按组随机选取同一行的value与treatment并替换组内对应列

现有如下R数据框：

data <- structure(list(group = c(1, 1, 1, 1, 2, 
2, 2, 2, 3, 3, 3), value = c("1", "4", "5", "3", "3", "5", "3", "5", "1", "4", "2"), treatment = c("A", "A", "B", "C", "C", 
"C", "C", "C", "A", "A","NA"), retain = c("88", "664", "797", "131", "88", "997", "645", "88", "13", "79", "5")), class = "data.frame", row.names = c(NA, -11L))

需要对每个group执行以下操作：

• 随机选取该组内某一行的value和treatment值
• 将该组内所有行的value和treatment列替换为选中的值
• 保留retain列的原有数据

期望输出示例（随机选取结果仅作参考，每次运行结果会不同）：

data <- structure(list(group = c(1, 1, 1, 1, 2, 
2, 2, 2, 3, 3, 3), value = c("4", "4", "4", "4", "5", "5", "5", "5", "2", "2", "2"), treatment = c("A", "A", "A", "A", "C", 
"C", "C", "C", "NA", "NA","NA"), retain = c("88", "664", "797", "131", "88", "997", "645", "88", "13", "79", "5")), class = "data.frame", row.names = c(NA, -11L))

方法1：使用dplyr包（推荐，代码简洁易读） #

先确保已安装dplyr包，未安装则运行install.packages("dplyr")：

library(dplyr)

set.seed(123) # 设置随机种子，确保结果可重复，不需要可移除

result <- data %>%
  group_by(group) %>%
  mutate(
    sample_idx = sample(n(), 1), # 随机生成组内一行的索引
    value = first(value[sample_idx]), # 用选中行的value替换整组
    treatment = first(treatment[sample_idx]) # 用选中行的treatment替换整组
  ) %>%
  select(-sample_idx) %>% # 删除临时生成的索引列
  ungroup() # 取消分组，返回普通数据框

# 查看结果
print(result)

方法2：Base R实现（无需额外包） #

set.seed(123)

# 按group拆分数据框
split_data <- split(data, data$group)

# 逐个处理分组
processed_data <- lapply(split_data, function(df) {
  # 随机选取组内一行
  sample_row <- df[sample(nrow(df), 1), ]
  # 替换整组的value和treatment
  df$value <- sample_row$value
  df$treatment <- sample_row$treatment
  return(df)
})

# 合并回完整数据框并重置行名
result <- do.call(rbind, processed_data)
row.names(result) <- NULL

# 查看结果
print(result)

内容的提问来源于stack exchange，提问作者kalex