如何使用R语言ggplot实现散点图、箱线图与线性回归线同图绘制

实现方案 #

你之前的核心冲突是散点用了离散因子型x轴，无法叠加需要连续x轴的线性回归线，我们通过统一x轴为连续数值、手动设置刻度标签的方式解决该问题，完整实现代码如下：

1. 加载依赖包

library(tidyverse)
# 可选依赖，用于自动生成回归公式，无需手动计算位置
library(ggpmisc)

2. 原数据（无需修改）

df <- structure(list(Sample = c(2113, 2113, 2114, 2114, 2115, 2115, 
2116, 2116, 2117, 2117, 2118, 2118, 2119, 2119, 2120, 2120, 2121, 
2121, 2122, 2122, 2123, 2123, 2124, 2124), Rep_No = c("A", "B", 
"A", "B", "A", "B", "A", "B", "A", "B", "A", "B", "A", "B", "A", 
"B", "A", "B", "A", "B", "A", "B", "A", "B"), Fe = c(57.24, 57.12, 
57.2, 57.13, 57.21, 57.14, 57.16, 57.31, 57.11, 57.18, 57.21, 
57.12, 57.14, 57.17, 57.1, 57.18, 57, 57.06, 57.13, 57.09, 57.17, 
57.23, 57.09, 57.1), SiO2 = c("6.85", "6.83", "6.7", "6.69", 
"6.83", "6.8", "6.76", "6.79", "6.82", "6.82", "6.8", "6.86", 
"6.9", "6.82", "6.81", "6.83", "6.79", "6.76", "6.8", "6.88", 
"6.83", "6.79", "6.8", "6.83"), Al2O3 = c("2.9", "2.88", "2.88", 
"2.88", "2.92", "2.9", "2.89", "2.87", "2.9", "2.89", "2.9", 
"2.89", "2.89", "2.88", "2.89", "2.91", "2.91", "2.91", "2.9", 
"2.9", "2.91", "2.91", "2.88", "2.86")), row.names = c(NA, -24L
), class = "data.frame")

3. 数据预处理

df_plot <- df %>%
  # 给每个唯一样本分配1~12的连续序号，作为散点的x轴位置
  mutate(sample_pos = as.integer(factor(Sample, levels = unique(Sample))))
# 自定义x轴标签，第一个位置对应箱线图，后面对应样本编号
x_ticks <- c("All Data", unique(df_plot$Sample))

4. 完整绘图代码（满足所有需求）

ggplot() +
  # 箱线图放在x=0的最左侧位置
  geom_boxplot(aes(x = 0, y = Fe), data = df_plot) +
  # 散点用样本序号作为x位置，保留按Sample分组的原有配色逻辑
  geom_point(aes(x = sample_pos, y = Fe, color = factor(Sample)), data = df_plot) +
  # 添加线性回归线
  geom_smooth(aes(x = sample_pos, y = Fe), data = df_plot,
              method = "lm", se = FALSE, color = "gray30") +
  # 自动添加回归公式与R²，不需要手动设置坐标
  stat_poly_eq(aes(x = sample_pos, y = Fe), data = df_plot,
               formula = y ~ x,
               label = paste(after_stat(eq.label), after_stat(rr.label), sep = "*\", \"*"),
               parse = TRUE,
               label.y = "bottom") +
  # 自定义x轴刻度和标签
  scale_x_continuous(breaks = 0:12, labels = x_ticks) +
  # 主题和标签设置，和你原有样式保持一致
  ggtitle("Lab Test Order Fe") +
  xlab("Sample No") +
  ylab("Homogeneity Test Fe %") +
  theme(
    plot.title = element_text(hjust = 0.5),
    legend.position = "none"
  )

无额外依赖的替代方案

如果你不想安装ggpmisc包，可以用你原来的lm_eqn函数，把公式部分替换为自适应坐标的版本即可：

# 你原来的公式计算函数，适配新的x轴映射
lm_eqn <- function(df,...){
  x <- df$sample_pos
  y <- df$Fe
  m <- lm(y ~ x, df);
  eq <- substitute(italic(y) == a + b %.% italic(x)*","~~italic(r)^2~"="~r2, 
                   list(a = format(unname(coef(m)[1]), digits = 2),
                        b = format(unname(coef(m)[2]), digits = 2),
                        r2 = format(summary(m)$r.squared, digits = 3)))
  as.character(as.expression(eq));
}
a <- lm_eqn(df_plot)

# 把stat_poly_eq部分替换为下面的代码即可，不需要手动指定固定坐标
geom_text(aes(x = median(unique(df_plot$sample_pos)), 
              y = min(df_plot$Fe) + 0.02, 
              label = a, parse = TRUE), 
          check_overlap = TRUE)

实现效果说明

• 箱线图固定在x轴最左侧的0位置，和右侧散点区域完全分隔
• 散点的颜色映射逻辑和你原有代码完全一致，配色保留
• 回归公式通过计算取值范围自动定位，不需要手动输入固定坐标，适配不同数据范围

内容的提问来源于stack exchange，提问作者Spooked