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

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)

其他回答

我觉得我应该加上我的答案,因为我花了很长时间才做到这一点:

这个答案是为你准备的:

您不想编辑原始数据 如果你需要表达式(bquote)在标签和 如果您想要单独的标签名称-向量的灵活性

我基本上把标签放在一个命名向量中,这样标签就不会混淆或切换。标签器表达式可能更简单,但这至少是可行的(非常欢迎改进)。注意'(后引号)以保护facet-factor。

n <- 10
x <- seq(0, 300, length.out = n)

# I have my data in a "long" format
my_data <- data.frame(
  Type = as.factor(c(rep('dl/l', n), rep('alpha', n))),
  T = c(x, x),
  Value = c(x*0.1, sqrt(x))
)

# the label names as a named vector
type_names <- c(
  `nonsense` = "this is just here because it looks good",
  `dl/l` = Linear~Expansion~~Delta*L/L[Ref]~"="~"[%]", # bquote expression
  `alpha` = Linear~Expansion~Coefficient~~alpha~"="~"[1/K]"
  )


ggplot() + 
  geom_point(data = my_data, mapping = aes(T, Value)) + 
  facet_wrap(. ~ Type, scales="free_y", 
             labeller = label_bquote(.(as.expression(
               eval(parse(text = paste0('type_names', '$`', Type, '`')))
               )))) +
  labs(x="Temperature [K]", y="", colour = "") +
  theme(legend.position = 'none')

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)

你试过改变医院载体的具体水平吗?

levels(survey$hospital)[levels(survey$hospital) == "Hospital #1"] <- "Hosp 1"
levels(survey$hospital)[levels(survey$hospital) == "Hospital #2"] <- "Hosp 2"
levels(survey$hospital)[levels(survey$hospital) == "Hospital #3"] <- "Hosp 3"

在不修改底层数据的情况下进行更改的最简单方法是:

使用as_labeller()创建一个对象。如果列名以数字开头,或者包含空格或特殊字符,不要忘记使用反标记:

# Necessary to put RH% into the facet labels
hum_names <- as_labeller(
     c(`50` = "RH% 50", `60` = "RH% 60",`70` = "RH% 70", 
       `80` = "RH% 80",`90` = "RH% 90", `100` = "RH% 100"))

在ggplot中添加:

    ggplot(dataframe, aes(x = Temperature.C, y = fit)) + 
        geom_line() + 
        facet_wrap(~Humidity.RH., nrow = 2, labeller = hum_names)

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。