I'd like to add a footnote citation to my 3-panel facet grid plot produced in R. It's a footnote to credit the data source. I'd ideally like to have it below and external to all three axes---preferably in the lower left.
I'm using ggplot2 and also ggsave(). This means I can't use grid.text()-based solutions, because that only draws on the x11() window, and can't be added to the ggplot object.
Using instead png() ...code... dev.off() does not appear to be an option because I need ggsave's resizing parameters, and find this command produces better, clearer prints (that are also much faster, because I'm not printing to the screen).
Here's my basic code:
p1 <- ggplot(data, aes(date, value))
facet_grid(variable ~ .) + geom_point(aes(y =value), size=1) +
theme_bw() +
opts(title=mytitle)
print(p1)
ggsave("FILE.png",width=mywidth, height=myheight, p1, dpi=90)
I've tried:
p1 <- ggplot(data, aes(date, value))
facet_grid(variable ~ .) + geom_point(aes(y =value), size=1) +
theme_bw() +
opts(title=mytitle)
print(p1)
grid.text(unit(0.1,"npc"),0.025,label = "Data courtesy of Me")
grid.gedit("GRID.text", gp=gpar(fontsize=7))
ggsave("FILE.png",width=mywidth, height=myheight, p1, dpi=90)
This appropriately puts the footnote in the lower left corner on the x11() display, external to the plots, but unfortunately, since it isn't applied to the p1 object, it isn't saved by the ggsave command.
I've also tried:
p1 <- ggplot(data, aes(date, value))
facet_grid(variable ~ .) + geom_point(aes(y =value), size=1) +
theme_bw() +
opts(title=mytitle) +
annotate("text", label = "Footnote", x = 0, y = 10, size = 5, colour = "black") +
print(p1)
ggsave("FILE.png",width=mywidth, height=myheight, p1, dpi=90)
This successfully prints using ggsave, however it has the following problems:
It is repeated 3 times, in each of the 3 facets, rather than 1 time.
It is contained within the plots, rather than external to them.
Text is difficult to place---seems to be using plot units (my x-axis is date, so 0 puts it around 1970).
The text size doesn't seem to change despite my size parameter.
A couple of related links from when I explored this...
ggplot2 footnote
(doesn't work with ggsave)
How to label the barplot in ggplot with the labels in another test result?
(is inside the plot, not external/below plot)
Different font faces and sizes within label text entries in ggplot2
(doesn't work with ggsave)
problem saving pdf file in R with ggplot2
ggplot2 now has this ability natively with no need for additional packages. ... + labs(caption = "footnote", ...)
library(ggplot2)
ggplot(diamonds, aes(carat, price, color = clarity)) +
geom_point() +
labs(title = "Diamonds are forever...",
subtitle = "Carat weight by Price",
caption = "H. Wickham. ggplot2: Elegant Graphics for Data Analysis Springer-Verlag New York, 2009.")
library(gridExtra)
library(grid)
library(ggplot2)
g <- grid.arrange(qplot(1:10, 1:10, colour=1:10) + labs(caption="ggplot2 caption"),
bottom = textGrob("grid caption", x = 1,
hjust = 1, gp = gpar(fontface = 3L, fontsize = 9)))
ggsave("plot.pdf", g)
Edit: note that this solution is somewhat complementary to the recent caption argument added to ggplot2, since the textGrob can here be aligned with respect to the whole figure, not just the plot panel.
Adding to the answer of Brandon Bertelsen: if you want to have the caption in the left corner, add
theme(plot.caption = element_text(hjust = 0))
Related
I'm attempting to write some code that can be used to make boxplots of temperatures at which proteins melt at, I'm 99% there except I need to introduce a line break on the y-axis of my boxplot.
Essentially, my current y axis scale goes from 45-60, I want to make the y axis start at 0, line break, 45-60. See the picture as an e.g.
I've tried using the scale_y_continuous to set a break but that didn't work as I'd hoped.
df %>%
group_by(Protein) %>%
ggplot(., aes(x = factor(Protein), y = Melting_Temperature)) +
geom_boxplot() +
theme_classic() +
geom_point(aes(x = as.numeric(df$Protein) + 0.5, colour = Protein),
alpha=0.7)+
xlab("Protein Type")+
ylab("Melting Temperature") +
stat_summary(fun.y=mean, colour = "darkred", geom = "point", shape =
18, size = 3, show_guide = FALSE) +
geom_text(data = means, aes(label = round(Melting_Temperature, 1), y =
Melting_Temperature + 0.5))
IMHO, tick marks and axis labels should be sufficient to indicate the range of data on display. So, there is no need to start an axis at 0 (except for bar charts and alike).
However, the package ggthemes offers Tufte style axes which might be an alternative to the solution the OP is asking for:
library(ggplot2)
library(ggthemes)
ggplot(iris) +
aes(x = Species, y = Sepal.Length) +
geom_boxplot() +
geom_rangeframe() +
theme_tufte(base_family = "")
Note that the iris dataset is used here in place of OP's data which are not available.
geom_rangeframe() plots axis lines which extend to the maximum and minimum of the plotted data. As the plot area is usually somewhat larger this creates a kind of gap.
theme_tufte() is a theme based on Chapter 6 "Data-Ink Maximization and Graphical Design" of Edward Tufte's The Visual Display of Quantitative Information with no border, no axis lines, and no grids.
This is not supported in ggplot as built. In this discussion from 2010, Hadley Wickham (author of ggplot as well as RStudio et al) explains that axis breaks are questionable practice in his view.
Those comments by Hadley are linked, and other options discussed, in this prior SO discussion.
I have 4 ggplot objects with quite a few elements making the individual plots taking a long time to load, but they do finish adding all elements when I load them individually.
I want all the 4 plots in the same plot, which I do using grid.arrange
When I run each element individually (saving the plots, then run the grid.arrange() line alone, the plot gets rendered as expected. However, when I run my full script with ctrl+alt+R, I only get the first plot, a bit of the second plot.
Is it possible to increase the time limit so that the script can finish making the plot?
data<- data.frame(c(1,2,3),c(4,5,6))
plot1 <- plot2 <- plot3 <- plot4 <- data %>%
ggplot(aes(x = .[,1], y = .[,2])) +
geom_text_repel(label = rownames(data)) +
geom_point(color = "blue") +
theme_bw() +
ggtitle("data title") +
labs(x = "xlabel", y = "ylabel") +
geom_vline(xintercept = 0)+
geom_hline(yintercept = 0)
grid.arrange(plot1, plot2, plot3, plot4, ncol = 2)
a<- menu(c("yes","no"), title="Make a choice")
The solution to this problem was to add a pause(0.1) between grid.arrange and menu
I wanted to add significant stars over 3 facets to compare them.
I google online but it is so complicated to add things outside plot. There is a ggsignif package but it does nothing to facets (https://github.com/const-ae/ggsignif/issues/22). It seems possible using gridExtra but I cannot make it.
The stars can be draw easily in a single plot, not facets. But I have to use facets to have separate rugs on the left. If you know how to have separate rugs inside a single plot, it should also solve the problem.
Here is the code and plot I want to add things on:
library(ggplot2)
ToothGrowth$dose = factor(ToothGrowth$dose)
ggplot(ToothGrowth, aes(x='', y=len, color=dose)) +
geom_boxplot() +
geom_rug(sides="l") +
facet_grid(. ~ dose)
What I want is:
Sorry for the drawing. The line width should be the same. The final result should be really similar to this but for facets:
This is a workaround - plot two plots (one for significance annotation, another for boxplots).
library(ggplot2)
library(ggsignif)
ToothGrowth$dose <- factor(ToothGrowth$dose)
Plot significance annotation. Don't use boxplot here and set tips to 0 (using only one comparison here as others return error from statistical test, but I'm assuming that this is only an example dataset).
p1 <- ggplot(ToothGrowth, aes(as.factor(dose), len)) +
geom_signif(comparisons = list(c("1", "2")), tip_length = 0.005) +
coord_cartesian(ylim = c(35, 35.5)) +
theme_void()
Plot boxplots with different x axis (need this to specify comparisons groups in ggsignif)
p2 <- ggplot(ToothGrowth, aes(factor(dose), len)) +
geom_boxplot() +
geom_rug(sides = "l") +
facet_grid(. ~ dose, scales = "free_x") +
labs(x = NULL) +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank())
Draw plots together geom_signif on-top of geom_boxplot with facet_wrap
egg::ggarrange(p1, p2, heights = c(2, 10))
I am having trouble with excessively wide panel labels on my ggplot2 faceted plot.
Here is the code that I used to generate the plot:
png(paste("/directory/", hgnc_symbol, "_", curr_gene, ".png", sep=""),
width=4, height=3, units="in", pointsize=1, res=300)
print({barplot <-
ggplot(curr_data, aes(x = condition, y = tpm, fill=condition)) +
geom_boxplot(outlier.colour=NA, lwd=0.2, color="grey18") +
stat_boxplot(geom ='errorbar', color="grey18") +
geom_jitter(size=0.8) +
facet_wrap(~target_id) +
guides(fill=FALSE) +
theme_bw() +
labs(title=paste(hgnc_symbol, "_", curr_gene, sep="")) +
labs(x="condition") + labs(y="TPM") +
theme(text = element_text(size=5), strip.background=element_rect(size = 1),
axis.text.x = element_text(angle = 90, hjust = 1, size=4.5))})
dev.off()
The plot comes out looking like this:
As you can see, the background of the panel labels is so wide, that the plots themselves are barely visible. The points plotted on the graph are also much larger than I expected them to be.
The odd thing is that I used this same exact code to produce this following plot (which looks good) just a few days ago:
What is causing this difference, and how can I fix the problem?
In ggplot, text is defined in pts, which are absolute units of measure. The plot panel is relative in size and scales according to the dimensions you specify when you save your plot. If the dimensions are small, then the text will be large relative to the panel areas. If the dimensions are large, then the text will be small relative to the panel areas. See examples below:
ggplot(diamonds, aes(x = x, y =y)) + geom_point() + facet_wrap(~ clarity)
ggsave("filepath//4x3.png", width=4, height = 3)
ggsave("filepath//8x6.png", width=8, height = 6)
The 4 x 3 in plot:
The 8 x 6 in plot:
You can edit the grobs to exert finer control on the plot dimensions (example).
How can I have a section of the legend with only one category? I tried to mess with the override.aes without sucess. Alternatively, the desired output could be seen as a legend with only the shape but not the scale.
ggplot(iris) +
geom_point(aes(x=Sepal.Width, y=Sepal.Length, color=Species, size=Sepal.Length))+
scale_size_continuous("Legend with \n only 1 circle ",range = c(5,10))+
guides(size = guide_legend( override.aes=list(range= c(1,5))))
An illustration of the type of product I am trying to get to:
Points are scaled but the legend does not report the scale.
Just create one break in the scale. You can add a custom label to it as well (here it is ""). You can also control the size of the point in the legend with the break you choose.
The scale_color_discrete() line is there because otherwise the 1-point legend would be on top, not what you had in your desired picture.
require(ggplot2)
g <- ggplot(iris) + geom_point(aes(x = Sepal.Width, y = Sepal.Length,
color = Species, size = Sepal.Length)) +
scale_color_discrete(name = "Color") +
scale_size_continuous(name = "Legend with \n only 1 circle",
breaks = 5, labels = "")
Although #choff solution is the best solution for the example I gave, here is the slightly different one I ended up using as I needed to have control over the range size of the circles.
ggplot(iris) +
geom_point(aes(x=Sepal.Width, y=Sepal.Length, color=Species, size=Sepal.Length))+
scale_size_continuous("Legend with \n only 1 circle ",range = c(5,10), labels=c("","","","",""))+
guides(size =guide_legend( override.aes=list(size=c(4,0,0)))) +
theme(legend.key = element_blank())
From your target map chart, it looks like you want your legend to separate your chart symbols by color and shape. Size used only to set the size of the symbols. Also, your data would likely have a column for separately countries with investments from those without. So we can add a column to iris which separates the rows by two values, map color and shape to that column, and then display the legend for those two aesthetics in a single, combined legend. The code looks like:
sp <- ggplot(transform(iris, Flower_size = ifelse(Petal.Width < 1, "Small Flower","Big Flower")))
sp <- sp + geom_point(aes(x=Sepal.Width, y=Sepal.Length, fill=Flower_size, shape=Flower_size, size=Sepal.Length), colour=NA)
sp <- sp + scale_size_continuous(range = c(4,7))
sp <- sp + scale_shape_manual(values=c(21, 22))
sp <- sp + scale_fill_manual(values=c("grey", "orange"))
sp <- sp + labs(fill="", shape="")
sp <- sp + guides(size=FALSE, fill=guide_legend(override.aes=list(size=7)))
sp <- sp + theme(legend.text=element_text(size=12))
plot(sp)