I'm using the package patchwork to combine multiple ggplot2 plots vertically. I'd like the scales for each plot to be directly above one another, regardless of the length of the scale name. At the moment, the scales are not aligned above one another.
I'm open to using ggpubr or facet_grid() if they would make it possible, but I've seen that facets doesn't allow multiple scales, and I haven't found any solution using ggpubr
library(ggplot2)
library(patchwork)
set.seed(0)
testdata <- data.frame(x=1:10, y=1:10, col=runif(10))
g1 <- ggplot(testdata, aes(x=x,y=y,col=col)) + geom_point() +
scale_color_gradient(name="Short")
g2 <- ggplot(testdata, aes(x=x,y=y,col=col)) + geom_point() +
scale_color_gradient(name="A rather longer name")
g1/g2
ggsave("testfile.tiff", units = "mm", device="tiff",
width=100, height=100, dpi = 100)
Ideal output:
With plot_layout you can "collect" the legends. This uses as default theme(legend.position = 'right'). You can add this after plot_layout with & theme(legend.position = 'right') and adjust the position if you want to change the location of the legends.
g1/g2 + plot_layout(guides = 'collect') # & theme(legend.position = 'right') <- adjust position here!
ggsave("testfile.tiff", units = "mm", device="tiff",
width=100, height=100, dpi = 100)
I'd also be curious to learn of a patchwork parameter than could fix this, but I don't think there is one (please correct me if I'm wrong). You may have noticed that Hadley's answer is more than 10 years old and people have been working on ggplot2 since then. The ggnewscale package solves the problem of having multiple scales per plot. Here is a facetted approach using multiple colourscales:
library(ggplot2)
library(ggnewscale)
set.seed(0)
testdata <- data.frame(x=1:10, y=1:10, col=runif(10))
ggplot(mapping = aes(x = x, y, y)) +
geom_point(data = transform(testdata,
facet = factor("Top", c("Top", "Bottom"))),
aes(colour = col)) +
scale_colour_continuous(name = "Short") +
new_scale_colour() +
geom_point(data = transform(testdata,
facet = factor("Bottom", c("Top", "Bottom"))),
aes(colour = col)) +
scale_colour_continuous(name = "A rather longer name") +
facet_wrap(~ facet, ncol = 1)
Related
I want to combine these two graphs :
p1 <- ggplot(iris, aes(Sepal.Length)) +
geom_density() +
facet_wrap(~ Species)
p2 <- ggplot(iris, aes(Sepal.Length)) +
geom_density()
To combine, I do :
multiplot(p1, p2, cols = 2)
But it is not the desired shape.
I would like the graph p2 has the same dimensions than others and is situated just next to the last faceted graph.
Thanks for help
Not sure if this is applicable in you generic case, but with facet_grid instead of facet_wrap, you can use the margins argument:
library(ggplot2)
ggplot(iris, aes(Sepal.Length)) +
geom_density() +
facet_grid(. ~ Species, margins = T)
If you question is more generic the answer probably lies in grid.arrange.
Something like this could be a start:
library(gridExtra)
grid.arrange(arrangeGrob(p1, p2,
widths = c(3,1),
heights = c(1,20),
layout_matrix = matrix(c(1,1,NA,2),2)))
As you can see there are several problems (different axes, top strip), but working with grid could gets complicated quickly.
This code should work:
p1 <- ggplot(iris, aes(Sepal.Length)) +
geom_density() +
ylim(limits = c(0, 1.25))+
facet_wrap(~ Species)
p2 <- ggplot(iris, aes(Sepal.Length)) +
geom_density() +
ggtitle("") + # ad empty title as place holder
labs(y = "", x = "") + # hide axis labels
ylim(limits = c(0, 1.25)) + # y axis values should be fixed in both plots
coord_fixed(ratio=20/1) + # ratio of x- and y-axis to reduce width of plot
theme(axis.ticks.y = element_blank(), axis.text.y = element_blank(), axis.line.y = element_blank(),
plot.margin=unit(c(0,0,0.65,-10), "lines")) # margin between plots = "0.65"
I fiddled a bit and used just different styling options to produce this result. If you have more plots than this one I would recommend to use one theme for all.
You can use either the multiplot function that you are already using
multiplot(p1, p2, cols = 2)
or you install the packages gridExtra and grid and use that one:
grid.arrange(p1, p2, ncol=2)
Hope this helps!
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 have a dataset with binary variables like the one below.
M4 = matrix(sample(1:2,20*5, replace=TRUE),20,5)
M4 <- as.data.frame(M4)
M4$id <- 1:20
I have produced a stacked bar plot using the code below
library(reshape)
library(ggplot2)
library(scales)
M5 <- melt(M4, id="id")
M5$value <- as.factor(M5$value)
ggplot(M5, aes(x = variable)) + geom_bar(aes(fill = value), position = 'fill') +
scale_y_continuous(labels = percent_format())
Now I want the percentage for each field in each bar to be displayed in the graph, so that each bar reach 100%. I have tried 1, 2, 3 and several similar questions, but I can't find any example that fits my situation. How can I manage this task?
Try this method:
test <- ggplot(M5, aes(x = variable, fill = value, position = 'fill')) +
geom_bar() +
scale_y_continuous(labels = percent_format()) +
stat_bin(aes(label=paste("n = ",..count..)), vjust=1, geom="text")
test
EDITED: to give percentages and using the scales package:
require(scales)
test <- ggplot(M5, aes(x = variable, fill = value, position = 'fill')) +
geom_bar() +
scale_y_continuous(labels = percent_format()) +
stat_bin(aes(label = paste("n = ", scales::percent((..count..)/sum(..count..)))), vjust=1, geom="text")
test
You could use the sjp.stackfrq function from the sjPlot-package (see examples here).
M4 = matrix(sample(1:2,20*5, replace=TRUE),20,5)
M4 <- as.data.frame(M4)
sjp.stackfrq(M4)
# alternative colors: sjp.stackfrq(M4, barColor = c("aquamarine4", "brown3"))
Plot appearance can be custzomized with various parameters...
I really like the usage of the implicit information that is created by ggplot itself, as described in this post:
using the ggplot_build() function
From my point of view this provides a lot of opportunities to finally control the appearance of a ggplot chart.
Hope this helps somehow
Tom
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)
is there a way in ggplot2 to get the plot type "b"? See example:
x <- c(1:5)
y <- x
plot(x,y,type="b")
Ideally, I want to replace the points by their values to have something similar to this famous example:
EDIT:
Here some sample data (I want to plot each "cat" in a facet with plot type "b"):
df <- data.frame(x=rep(1:5,9),y=c(0.02,0.04,0.07,0.09,0.11,0.13,0.16,0.18,0.2,0.22,0.24,0.27,0.29,0.31,0.33,0.36,0.38,0.4,0.42,0.44,0.47,0.49,0.51,0.53,0.56,0.58,0.6,0.62,0.64,0.67,0.69,0.71,0.73,0.76,0.78,0.8,0.82,0.84,0.87,0.89,0.91,0.93,0.96,0.98,1),cat=rep(paste("a",1:9,sep=""),each=5))
Set up the axes by drawing the plot without any content.
plot(x, y, type = "n")
Then use text to make your data points.
text(x, y, labels = y)
You can add line segments with lines.
lines(x, y, col = "grey80")
EDIT: Totally failed to clock the mention of ggplot in the question. Try this.
dfr <- data.frame(x = 1:5, y = 1:5)
p <- ggplot(dfr, aes(x, y)) +
geom_text(aes(x, y, label = y)) +
geom_line(col = "grey80")
p
ANOTHER EDIT: Given your new dataset and request, this is what you need.
ggplot(df, aes(x, y)) + geom_point() + geom_line() + facet_wrap(~cat)
YET ANOTHER EDIT: We're starting to approach a real question. As in 'how do you make the lines not quite reach the points'.
The short answer is that that isn't a standard way to do this in ggplot2. The proper way to do this would be to use geom_segment and interpolate between your data points. This is quite a lot of effort however, so I suggest an easier fudge: draw big white circles around your points. The downside to this is that it makes the gridlines look silly, so you'll have to get rid of those.
ggplot(df, aes(x, y)) +
facet_wrap(~cat) +
geom_line() +
geom_point(size = 5, colour = "white") +
geom_point() +
opts(panel.background = theme_blank())
There's an experimental grob in gridExtra to implement this in Grid graphics,
library(gridExtra)
grid.newpage() ; grid.barbed(pch=5)
This is now easy with ggh4x::geom_pointpath. Set shape = NA and add a geom_text layer.
library(ggh4x)
#> Loading required package: ggplot2
df <- data.frame(x = rep(1:5, each = 5),
y = c(outer(seq(0, .8, .2), seq(0.02, 0.1, 0.02), `+`)),
cat = rep(paste0("a", 1:5)))
ggplot(df, aes(x, y)) +
geom_text(aes(label = cat)) +
geom_pointpath(aes(group = cat, shape = NA))
Created on 2021-11-13 by the reprex package (v2.0.1)
Another way to make great slope graphs is using the package CGPfunctions.
library(CGPfunctions)
newggslopegraph(newcancer, Year, Survival, Type)
You have also many options to choose. You can find a good tutorial here:
https://www.r-bloggers.com/2018/06/creating-slopegraphs-with-r/