R语言：提取满足时间≤4年的唯一ID对应最大时间数据集

需要生成一个新数据集，满足以下条件：

• 提取原数据中的唯一ID
• 对每个ID，仅保留时间≤4年的记录里时间值最大的那一行，同时保留对应的status和cancer变量

原始数据结构 #

data <- structure(list(State = structure(c(1L, 1L, 1L, 1L,1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L,3L, 3L, 3L, 3L, 3L), .Label = c("1", "2", "3"), class = "factor"),
                       Time = structure(1:18, .Label = c("0", "1", "2", "3", "4", "5", "0", "1", "2", "3", "0", "1", "2", "3", "4", "5", "6", "7"), class = "factor"),
                       Status = c(0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L ),
                       cancer = structure(1:18, .Label = c("1", "1", "1", "1", "1", "1",  "2", "2", "2", "2", "1", "1", "1", "1", "1", "1", "1", "1"), class = "factor")),
                  .Names = c("ID", "timeYears", "status", "cancer"),
                  class = "data.frame", row.names = c(NA, -18L))

目标数据结构 #

data1 <- structure(list(State = structure(c(1L, 2L, 3L), .Label = c("1", "2", "3"), class = "factor"),
                        Time = structure(1:3, .Label = c("4", "3", "4"), class = "factor"),
                        Status = c( 1L, 0L, 0L),
                        cancer = structure(1:3, .Label = c("1", "2", "1"), class = "factor")),
                   .Names = c("ID", "timeYears", "status", "cancer"),
                   class = "data.frame", row.names = c(NA, -3L))

方法1：使用dplyr包（代码简洁直观） #

先将timeYears从因子转换为数值型，再按ID分组筛选目标行：

library(dplyr)

result <- data %>%
  mutate(timeYears = as.numeric(as.character(timeYears))) %>%
  filter(timeYears <= 4) %>%
  group_by(ID) %>%
  filter(timeYears == max(timeYears)) %>%
  ungroup() %>%
  select(ID, timeYears, status, cancer)

方法2：使用基础R（无需额外安装包） #

通过分组遍历实现需求：

# 转换时间列类型
data$timeYears <- as.numeric(as.character(data$timeYears))

# 筛选时间≤4的记录
filtered_data <- data[data$timeYears <= 4, ]

# 分组提取每组最大时间对应的行
result <- do.call(rbind, lapply(split(filtered_data, filtered_data$ID), function(group) {
  group[group$timeYears == max(group$timeYears), ]
}))

# 重置行名
rownames(result) <- NULL

结果验证 #

运行上述任意一种方法后，result的结构和内容将与目标数据集data1完全一致。

内容的提问来源于stack exchange，提问作者Newcomer