如何用ggplot为散点图的雌雄跗骨长度变量设置不同颜色/形状？

以下两种方法都不需要修改原datos数据框，直接在绘图环节实现雌雄数值的颜色/形状区分：

方法1：临时转长格式映射颜色（推荐，自动生成规范图例） #

利用tidyr::pivot_longer在绘图时将宽格式数据临时转换为长格式，自动生成性别变量用于颜色映射：

library(tidyr)
library(ggplot2)

ggplot(pivot_longer(datos, 
                    cols = c(Log10.Tarso.H, Log10.Tarso.M),  # 指定雌雄对应的列
                    names_to = "Sex", 
                    values_to = "Tarso_Length"),
       aes(x = Species, y = Tarso_Length, color = Sex)) +
  geom_point(size = 3) +
  labs(x = "物种", 
       y = "跗骨长度（Log10转换后）", 
       title = "雌雄跗骨长度对比",
       color = "性别") +
  scale_color_manual(values = c("Log10.Tarso.H" = "#ff6b6b", "Log10.Tarso.M" = "#4ecdc4"),
                     labels = c("雌性", "雄性"))

方法2：分两次调用geom_point手动指定样式 #

如果不想转换数据格式，可以分别绘制雌雄两列的点，手动设置颜色和形状：

library(ggplot2)

ggplot(datos) +
  # 绘制雌性跗骨长度点
  geom_point(aes(x = Species, y = Log10.Tarso.H), 
             color = "#ff6b6b", shape = 16, size = 3) +
  # 绘制雄性跗骨长度点
  geom_point(aes(x = Species, y = Log10.Tarso.M), 
             color = "#4ecdc4", shape = 17, size = 3) +
  labs(x = "物种", 
       y = "跗骨长度（Log10转换后）", 
       title = "雌雄跗骨长度对比") +
  # 手动构建图例
  scale_color_discrete(name = "性别", 
                       breaks = c("雌性", "雄性"),
                       values = c("#ff6b6b", "#4ecdc4")) +
  guides(color = guide_legend(override.aes = list(shape = c(16, 17))))

若需保留原散点图形式（x=雌，y=雄） #

如果要维持你原代码中x=Log10.Tarso.H, y=Log10.Tarso.M的配对散点形式，可以根据雌雄数值的差异设置颜色：

ggplot(datos, aes(x = Log10.Tarso.H, y = Log10.Tarso.M, 
                  color = Log10.Tarso.H > Log10.Tarso.M)) +
  geom_jitter(size = 3) +
  labs(x = "雌性跗骨长度（Log10）", 
       y = "雄性跗骨长度（Log10）", 
       title = "雌雄跗骨长度独立对比",
       color = "雌性长度 > 雄性长度") +
  scale_color_manual(values = c("FALSE" = "#4ecdc4", "TRUE" = "#ff6b6b"))

内容的提问来源于stack exchange，提问作者RogelioSNT