我使用了以下ggplot命令:

ggplot(survey, aes(x = age)) + stat_bin(aes(n = nrow(h3), y = ..count.. / n), binwidth = 10)
  + scale_y_continuous(formatter = "percent", breaks = c(0, 0.1, 0.2))
  + facet_grid(hospital ~ .)
  + theme(panel.background = theme_blank())

生产

然而,我想将facet标签更改为更短的内容(如Hosp 1, Hosp 2…),因为它们现在太长了,看起来很局促(增加图形的高度不是一个选项,它将占用文档中的太多空间)。我查看了facet_grid帮助页面,但不知道如何操作。


当前回答

添加另一个类似于@domi的解决方案,解析数学符号、上标、下标、圆括号/方括号等。

library(tidyverse)
theme_set(theme_bw(base_size = 18))

### create separate name vectors
# run `demo(plotmath)` for more examples of mathematical annotation in R
am_names <- c(
  `0` = "delta^{15}*N-NO[3]^-{}",
  `1` = "sqrt(x,y)"
)

# use `scriptstyle` to reduce the size of the parentheses &
# `bgroup` to make adding `)` possible 
cyl_names <- c(
  `4` = 'scriptstyle(bgroup("", a, ")"))~T~-~5*"%"',
  `6` = 'scriptstyle(bgroup("", b, ")"))~T~+~10~degree*C',
  `8` = 'scriptstyle(bgroup("", c, ")"))~T~+~30*"%"'
)

ggplot(mtcars, aes(wt, mpg)) + 
  geom_jitter() +
  facet_grid(am ~ cyl,
             labeller = labeller(am  = as_labeller(am_names,  label_parsed),
                                 cyl = as_labeller(cyl_names, label_parsed))
             ) +
  geom_text(x = 4, y = 25, size = 4, nudge_y = 1,
            parse = TRUE, check_overlap = TRUE,
            label = as.character(expression(paste("Log"["10"], bgroup("(", frac("x", "y"), ")")))))

### OR create new variables then assign labels directly
# reverse facet orders just for fun
mtcars <- mtcars %>% 
  mutate(am2  = factor(am,  labels = am_names),
         cyl2 = factor(cyl, labels = rev(cyl_names), levels = rev(attr(cyl_names, "names")))
  )

ggplot(mtcars, aes(wt, mpg)) + 
  geom_jitter() +
  facet_grid(am2 ~ cyl2,
             labeller = label_parsed) +
  annotate("text", x = 4, y = 30, size = 5,
           parse = TRUE, 
           label = as.character(expression(paste("speed [", m * s^{-1}, "]"))))

由reprex包于2019-03-30创建(v0.2.1.9000)

其他回答

下面是我如何使用2.2.1版本的ggplot2使用facet_grid(yfacet~xfacet):

facet_grid(
    yfacet~xfacet,
    labeller = labeller(
        yfacet = c(`0` = "an y label", `1` = "another y label"),
        xfacet = c(`10` = "an x label", `20` = "another x label")
    )
)

请注意,这里不包含对as_labeller()的调用——这一点我曾纠结过一段时间。

这种方法的灵感来自帮助页面上的最后一个示例强制到标签器函数。

facet_wrap和facet_grid都接受ifelse作为参数的输入。因此,如果用于刻面的变量是合乎逻辑的,解决方案非常简单:

facet_wrap(~ifelse(variable, "Label if true", "Label if false"))

如果变量有更多类别,则需要嵌套ifelse语句。

作为一个副作用,这也允许在ggplot调用中创建分面组。

从米沙巴利亚辛来的一条航线 :

facet_grid(。~vs, labeller = purrr::partial(label_both, sep = " #"))

看看它的实际应用

library(reprex)
library(tidyverse)

mtcars %>% 
  ggplot(aes(x="", y=gear,fill=factor(gear), group=am)) +
  geom_bar(stat="identity", width=1) +
  coord_polar("y", start=0) +
  facet_grid(.~vs, labeller = purrr::partial(label_both, sep = " #"))

由reprex包于2021-07-09创建(v2.0.0)

用变量,值作为参数的标签函数定义不适合我。另外,如果你想使用表达式,你需要使用lapply,而不能简单地使用arr[val],因为函数的参数是data.frame。

这段代码确实有效:

libary(latex2exp)
library(ggplot2)
arr <- list('virginica'=TeX("x_1"), "versicolor"=TeX("x_2"), "setosa"=TeX("x_3"))
mylabel <- function(val) { return(lapply(val, function(x) arr[x])) }
ggplot(iris, aes(x=Sepal.Length, y=Sepal.Width)) + geom_line() + facet_wrap(~Species, labeller=mylabel)

只是延续了"淘气101 "的答案,功劳归他

plot_labeller <- function(variable,value, facetVar1='<name-of-1st-facetting-var>', var1NamesMapping=<pass-list-of-name-mappings-here>, facetVar2='', var2NamesMapping=list() )
{
  #print (variable)
  #print (value)
  if (variable==facetVar1) 
    {
      value <- as.character(value)
      return(var1NamesMapping[value])
    } 
  else if (variable==facetVar2) 
    {
      value <- as.character(value)
      return(var2NamesMapping[value])
    } 
  else 
    {
      return(as.character(value))
    }
}

你要做的就是创建一个名称到名称映射的列表

clusteringDistance_names <- list(
  '100'="100",
  '200'="200",
  '300'="300",
  '400'="400",
  '600'="500"
)

用新的默认参数重新定义plot_labeller():

plot_labeller <- function(variable,value, facetVar1='clusteringDistance', var1NamesMapping=clusteringDistance_names, facetVar2='', var1NamesMapping=list() )

然后:

ggplot() + 
  facet_grid(clusteringDistance ~ . , labeller=plot_labeller) 

或者,您可以为您想要的每个标签更改创建一个专用函数。