在ggplot 2中为两个离散变量创建百分比标签[重复]

Question

这是一些示例数据：

gender <- c("male", "female", "male", "male", "female", "female", "male", "female", "female", "male")
outcome <- factor(c(0,0,0,1,1,1,0,1,1,1), levels = c(0,1), labels = c("responders", "non-responders"))      
df <- c(gender, outcome)

我希望创建一个 ggplot，其中 y 轴是百分比，x 轴是性别，填充是结果。它必须是一个带有百分比标签的堆叠条。

在这里试过这个代码：

ggplot (df, aes (x = 性别, fill = 结果)) + geom_bar()

但这给了我 y 轴的计数。我希望在 y 轴上创建百分比。堆叠的女性条必须指示“女性组内有反应者和无反应者结果”的女性百分比，而不是总人口中有反应或没有反应的女性百分比。例如，我希望看到 40% 的女性响应者与 60% 的无响应者以及男性的类似情况。

为了准备好发布，我还需要在堆叠栏中添加这些百分比的标签。

Answer 1

这里是标签：

library(ggplot2)
gender <- c("male", "female", "male", "male", "female", "female", "male", "female", "female", "male")
outcome <- factor(c(0,0,0,1,1,1,0,1,1,1),  labels = c("responders", "non-responders"))      
df <- data.frame(gender, outcome)

ggplot(df, aes(x= gender)) + 
  geom_bar(aes(y = 2*(..count..)/sum(..count..), fill = outcome, group=outcome), stat="count") +
  geom_label(aes(label = scales::percent(2*(..count..)/sum(..count..)),
                  group = outcome), position = "fill", stat= "count", vjust = 0) +
  labs(y = "Percent", fill="outcome") +
  scale_y_continuous(labels = scales::percent)

看来@Paul 对geom_bar 有更好的办法。

编辑

这是一个通用的解决方案：

library(ggplot2)
gender <- c("female", "female", "male", "male", "female", "female", "male", "female", "female", "male")
outcome <- factor(c(0,0,0,1,1,1,0,1,1,1),  labels = c("responders", "non-responders"))      
df <- data.frame(gender, outcome)

gg <- ggplot() + 
  geom_bar(aes(x= gender, fill = outcome), data = df, position = "fill")
ggb <- ggplot_build(gg)
df2 <- data.frame(y = ggb$data[[1]][["y"]])

gg + geom_label(
  aes(x = rep(c(1,2), each = 2), label = scales::percent(y), y = y), 
  data = df2
)

Answer 2

不必更改数据的诀窍是使用geom_bar(position = "fill")，如下所述：https://stackoverflow.com/a/48602277/10264278。 要格式化 y 轴的标签，您有多种选择。以下是其中两个：

• 使用scales 包scales::percent_format()
• 改用自定义函数，只需将上面的代码替换为function(x) paste0(x*100, "%")

这里是：

gender <- c("male", "female", "male", "male", "female", "female", "male", "female", "female", "male")
outcome <- factor(c(0,0,0,1,1,1,0,1,1,1), levels = c(0,1), labels = c("responders", "non-responders"))      
df <- data.frame(gender, outcome)

library(ggplot2)
ggplot(data = df, aes(x = gender, fill = outcome)) +
  geom_bar(position="fill") +
  scale_y_continuous(labels = function(x) paste0(x*100, "%"))

^{由reprex package (v2.0.0) 于 2021-08-19 创建}

Answer 3

设法找到 Paul 和 Stéphane 发布的替代工作答案（两者都很棒）。这种方法的优点是通用性强，创建很多地块时可以节省时间。

library(dplyr)
library(ggplot2)

gender <- c("male", "female", "male", "male", "female", "female", "male", "female", "female", "male")
outcome <- factor(c(0,0,0,1,1,1,0,1,1,1), levels = c(0,1), labels = c("responders", "non-responders"))      
df <- data.frame(gender, outcome)

df %>%
  group_by(gender, outcome) %>% 
  summarise(count = n()) %>% 
  mutate(pct = round(count/sum(count), 2)) %>%
ggplot(aes(x = factor(gender), y = pct, fill = factor(outcome))) +
  geom_bar(stat="identity", width = 0.7) + scale_y_continuous(labels = scales::percent_format()) +
  labs(x = "Sex", y = "Percentage", fill = "Outcome") +
  theme_minimal(base_size = 14) +
  geom_text(aes(label=paste0(pct*100, "%")), vjust=-0.25, position=position_stack(0.5))

这是输出