如何在R语言中对坐标数据进行随机分类？

1. 数据随机分组处理 #

先修正原代码中runif的冗余参数，再添加随机分组逻辑：通过随机生成互斥的分组标识，得到Group1和Group2列（1表示属于该组，-1表示不属于）。

完整代码如下：

# Number of observations
n <- 250
# x randomly drawn from a continuous uniform distribution with bounds [0,1]
x <- runif(min = 0, max = 1, n = n)
# Error term from Normal distribution
error <- rnorm(n = n, mean = 0, sd = 2)
beta_0 <- 1
beta_1 <- -1
y <- beta_0*x + (beta_1*x - error)

library(tibble)
# 设置随机种子保证分组结果可重复
set.seed(123)
# 生成Group1的分组标识，再通过相反数得到互斥的Group2
group1 <- sample(c(1, -1), n, replace = TRUE)
group2 <- -group1
# 组装包含分组列的数据表
df <- tibble(x = x, y = y, Group1 = group1, Group2 = group2)
df

2. 分组散点图绘制 #

修改ggplot代码，通过颜色映射区分两组数据，指定蓝色对应Group1、红色对应Group2：

library(ggplot2)
# 生成可读性更强的分组名称列（可选，便于图例展示）
df <- df %>% 
  mutate(Group = ifelse(Group1 == 1, "Group1", "Group2"))

ggplot(data = df, aes(x = x, y = y, color = Group)) +
  geom_point(size = 2) +
  # 手动指定两组颜色
  scale_color_manual(values = c("Group1" = "blue", "Group2" = "red")) +
  labs(title = "y = f(x) (分组散点图)", x = "x", y = "y") +
  theme_minimal()

替代方案（无需额外分组列） #

如果不想新增Group列，可直接基于Group1的取值映射颜色：

ggplot(data = df, aes(x = x, y = y, color = factor(Group1))) +
  geom_point(size = 2) +
  scale_color_manual(values = c("-1" = "red", "1" = "blue"),
                     labels = c("Group2", "Group1")) +
  labs(title = "y = f(x) (分组散点图)", x = "x", y = "y", color = "分组") +
  theme_minimal()

内容的提问来源于stack exchange，提问作者Prometheus