如何让ggplot2次Y轴在自定义累计值位置设置刻度断点？

先来看@camille最初用ggplot2制作的帕累托图代码，效果已经相当不错了：

library(tidyverse)
d <- tribble(
  ~ category, ~defect,
  "price", 80,
  "schedule", 27,
  "supplier", 66,
  "contact", 94,
  "item", 33
) %>% 
  arrange(desc(defect)) %>% 
  mutate(
    cumsum = cumsum(defect),
    freq = round(defect / sum(defect), 3),
    cum_freq = cumsum(freq)
  ) %>% 
  mutate(category = as.factor(category) %>% fct_reorder(defect))
brks <- unique(d$cumsum)
ggplot(d, aes(x = fct_rev(category))) +
  geom_col(aes(y = defect)) +
  geom_point(aes(y = cumsum)) +
  geom_line(aes(y = cumsum, group = 1)) +
  scale_y_continuous(sec.axis = sec_axis(~. / max(d$cumsum), labels = scales::percent), breaks = brks)

对应的效果如下：

这个图的表现已经近乎完美，但咱们还想优化一点：让次Y轴的刻度精准落在每个累计值的位置——就像下面这段Base R代码实现的效果：

## Creating the d tribble
library(tidyverse)
d <- tribble(
  ~ category, ~defect,
  "price", 80,
  "schedule", 27,
  "supplier", 66,
  "contact", 94,
  "item", 33
)
## Creating new columns
d <- arrange(d, desc(defect)) %>% 
  mutate(
    cumsum = cumsum(defect),
    freq = round(defect / sum(defect), 3),
    cum_freq = cumsum(freq)
  )
## Saving Parameters
def_par <- par()
## New margins
par(mar=c(5,5,4,5))
## bar plot, pc will hold x values for bars
pc = barplot(d$defect, width = 1, space = 0.2, border = NA, axes = F, ylim = c(0, 1.05 * max(d$cumsum, na.rm = T)), ylab = "Cummulative Counts" , cex.names = 0.7, names.arg = d$category, main = "Pareto Chart (version 1)")
## Cumulative counts line
lines(pc, d$cumsum, type = "b", cex = 0.7, pch = 19, col="cyan4")
## Framing plot
box(col = "grey62")
## adding axes
axis(side = 2, at = c(0, d$cumsum), las = 1, col.axis = "grey62", col = "grey62", cex.axis = 0.8)
axis(side = 4, at = c(0, d$cumsum), labels = paste(c(0, round(d$cum_freq * 100)) ,"%",sep=""), las = 1, col.axis = "cyan4", col = "cyan4", cex.axis = 0.8)
## restoring default paramenter
par(def_par)

对应的Base R实现效果：

正如Camille提到的，新版ggplot2支持次轴，但必须基于主轴的转换逻辑——这里的核心是把主轴的累计值转换为次轴的百分比，关键在于手动指定次轴的breaks和labels，让它们和累计值一一对应。下面是修改后的ggplot2代码，完美实现需求：

library(tidyverse)
d <- tribble(
  ~ category, ~defect,
  "price", 80,
  "schedule", 27,
  "supplier", 66,
  "contact", 94,
  "item", 33
) %>% 
  arrange(desc(defect)) %>% 
  mutate(
    cumsum = cumsum(defect),
    freq = round(defect / sum(defect), 3),
    cum_freq = cumsum(freq)
  ) %>% 
  # 调整分类顺序，让最大的缺陷类别在最左边
  mutate(category = fct_reorder(category, defect) %>% fct_rev())

# 准备次轴的断点和标签：
# 次轴断点需要是主轴累计值除以总缺陷数（转换为0-1的比例，对应次轴的百分比）
sec_breaks <- d$cumsum / max(d$cumsum)
# 标签直接用预先计算好的累计频率转成百分比格式
sec_labels <- scales::percent(d$cum_freq)

ggplot(d, aes(x = category)) +
  geom_col(aes(y = defect), fill = "steelblue", alpha = 0.8) +
  geom_point(aes(y = cumsum), color = "darkorange", size = 2) +
  geom_line(aes(y = cumsum, group = 1), color = "darkorange", linewidth = 1) +
  scale_y_continuous(
    name = "缺陷数量",
    # 主轴也可以设置断点对应累计值，让图表更清晰
    breaks = c(0, d$cumsum),
    sec.axis = sec_axis(
      ~ . / max(d$cumsum),
      name = "累计百分比",
      breaks = sec_breaks,
      labels = sec_labels
    )
  ) +
  labs(title = "优化后的ggplot2帕累托图") +
  theme_minimal() +
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

关键逻辑说明： #

• 次轴的本质是对主轴数值做线性转换（这里是除以总缺陷数得到比例），所以次轴的breaks必须是转换后的数值（累计值/总缺陷数）
• labels直接使用提前计算好的cum_freq，转成百分比格式，这样每个刻度就精准对应到了累计值的位置
• 同时主轴也可以设置对应累计值的断点，让整个图表的刻度更直观

内容的提问来源于stack exchange，提问作者stackinator