基于dplyr生成TRUE/FALSE列，检测Time开头列是否含指定值

我有一个dataframe，需要检查所有以Time开头的列是否包含特定值（例如'1'）。若某一行中有1个及以上符合条件的列，需生成一列包含TRUE/FALSE的结果列。优先采用dplyr解决方案。

示例dataframe的结构如下：

structure(list(Nummer = c("449002", "449003", "449005", "449006", 
"449010"), `Sample ID.1` = c("4490021", "4490031", "4490051", 
"4490061", "4490101"), Time.1 = c("1", "1", "1", "1", "1"), `Sample ID.2` = c("4490022", 
"4490032", "4490052", "4490062", "4490102"), Time.2 = c("2", 
"2", "2", "2", "2"), `Sample ID.3` = c("4490022", "4490032", 
"4490052", "4490062", "4490102"), Time.3 = c("2", "2", "2", "2", "2"), `Sample ID.4` = c("4490023", "4490033", "4490053", "4490063", 
"4490103"), Time.4 = c("3", "3", "3", "3", "3"), `Sample ID.5` = c("4490023", 
"4490031", "4490053", "4490063", "4490103"), Time.5 = c("3", 
"1", "3", "3", "3"), `Sample ID.6` = c("4490021", "4490031", 
"44900551", "4490061", "44901051"), Time.6 = c("1", "1", "51", 
"1", "51"), `Sample ID.7` = c("4490021", "4490031", "4490051", 
"4490061", "4490101"), Time.7 = c("1", "1", "1", "1", "1"), `Sample ID.8` = c("4490022", 
"4490032", "4490051", "4490062", "4490101"), Time.8 = c("2", 
"2", "1", "2", "1"), `Sample ID.9` = c("4490022", "4490032", 
"4490052", "4490062", "4490102"), Time.9 = c("2", "2", "2", "2", 
"2"), `Sample ID.10` = c("4490023", "4490032", "4490052", "4490063", 
"4490102"), Time.10 = c("3", "2", "2", "3", "2"), `Sample ID.11` = c("4490023", 
"4490033", "4490053", "4490063", "4490103"), Time.11 = c("3", 
"3", "3", "3", "3"), `Sample ID.12` = c(NA, "4490033", "4490053", 
NA, "4490103"), Time.12 = c(NA, "3", "3", NA, "3"), `Sample ID.13` = c(NA, 
"4490033", "44900551", NA, "44901051"), Time.13 = c(NA, "3", 
"51", NA, "51"), `Sample ID.14` = c(NA_character_, NA_character_, 
NA_character_, NA_character_, NA_character_), Time.14 = c(NA_character_, 
NA_character_, NA_character_, NA_character_, NA_character_), 
    `Sample ID.15` = c(NA_character_, NA_character_, NA_character_, 
    NA_character_, NA_character_), Time.15 = c(NA_character_, 
    NA_character_, NA_character_, NA_character_, NA_character_
    ), `Sample ID.16` = c(NA_character_, NA_character_, NA_character_, 
    NA_character_, NA_character_), Time.16 = c(NA_character_, 
    NA_character_, NA_character_, NA_character_, NA_character_
    )), class = c("grouped_df", "tbl_df", "tbl", "data.frame"
), row.names = c(NA, -5L), groups = structure(list(Nummer = c("449002", 
"449003", "449005", "449006", "449010"), .rows = structure(list(
    1L, 2L, 3L, 4L, 5L), ptype = integer(0), class = c("vctrs_list_of", 
"vctrs_vctr", "list"))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -5L), .drop = TRUE))

可以使用dplyr的if_any()函数直接实现需求，代码简洁高效：

library(dplyr)

# 假设数据框名为df，生成结果列
df_result <- df %>%
  mutate(has_target_value = if_any(starts_with("Time"), ~ .x == "1"))

代码说明 #

• starts_with("Time")：精准筛选所有列名以Time开头的列
• ~ .x == "1"：对每一列的每个元素检查是否等于目标值"1"（示例中Time列为字符类型，若为数值类型可去掉引号）
• if_any()：只要该行内任意一列满足条件，就返回TRUE，否则返回FALSE
• mutate()：将判断结果作为新列has_target_value添加到数据框中

分组数据框处理 #

示例数据为分组数据框（grouped_df），上述代码会保留原有分组结构；若不需要分组，可先解除分组：

df_result <- df %>%
  ungroup() %>%
  mutate(has_target_value = if_any(starts_with("Time"), ~ .x == "1"))

结果验证 #

针对示例数据，生成的has_target_value列结果为TRUE, TRUE, TRUE, TRUE, TRUE，因为每一行的Time列中都至少存在一个"1"。

内容的提问来源于stack exchange，提问作者Debbie Oomen