如何用ggplot2绘制堆叠柱状图+双折线图的组合图表

要实现堆叠柱状（chromosome、plasmid）与双折线（gc、cds）的组合图表，需利用ggplot2的双Y轴功能适配不同数据量级，以下是修改后的完整代码：

# 加载所需包
library(readxl)
library(ggplot2)
library(dplyr)
library(reshape2) # 替换原reshape包，兼容性更稳定

# 读取数据
years_data <- read_excel("D:/menuscript/forgraph.xlsx", sheet = "data")
years_data <- as.data.frame(years_data)

# 1. 绘制堆叠柱状图主图层（仅chromosome和plasmid）
p <- ggplot() +
  geom_bar(
    data = years_data %>% select(Year, chromosome, plasmid) %>% melt(id.vars = "Year"),
    aes(x = Year, y = value, fill = variable),
    stat = "identity", position = "stack"
  ) +
  labs(x = "Year", y = "Chromosome/Plasmid Count", fill = "Type") +
  ggtitle("Counts & GC/CDS Trends by Year") +
  scale_x_continuous(breaks = years_data$Year) +
  theme(axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)) # 优化X轴标签显示位置

# 2. 处理折线图数据（gc和cds）
line_data <- years_data %>% select(Year, gc, cds) %>% melt(id.vars = "Year")

# 计算缩放系数：让gc百分比适配右侧Y轴的量级（可根据实际数据调整）
cds_max <- max(years_data$cds)
bar_sum_max <- max(rowSums(years_data[, c("chromosome", "plasmid")]))
gc_scale <- cds_max / max(years_data$gc)

# 3. 添加双折线图层+右侧Y轴
p <- p +
  # gc折线（缩放后适配右侧轴）
  geom_line(data = line_data %>% filter(variable == "gc"),
            aes(x = Year, y = value * gc_scale, color = variable),
            linewidth = 1) +
  geom_point(data = line_data %>% filter(variable == "gc"),
             aes(x = Year, y = value * gc_scale, color = variable),
             size = 2) +
  # cds折线（直接用原数值）
  geom_line(data = line_data %>% filter(variable == "cds"),
            aes(x = Year, y = value, color = variable),
            linewidth = 1) +
  geom_point(data = line_data %>% filter(variable == "cds"),
             aes(x = Year, y = value, color = variable),
             size = 2) +
  # 设置右侧双刻度Y轴
  scale_y_continuous(
    sec.axis = sec_axis(
      ~ . / gc_scale,
      name = "GC(%) / CDS Count",
      breaks = c(seq(0, max(years_data$gc), 2), seq(0, cds_max, 500))
    )
  ) +
  # 自定义颜色区分不同元素
  scale_fill_manual(values = c("chromosome" = "#2E86AB", "plasmid" = "#F2D388")) +
  scale_color_manual(values = c("gc" = "#C94C4C", "cds" = "#8D93AB")) +
  # 调整图例布局
  guides(fill = guide_legend(order = 1), color = guide_legend(order = 2)) +
  theme(plot.title = element_text(hjust = 0.5), legend.position = "bottom")

# 显示图表
print(p)

核心要点说明 #

• 数据拆分：将柱状图和折线图的数据分开处理，避免不同类型数据的混淆
• 双Y轴适配：通过缩放系数让gc百分比与cds计数、柱状图数值的量级匹配，确保右侧轴能同时展示两种数据
• 图层顺序：先绘制柱状图再叠加折线图，防止折线被遮挡
• 样式优化：自定义颜色、调整X轴标签角度和图例位置，提升图表可读性

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