问题
I would like the levels of two different nested grouping variables to appear on separate lines below the plot, and not in the legend. What I have right now is this code:
data <- read.table(text = \"Group Category Value
S1 A 73
S2 A 57
S1 B 7
S2 B 23
S1 C 51
S2 C 87\", header = TRUE)
ggplot(data = data, aes(x = Category, y = Value, fill = Group)) +
geom_bar(position = \'dodge\') +
geom_text(aes(label = paste(Value, \"%\")),
position = position_dodge(width = 0.9), vjust = -0.25)
What I would like to have is something like this:
Any ideas?
回答1:
You can create a custom element function for axis.text.x
.

library(ggplot2)
library(grid)
## create some data with asymmetric fill aes to generalize solution
data <- read.table(text = "Group Category Value
S1 A 73
S2 A 57
S3 A 57
S4 A 57
S1 B 7
S2 B 23
S3 B 57
S1 C 51
S2 C 57
S3 C 87", header=TRUE)
# user-level interface
axis.groups = function(groups) {
structure(
list(groups=groups),
## inheritance since it should be a element_text
class = c("element_custom","element_blank")
)
}
# returns a gTree with two children:
# the categories axis
# the groups axis
element_grob.element_custom <- function(element, x,...) {
cat <- list(...)[[1]]
groups <- element$group
ll <- by(data$Group,data$Category,I)
tt <- as.numeric(x)
grbs <- Map(function(z,t){
labs <- ll[[z]]
vp = viewport(
x = unit(t,'native'),
height=unit(2,'line'),
width=unit(diff(tt)[1],'native'),
xscale=c(0,length(labs)))
grid.rect(vp=vp)
textGrob(labs,x= unit(seq_along(labs)-0.5,
'native'),
y=unit(2,'line'),
vp=vp)
},cat,tt)
g.X <- textGrob(cat, x=x)
gTree(children=gList(do.call(gList,grbs),g.X), cl = "custom_axis")
}
## # gTrees don't know their size
grobHeight.custom_axis =
heightDetails.custom_axis = function(x, ...)
unit(3, "lines")
## the final plot call
ggplot(data=data, aes(x=Category, y=Value, fill=Group)) +
geom_bar(position = position_dodge(width=0.9),stat='identity') +
geom_text(aes(label=paste(Value, "%")),
position=position_dodge(width=0.9), vjust=-0.25)+
theme(axis.text.x = axis.groups(unique(data$Group)),
legend.position="none")
回答2:
The strip.position
argument in facet_wrap()
and switch
argument in facet_grid()
since ggplot2 2.2.0 now makes the creation of a simple version of this plot fairly straightforward via faceting. To give the plot the uninterrupted look, set the panel.spacing
to 0.
Here's the example using the dataset with a different number of Groups per Category from @agtudy's answer.
- I used
scales = "free_x"
to drop the extra Group from the Categories that don't have it, although this won't always be desirable. - The
strip.position = "bottom"
argument moves the facet labels to the bottom. I removed the strip background all together withstrip.background
, but I could see that leaving the strip rectangle would be useful in some situations. - I used
width = 1
to make the bars within each Category touch - they'd have spaces between them by default.
I also use strip.placement
and strip.background
in theme
to get the strips on the bottom and remove the strip rectangle.
The code for versions of ggplot2_2.2.0 or newer:
ggplot(data = data, aes(x = Group, y = Value, fill = Group)) +
geom_bar(stat = "identity", width = 1) +
geom_text(aes(label = paste(Value, "%")), vjust = -0.25) +
facet_wrap(~Category, strip.position = "bottom", scales = "free_x") +
theme(panel.spacing = unit(0, "lines"),
strip.background = element_blank(),
strip.placement = "outside")
You could use space= "free_x"
in facet_grid()
if you wanted all the bars to be the same width regardless of how many Groups per Category. Note that this uses switch = "x"
instead of strip.position
. You also might want to change the label of the x axis; I wasn't sure what it should be, maybe Category instead of Group?
ggplot(data = data, aes(x = Group, y = Value, fill = Group)) +
geom_bar(stat = "identity", width = 1) +
geom_text(aes(label = paste(Value, "%")), vjust = -0.25) +
facet_grid(~Category, switch = "x", scales = "free_x", space = "free_x") +
theme(panel.spacing = unit(0, "lines"),
strip.background = element_blank(),
strip.placement = "outside") +
xlab("Category")
Older code versions
The code for ggplot2_2.0.0, when this feature was first introduced, was a little different. I've saved it below for posterity:
ggplot(data = data, aes(x = Group, y = Value, fill = Group)) +
geom_bar(stat = "identity") +
geom_text(aes(label = paste(Value, "%")), vjust = -0.25) +
facet_wrap(~Category, switch = "x", scales = "free_x") +
theme(panel.margin = unit(0, "lines"),
strip.background = element_blank())
回答3:
An alternative to agstudy's method is to edit the gtable and insert an "axis" calculated by ggplot2,
p <- ggplot(data=data, aes(x=Category, y=Value, fill=Group)) +
geom_bar(position = position_dodge(width=0.9),stat='identity') +
geom_text(aes(label=paste(Value, "%")),
position=position_dodge(width=0.9), vjust=-0.25)
axis <- ggplot(data=data, aes(x=Category, y=Value, colour=Group)) +
geom_text(aes(label=Group, y=0),
position=position_dodge(width=0.9))
annotation <- gtable_filter(ggplotGrob(axis), "panel", trim=TRUE)
annotation[["grobs"]][[1]][["children"]][c(1,3)] <- NULL #only keep textGrob
library(gtable)
g <- ggplotGrob(p)
gtable_add_grobs <- gtable_add_grob # let's use this alias
g <- gtable_add_rows(g, unit(1,"line"), pos=4)
g <- gtable_add_grobs(g, annotation, t=5, b=5, l=4, r=4)
grid.newpage()
grid.draw(g)

回答4:
A very simple solution which gives a similar (though not identical) result is to use faceting. The downside is that the Category label is above rather than below.
ggplot(data=data, aes(x=Group, y=Value, fill=Group)) +
geom_bar(position = 'dodge', stat="identity") +
geom_text(aes(label=paste(Value, "%")), position=position_dodge(width=0.9), vjust=-0.25) +
facet_grid(. ~ Category) +
theme(legend.position="none")

回答5:
@agstudy already answered this question and I'm going to use it myself, but if you'd accept something uglier, but simpler, this is what I came with before his answer:
data <- read.table(text = "Group Category Value
S1 A 73
S2 A 57
S1 B 7
S2 B 23
S1 C 51
S2 C 87", header=TRUE)
p <- ggplot(data=data, aes(x=Category, y=Value, fill=Group))
p + geom_bar(position = 'dodge') +
geom_text(aes(label=paste(Value, "%")), position=position_dodge(width=0.9), vjust=-0.25) +
geom_text(colour="darkgray", aes(y=-3, label=Group), position=position_dodge(width=0.9), col=gray) +
theme(legend.position = "none",
panel.background=element_blank(),
axis.line = element_line(colour = "black"),
axis.line.x = element_line(colour = "white"),
axis.ticks.x = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank()) +
annotate("segment", x = 0, xend = Inf, y = 0, yend = 0)
Which will give us:

回答6:
Here's another solution using a package I'm working on for grouped bar charts (ggNestedBarChart):
data <- read.table(text = "Group Category Value
S1 A 73
S2 A 57
S3 A 57
S4 A 57
S1 B 7
S2 B 23
S3 B 57
S1 C 51
S2 C 57
S3 C 87", header = TRUE)
devtools::install_github("davedgd/ggNestedBarChart")
library(ggNestedBarChart)
library(scales)
p1 <- ggplot(data, aes(x = Category, y = Value/100, fill = Category), stat = "identity") +
geom_bar(stat = "identity") +
facet_wrap(vars(Category, Group), strip.position = "top", scales = "free_x", nrow = 1) +
theme_bw(base_size = 13) +
theme(panel.spacing = unit(0, "lines"),
strip.background = element_rect(color = "black", size = 0, fill = "grey92"),
strip.placement = "outside",
axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
panel.grid.major.y = element_line(colour = "grey"),
panel.grid.major.x = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_rect(color = "black", fill = NA, size = 0),
panel.background = element_rect(fill = "white"),
legend.position = "none") +
scale_y_continuous(expand = expand_scale(mult = c(0, .1)), labels = percent) +
geom_text(aes(label = paste0(Value, "%")), position = position_stack(0.5), color = "white", fontface = "bold")
ggNestedBarChart(p1)
ggsave("p1.png", width = 10, height = 5)
Note that ggNestedBarChart can group as many levels as necessary and isn't limited to just two (i.e., Category and Group in this example). For instance, using data(mtcars):
Code for this example is on the GitHub page.
来源:https://stackoverflow.com/questions/18165863/multirow-axis-labels-with-nested-grouping-variables