grid.arrange(
p1 + opts(legend.position="none"),
p2 + opts(legend.position="none"),
legend=legend, main ="", left = "")
Output
A cleaner way of doing the same thing but in a more generic way is by using the formatter arg:
p1 <- ggplot(data1) +
aes(x=x, y=y, colour=x) +
geom_line() +
scale_y_continuous(formatter = function(x) format(x, width = 5))
Do the same for your second plot and make sure to set the width >= the widest number you expect across both plots.
1. Using cowplot package:
library(cowplot)
plot_grid(p1, p2, ncol=1, align="v")
2. Using tracks from ggbio package:
Note: There seems to be a bug, x ticks do not align. (tested on 17/03/2016, ggbio_1.18.5)
library(ggbio)
tracks(data1=p1,data2=p2)
If you don't mind a shameless kludge, just add an extra character to the longest label in p1, like this:
p1 <- ggplot(data1) +
aes(x=x, y=y, colour=x) +
geom_line() +
scale_y_continuous(breaks = seq(200, 1000, 200),
labels = c(seq(200, 800, 200), " 1000"))
I have two underlying questions, which I hope you'll forgive if you have your reasons:
1) Why not use the same y axis on both? I feel like that's a more straight-forward approach, and easily achieved in your above example by adding scale_y_continuous(limits = c(0, 10000)) to p1.
2) Is the functionality provided by facet_wrap not adequate here? It's hard to know what your data structure is actually like, but here's a toy example of how I'd do this:
library(ggplot2)
# Maybe your dataset is like this
x <- data.frame(x = c(1, 2),
y1 = c(0, 1000),
y2 = c(0, 10000))
# Molten data makes a lot of things easier in ggplot
x.melt <- melt(x, id.var = "x", measure.var = c("y1", "y2"))
# Plot it - one page, two facets, identical axes (though you could change them),
# one legend
ggplot(x.melt, aes(x = x, y = value, color = x)) +
geom_line() +
facet_wrap( ~ variable, nrow = 2)
Related
This question already has an answer here:
draw straight line between any two point when using coord_polar() in ggplot2 (R)
(1 answer)
Closed 2 years ago.
I am making a polar violin plot. I would like to add lines and labels to the plot to annotate what each spoke means.
I'm running into two problems.
The first is that when I try to create line segments, if x != xend, then the segments are drawn as curves rather than as lines.
For example:
data.frame(
x = rnorm(1000),
spoke = factor(sample(1:6, 1000, replace=T))
) %>%
ggplot(aes(x = spoke, fill=spoke, y = x)) +
geom_violin() +
coord_polar() +
annotate("segment", x=1.1, xend=1.3, y=0, yend=3, color="black", size=0.6) +
theme_minimal()
The second problem that arises occurs when I try to add an annotation between the last spoke and the first. In this case, the annotation causes the coordinate scale to shift, so that spokes are no longer evenly distributed.
See as here:
data.frame(
x = rnorm(1000),
spoke = factor(sample(1:5, 1000, replace=T))
) %>%
ggplot(aes(x = spoke, fill=spoke, y = x)) +
geom_violin() +
coord_polar() +
scale_x_discrete(limits = 1:5) +
annotate("segment", x=5.9, xend=5.7, y=0, yend=3, color="black", size=0.6) +
theme_minimal()
Any assistance is greatly appreciated!
(PS: I do understand that there are perceptual issues with plots like these. I have a good reason...)
You want an 'generic annotation' as shown here
You basically have to overlay your plots and not use the layer facility, if you don't want to exactly calculate the distance in radians of each x for each y.
With cowplot
require(ggplot2) #again, you should specify your required packages in your question as well
require(cowplot)
my_dat <- data.frame(x = rnorm(1000),
spoke = factor(sample(1:6, 1000, replace=T)))
my_annot <- data.frame(para = c('start','end'), x = c(0,0.4), y = c(0,0.2))
#first point x/y = c(0,0) because this makes positioning easier
When I edited your question and removed the piping - that was not only a matter of good style, but also makes it much easier to then work with your different plots. So - I would suggest you should remove the pipe.
p1 <- ggplot(my_dat, aes(x = spoke, fill=spoke, y = x)) +
geom_violin() +
theme_minimal()+
coord_polar()
p2 <- ggplot(my_annot) +
geom_line(aes(x,y)) +
coord_cartesian(xlim = c(0,2), ylim =c(0,2)) +
# the limits change the length of your line too
theme_void()
ggdraw() +
draw_plot(p1) +
draw_plot(p2, x = 0.55, y = 0.6)
Obviously - you can now play around with both length of your line and its position within draw_plot()
I have a plot with three different lines. I want one of those lines to have points on as well. I also want the two lines without points to be thicker than the one without points. I have managed to get the plot I want, but I the legend isn't keeping up.
library(ggplot2)
y <- c(1:10, 2:11, 3:12)
x <- c(1:10, 1:10, 1:10)
testnames <- c(rep('mod1', 10), rep('mod2', 10), rep('meas', 10))
df <- data.frame(testnames, y, x)
ggplot(data=df, aes(x=x, y=y, colour=testnames)) +
geom_line(aes(size=testnames)) +
scale_size_manual("", values=c(0.5,1,1)) +
geom_point(aes(alpha=testnames), size=5, shape=4) +
scale_alpha_manual("", values=c(1, 0, 0))
I can remove the second (black) legend:
ggplot(data = df, aes(x=x, y=y, colour=testnames)) +
geom_line(aes(size=testnames)) +
scale_size_manual("", values=c(0.5,1,1), guide='none') +
geom_point(aes(alpha=testnames), size=5, shape=4) +
scale_alpha_manual("", values=c(1, 0.05, 0.05), guide='none')
But what I really want is a merge of the two legends - a legend with colours, cross only on the first variable (meas) and the lines of mod1 and mod2 thicker than the first line. I have tried guide and override, but with little luck.
You don't need transparency to hide the shapes for mod1 and mod2. You can omit these points from the plot and legend by setting their shape to NA in scale_shape_manual:
ggplot(data = df, aes(x = x, y = y, colour = testnames, size = testnames)) +
geom_line() +
geom_point(aes(shape = testnames), size = 5) +
scale_size_manual(values=c(0.5, 2, 2)) +
scale_shape_manual(values=c(8, NA, NA))
This gives the following plot:
NOTE: I used some more distinct values in the size-scale and another shape in order to better illustrate the effect.
Is there any way to line up the points of a line plot with the bars of a bar graph using ggplot when they have the same x-axis? Here is the sample data I'm trying to do it with.
library(ggplot2)
library(gridExtra)
data=data.frame(x=rep(1:27, each=5), y = rep(1:5, times = 27))
yes <- ggplot(data, aes(x = x, y = y))
yes <- yes + geom_point() + geom_line()
other_data = data.frame(x = 1:27, y = 50:76 )
no <- ggplot(other_data, aes(x=x, y=y))
no <- no + geom_bar(stat = "identity")
grid.arrange(no, yes)
Here is the output:
The first point of the line plot is to the left of the first bar, and the last point of the line plot is to the right of the last bar.
Thank you for your time.
Extending #Stibu's post a little: To align the plots, use gtable (Or see answers to your earlier question)
library(ggplot2)
library(gtable)
data=data.frame(x=rep(1:27, each=5), y = rep(1:5, times = 27))
yes <- ggplot(data, aes(x = x, y = y))
yes <- yes + geom_point() + geom_line() +
scale_x_continuous(limits = c(0,28), expand = c(0,0))
other_data = data.frame(x = 1:27, y = 50:76 )
no <- ggplot(other_data, aes(x=x, y=y))
no <- no + geom_bar(stat = "identity") +
scale_x_continuous(limits = c(0,28), expand = c(0,0))
gYes = ggplotGrob(yes) # get the ggplot grobs
gNo = ggplotGrob(no)
plot(rbind(gNo, gYes, size = "first")) # Arrange and plot the grobs
Edit To change heights of plots:
g = rbind(gNo, gYes, size = "first") # Combine the plots
panels <- g$layout$t[grepl("panel", g$layout$name)] # Get the positions for plot panels
g$heights[panels] <- unit(c(0.7, 0.3), "null") # Replace heights with your relative heights
plot(g)
I can think of (at least) two ways to align the x-axes in the two plots:
The two axis do not align because in the bar plot, the geoms cover the x-axis from 0.5 to 27.5, while in the other plot, the data only ranges from 1 to 27. The reason is that the bars have a width and the points don't. You can force the axex to align by explicitly specifying an x-axis range. Using the definitions from your plot, this can be achieved by
yes <- yes + scale_x_continuous(limits=c(0,28))
no <- no + scale_x_continuous(limits=c(0,28))
grid.arrange(no, yes)
limits sets the range of the x-axis. Note, though, that the alginment is still not quite perfect. The y-axis labels take up a little more space in the upper plot, because the numbers have two digits. The plot looks as follows:
The other solution is a bit more complicated but it has the advantage that the x-axis is drawn only once and that ggplot makes sure that the alignment is perfect. It makes use of faceting and the trick described in this answer. First, the data must be combined into a single data frame by
all <- rbind(data.frame(other_data,type="other"),data.frame(data,type="data"))
and then the plot can be created as follows:
ggplot(all,aes(x=x,y=y)) + facet_grid(type~.,scales = "free_y") +
geom_bar(data=subset(all,type=="other"),stat="identity") +
geom_point(data=subset(all,type=="data")) +
geom_line(data=subset(all,type=="data"))
The trick is to let the facets be constructed by the variable type which was used before to label the two data sets. But then each geom only gets the subset of the data that should be drawn with that specific geom. In facet_grid, I also used scales = "free_y" because the two y-axes should be independent. This plot looks as follows:
You can change the labels of the facets by giving other names when you define the data frame all. If you want to remove them alltogether, then add the following to your plot:
+ theme(strip.background = element_blank(), strip.text = element_blank())
I would like two separate plots. I am using them in different frames of a beamer presentation and I will add one line to the other (eventually, not in example below). Thus I do not want the presentation to "skip" ("jump" ?) from one slide to the next slide. I would like it to look like the line is being added naturally. The below code I believe shows the problem. It is subtle, but not how the plot area of the second plot is slightly larger than of the first plot. This happens because of the y axis label.
library(ggplot2)
dfr1 <- data.frame(
time = 1:10,
value = runif(10)
)
dfr2 <- data.frame(
time = 1:10,
value = runif(10, 1000, 1001)
)
p1 <- ggplot(dfr1, aes(time, value)) + geom_line() + scale_y_continuous(breaks = NULL) + scale_x_continuous(breaks = NULL) + ylab(expression(hat(z)==hat(gamma)[1]*time+hat(gamma)[4]*time^2))
print(p1)
dev.new()
p2 <- ggplot(dfr2, aes(time, value)) + geom_line() + scale_y_continuous(breaks = NULL) + scale_x_continuous(breaks = NULL) + ylab(".")
print(p2)
I would prefer to not have a hackish solution such as setting the size of the axis label manually or adding spaces on the x-axis (see one reference below), because I will use this technique in several settings and the labels can change at any time (I like reproducibility so want a flexible solution).
I'm searched a lot and have found the following:
Specifying ggplot2 panel width
How can I make consistent-width plots in ggplot (with legends)?
https://groups.google.com/forum/#!topic/ggplot2/2MNoYtX8EEY
How can I add variable size y-axis labels in R with ggplot2 without changing the plot width?
They do not work for me, mainly because I need separate plots, so it is not a matter of aligning them virtically on one combined plot as in some of the above solutions.
haven't tried, but this might work,
gl <- lapply(list(p1,p2), ggplotGrob)
library(grid)
widths <- do.call(unit.pmax, lapply(gl, "[[", "widths"))
heights <- do.call(unit.pmax, lapply(gl, "[[", "heights"))
lg <- lapply(gl, function(g) {g$widths <- widths; g$heights <- heights; g})
grid.newpage()
grid.draw(lg[[1]])
grid.newpage()
grid.draw(lg[[2]])
How about using this for p2:
p2 <- ggplot(dfr2, aes(time, value)) + geom_line() +
scale_y_continuous(breaks = NULL) +
scale_x_continuous(breaks = NULL) +
ylab(expression(hat(z)==hat(gamma)[1]*time+hat(gamma)[4]*time^2)) +
theme(axis.title.y=element_text(color=NA))
This has the same label as p1, but the color is NA so it doesn't display. You could also use color="white".
I've become quite fond of boxplots in which jittered points are overlain over the boxplots to represent the actual data, as below:
set.seed(7)
l1 <- gl(3, 1, length=102, labels=letters[1:3])
l2 <- gl(2, 51, length=102, labels=LETTERS[1:2]) # Will use this later
y <- runif(102)
d <- data.frame(l1, l2, y)
ggplot(d, aes(x=l1, y=y)) +
geom_point(position=position_jitter(width=0.2), alpha=0.5) +
geom_boxplot(fill=NA)
(These are particularly helpful when there are very different numbers of data points in each box.)
I'd like to use this technique when I am also (implicitly) using position_dodge to separate boxplots by a second variable, e.g.
ggplot(d, aes(x=l1, y=y, colour=l2)) +
geom_point(position=position_jitter(width=0.2), alpha=0.5) +
geom_boxplot(fill=NA)
However, I can't figure out how to dodge the points by the colour variable (here, l2) and also jitter them.
Here is an approach that manually performs the jittering and dodging.
# a plot with no dodging or jittering of the points
dp <- ggplot(d, aes(x=l1, y=y, colour=l2)) +
geom_point(alpha=0.5) +
geom_boxplot(fill=NA)
# build the plot for rendering
foo <- ggplot_build(dp)
# now replace the 'x' values in the data for layer 1 (unjittered and un-dodged points)
# with the appropriately dodged and jittered points
foo$data[[1]][['x']] <- jitter(foo$data[[2]][['x']][foo$data[[1]][['group']]],amount = 0.2)
# now draw the plot (need to explicitly load grid package)
library(grid)
grid.draw(ggplot_gtable(foo))
# note the following works without explicitly loading grid
plot(ggplot_gtable(foo))
I don't think you'll like it, but I've never found a way around this except to produce your own x values for the points. In this case:
d$l1.num <- as.numeric(d$l1)
d$l2.num <- (as.numeric(d$l2)/3)-(1/3 + 1/6)
d$x <- d$l1.num + d$l2.num
ggplot(d, aes(l1, y, colour = l2)) + geom_boxplot(fill = NA) +
geom_point(aes(x = x), position = position_jitter(width = 0.15), alpha = 0.5) + theme_bw()
It's certainly a long way from ideal, but becomes routine pretty quickly. If anyone has an alternative solution, I'd be very happy!
The new position_jitterdodge() works for this. However, it requires the fill aesthetic to tell it how to group points, so you have to specify a manual fill to get uncolored boxes:
ggplot(d, aes(x=l1, y=y, colour=l2, fill=l2)) +
geom_point(position=position_jitterdodge(width=0.2), alpha=0.5) +
geom_boxplot() + scale_fill_manual(values=rep('white', length(unique(l2))))
I'm using a newer version of ggplot2 (ggplot2_2.2.1.9000) and I was struggling to find an answer that worked for a similar plot of my own. #John Didon's answer produced an error for me; Error in position_jitterdodge(width = 0.2) : unused argument (width = 0.2). I had previous code that worked with geom_jitter that stopped working after downloading the newer version of ggplot2. This is how I solved it below - minimal-fuss code....
ggplot(d, aes(x=l1, y=y, colour=l2, fill=l2)) +
geom_point(position = position_jitterdodge(dodge.width = 1,
jitter.width = 0.5), alpha=0.5) +
geom_boxplot(position = position_dodge(width = 1), fill = NA)
Another option would be to use facets:
set.seed(7)
l1 <- gl(3, 1, length=102, labels=letters[1:3])
l2 <- gl(2, 51, length=102, labels=LETTERS[1:2]) # Will use this later
y <- runif(102)
d <- data.frame(l1, l2, y)
ggplot(d, aes(x=l1, y=y, colour=l2)) +
geom_point(position=position_jitter(width=0.2), alpha=0.5) +
geom_boxplot(fill=NA) +
facet_grid(.~l2) +
theme_bw()
Sorry, don´t have enough points to post the resulting graph.