ggplot：显示启用了类的每个bin的计数

Question

我正在尝试绘制一个直方图，其中每个垃圾箱的总数都在顶部。 以下是我的数据：

您可以使用以下示例数据：

histData <- data.frame("UserId" = 1:20, "age" = c(replicate(20,sample(10:20,20,rep=TRUE))), "Gender" = c("Male", "Female"))

我正在使用ggplot，如下所示：

ggplot(histData, aes(x = age, color = Gender, fill = Gender)) +
  geom_histogram(binwidth = 1,
                 alpha = 0.2,
                 position = "identity", aes(y = 100*(..count..)/sum(..count..))) +
  scale_color_manual(values = rainbow(3)) +
  geom_vline(
    aes(xintercept = mean(age)),
    color = "black",
    linetype = "dashed",
    size = 1
  ) +
  labs(title = "Age histogram plot", x = "Age", y = "Percentage") +
  theme_minimal() + theme(plot.title = element_text(hjust = 0.5))+
  stat_bin(aes(y=round(100*(..count..)/sum(..count..),1), label=round(100*(..count..)/sum(..count..),1)), geom="text", vjust=0, binwidth = 1) 

这将导致如下图所示：

在绘图中，每种性别的计数分别显示在其各自bin的顶部。但是，我不希望按性别区分人数，我只想将总人数放在垃圾箱的顶部（即我只想要红色数字表示总人数）。在ggplot2中针对性别类别具有aes(x = age, color = Gender, fill = Gender)美学的同时，我该如何实现？

编辑：根据以下答案，尝试了以下操作

ageGroupCount <- histData[, -1]
ageGroupCount$age <- as.integer(df$age)
ageGroupCount$Gender <- as.factor(df$Gender)
ageGroupCount <-
  ageGroupCount %>%  group_by(age, Gender) %>% count()

ageCount <- histData[2] %>% count()

ageGroupCount %>%
  ggplot(aes(x = age, y = freq, label = freq)) +
  geom_col(aes(fill = Gender, color = Gender), alpha = 0.65) +
  scale_y_continuous(labels = percent) +
  geom_text(
    data = ageCount,
    size = 3,
    position = position_dodge(width = 1),
    vjust = -0.5
  ) + geom_vline(
    aes(xintercept = mean(age)),
    color = "black",
    linetype = "dashed",
    size = 1
  ) + scale_color_manual(values = rainbow(3)) +
  labs(title = "Age histogram plot", x = "Age", y = "Percentage") +
  theme_minimal() + theme(plot.title = element_text(hjust = 0.5))

这导致了以下情节： 如何消除刻度中的尾随零，如何将百分比值而不是绝对数放在每个小节的顶部？

答案：我可以使用下面的代码来实现

ageGroupCount <- histData[, -1]
ageGroupCount$age <- as.integer(ageGroupCount$age)
ageGroupCount$Gender <- as.factor(ageGroupCount$Gender)
ageGroupCount <-
  ageGroupCount %>%  group_by(age, Gender) %>% count()
ageGroupCount <- mutate(ageGroupCount, freq = round(100*freq / sum(freq),1))

ageCount <- histData[2] %>% count()
ageCount$age <- as.integer(ageCount$age)
ageCount <- mutate(ageCount, freq = round(100*freq / sum(freq),1))

ageGroupCount %>%
  ggplot(aes(x = age, y = freq, label = freq)) +
  geom_col(aes(fill = Gender, color = Gender), alpha = 0.65) +
  geom_text(
    data = ageCount,
    size = 3,
    position = position_dodge(width = 1),
    vjust = -0.5
  ) + geom_vline(
    aes(xintercept = mean(age)),
    color = "black",
    linetype = "dashed",
    size = 1
  ) + scale_color_manual(values = rainbow(3)) +
  scale_y_continuous(labels = function(x) paste0(x, "%"))+
  labs(title = "Age histogram plot", x = "Age", y = "Percentage") +
  theme_minimal() + theme(plot.title = element_text(hjust = 0.5))

Answer 1

好的，首先让我们通过按年龄和性别进行计数的摘要数据框来简化此操作。

df <-
  histData %>% 
  group_by(age, Gender) %>% 
  count()

df
# A tibble: 22 x 3
# Groups:   age, Gender [22]
     age Gender     n
   <int> <fct>  <int>
 1    10 Female    20
 2    10 Male      22
 3    11 Female    22
...

然后，我们可以使用geom_col直接绘制结果，而不用geom_histogram用很多讨厌的语法来计算结果。文本标签来自第二个分组/计数操作，使用性别数字作为权重：

df %>% 
  ggplot(aes(x = age, y = n)) +
  geom_col(aes(fill = Gender)) +
  geom_text(
    data = . %>% group_by(age) %>% count(wt = n),
    aes(y = n + 2, label = n)
  )

这完成了图的核心部分-看来您应该可以从这里处理格式和其他添加内容。