如何用R（优先dplyr）筛选Departure列符合指定连续模式的行？

需求说明 #

从给定数据集中，按ID分组后，筛选出Departure列连续出现TRUE→FALSE→FALSE→FALSE模式的所有对应行。

原始数据集 #

ID Departure  Date
A      TRUE Jan 1
A     FALSE Jan 2
A      TRUE Jan 3
A     FALSE Jan 4
A     FALSE Jan 5
A     FALSE Jan 6
A     FALSE Jan 7
A      TRUE Jan 8
A     FALSE Jan 9
B      TRUE Jan 1
B     FALSE Jan 2
B     FALSE Jan 3
B     FALSE Jan 4
B      TRUE Jan 5

对应的R数据结构：

data <- structure(list(ID = c("A", "A", "A", "A", "A", "A", "A", "A", 
"A", "B", "B", "B", "B", "B"), Departure = c("TRUE", "FALSE", 
"TRUE", "FALSE", "FALSE", "FALSE", "FALSE", "TRUE", "FALSE", 
"TRUE", "FALSE", "FALSE", "FALSE", "TRUE"), Date = c("Jan 1", 
"Jan 2", "Jan 3", "Jan 4", "Jan 5", "Jan 6", "Jan 7", "Jan 8", 
"Jan 9", "Jan 1", "Jan 2", "Jan 3", "Jan 4", "Jan 5")), class = "data.frame", row.names = c(NA, 
-14L))

期望结果 #

ID Departure  Date
    A      TRUE Jan 3
    A     FALSE Jan 4
    A     FALSE Jan 5
    A     FALSE Jan 6
    B      TRUE Jan 1
    B     FALSE Jan 2
    B     FALSE Jan 3
    B     FALSE Jan 4

解决方案（优先使用dplyr） #

可以通过按ID分组，结合lead()/lag()函数检测目标模式，标记并筛选符合条件的行，无需额外依赖其他包：

library(dplyr)

result <- data %>%
  group_by(ID) %>%
  mutate(
    # 标记模式的起始行：当前行是TRUE，且后续3行都是FALSE
    match_start = Departure == "TRUE" &
      lead(Departure, 1) == "FALSE" &
      lead(Departure, 2) == "FALSE" &
      lead(Departure, 3) == "FALSE",
    # 标记需要保留的行：起始行及之后的3行都要保留
    keep = match_start |
      lag(match_start, 1, default = FALSE) |
      lag(match_start, 2, default = FALSE) |
      lag(match_start, 3, default = FALSE)
  ) %>%
  filter(keep) %>%
  select(-match_start, -keep) %>%
  ungroup()

print(result)

代码逻辑说明 #

1. group_by(ID)：确保每个ID组内独立检测模式，避免跨ID匹配。
2. match_start列：标记出符合模式的起始行（即连续4行的第一行）。
3. keep列：将起始行及其后3行都标记为需要保留，覆盖整个模式的4行数据。
4. 最后筛选出keep为TRUE的行，移除辅助列后得到目标结果。

如果习惯用滑动窗口工具，也可以搭配slider包实现，代码逻辑更直观：

library(dplyr)
library(slider)

result <- data %>%
  group_by(ID) %>%
  mutate(
    # 滑动窗口检测4行是否匹配目标模式
    match_pattern = slide_lgl(
      Departure,
      ~ all(.x == c("TRUE", "FALSE", "FALSE", "FALSE")),
      .before = 0, .after = 3, .complete = TRUE
    ),
    # 标记所有属于匹配模式的行
    keep = any(match_pattern | lead(match_pattern, 1) | lead(match_pattern, 2) | lead(match_pattern, 3))
  ) %>%
  filter(keep) %>%
  select(-match_pattern, -keep) %>%
  ungroup()

print(result)

内容的提问来源于stack exchange，提问作者Cam