R语言如何按Stage列规则删除Study_ID字段的重复值

需求核心是按Study_ID去重时，优先保留Stage字段值为Stable的记录，仅当某个ID没有对应Stable记录时才保留Early Stage记录，以下提供两种可直接运行的实现方案：

方案1：dplyr实现（代码可读性高，适合日常数据处理） #

首先确保已安装dplyr包，未安装可先运行install.packages("dplyr")，代码如下：

library(dplyr)

# 构造原始测试数据集
data <- data.frame(
  Study_ID = c("100","100","200","300","400","400","500","500","600","700"),
  Stage = c("Early Stage","Stable","Stable","Early Stage","Early Stage","Stable","Early Stage","Stable","Stable","Early Stage")
)

result <- data %>%
  # 设定Stage的保留优先级：Stable > Early Stage
  mutate(Stage = factor(Stage, levels = c("Stable", "Early Stage"))) %>%
  group_by(Study_ID) %>%
  # 组内按优先级排序，取第一条记录
  arrange(Stage, .by_group = TRUE) %>%
  slice_head(n = 1) %>%
  # 还原Stage为字符格式，和原数据类型保持一致
  mutate(Stage = as.character(Stage)) %>%
  ungroup()

方案2：base R实现（无需安装第三方包） #

如果不想加载额外扩展包，可以用R原生函数实现，核心逻辑和方案1完全一致：

# 构造原始测试数据集
data <- data.frame(
  Study_ID = c("100","100","200","300","400","400","500","500","600","700"),
  Stage = c("Early Stage","Stable","Stable","Early Stage","Early Stage","Stable","Early Stage","Stable","Stable","Early Stage")
)

# 新增优先级列：Stable权重为1（优先级更高），Early Stage权重为2
data$priority <- match(data$Stage, c("Stable", "Early Stage"))
# 按Study_ID分组、优先级升序排序
data_sorted <- data[order(data$Study_ID, data$priority), ]
# 去重：每个Study_ID仅保留排序后的第一条记录，删除临时优先级列
result <- data_sorted[!duplicated(data_sorted$Study_ID), c("Study_ID", "Stage")]

# 可选：重置行号，和期望输出格式完全对齐
rownames(result) <- seq_len(nrow(result))

输出结果验证 #

运行上述任意方案后，打印result即可得到完全符合预期的输出：

Study_ID       Stage
1      100      Stable
2      200      Stable
3      300 Early Stage
4      400      Stable
5      500      Stable
6      600      Stable
7      700 Early Stage

内容的提问来源于stack exchange，提问作者sabc04