R语言：基于V4分组替换V7为组内最小值、V8为组内最大值

需求说明 #

现有按V7升序排列的grouped_df数据框，每个V4分组固定包含2行数据，需完成以下操作：

• 将每个V4分组内的V7字段值全部替换为该分组V7的最小值
• 将每个V4分组内的V8字段值全部替换为该分组V8的最大值

原始数据 #

df <- structure(list(V1 = c("chr9", "chr9", "chr1", "chr1", "chr2", 
"chr2"), V2 = c(130714314L, 130883963L, 179107712L, 179229235L, 
157737525L, 157799421L), V3 = c(130714460L, 130885688L, 179109446L, 
179229402L, 157737670L, 157799498L), V4 = c("ABL1", "ABL1", "ABL2", 
"ABL2", "ACVR1", "ACVR1"), V5 = c(0L, 0L, 0L, 0L, 0L, 0L), V6 = c(".", 
".", ".", ".", ".", "."), V7 = c(130714314L, 130883963L, 179107712L, 
179229235L, 157737525L, 157799421L), V8 = c(130714460L, 130885688L, 
179109446L, 179229402L, 157737670L, 157799498L), V9 = c(0L, 0L, 
0L, 0L, 0L, 0L), V10 = c(1L, 1L, 1L, 1L, 1L, 1L), V11 = c("146,", 
"1725,", "1734,", "167,", "145,", "77,"), V12 = c("0,", "0,", 
"0,", "0,", "0,", "0,")), class = c("grouped_df", "tbl_df", "tbl", 
"data.frame"), row.names = c(NA, -6L), groups = structure(list(
    V4 = c("ABL1", "ABL2", "ACVR1"), .rows = structure(list(1:2, 
        3:4, 5:6), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -3L), .drop = TRUE))

期望输出 #

# A tibble: 6 × 12
# Groups:   V4 [3]
  V1           V2        V3 V4       V5 V6           V7        V8    V9   V10 V11   V12  
  <chr>     <int>     <int> <chr> <int> <chr>     <int>     <int> <int> <int> <chr> <chr>
1 chr9  130714314 130714460 ABL1      0 .     130714314 130885688     0     1 146,  0,   
2 chr9  130883963 130885688 ABL1      0 .     130714314 130885688     0     1 1725, 0,   
3 chr1  179107712 179109446 ABL2      0 .     179107712 179229402     0     1 1734, 0,   
4 chr1  179229235 179229402 ABL2      0 .     179107712 179229402     0     1 167,  0,   
5 chr2  157737525 157737670 ACVR1     0 .     157737525 157799498     0     1 145,  0,   
6 chr2  157799421 157799498 ACVR1     0 .     157737525 157799498     0     1 77,   0,  

现有尝试 #

已尝试通过以下代码获取分组内V7的最小值，但无法同时处理V8的最大值：

df %>% 
  dplyr::group_by(V4) %>%
  dplyr::slice(which.min(V7))

备选思路考虑使用lag()/lead()函数，但未找到可行方案。

解决方案 #

方法一：使用dplyr的mutate结合min/max（通用方案） #

直接在分组内计算V7的最小值和V8的最大值，替换原字段，适用于任意行数的分组：

library(dplyr)

df_processed <- df %>%
  group_by(V4) %>%
  mutate(
    V7 = min(V7, na.rm = TRUE),
    V8 = max(V8, na.rm = TRUE)
  ) %>%
  ungroup() %>% # 若需保留分组可移除该行
  group_by(V4) # 恢复分组结构（可选）

方法二：利用固定2行分组的特点使用lag/lead #

由于数据已按V7升序排列，每个分组的第一行V7即为最小值；而V8的最大值在分组的第二行，因此可以用lead()获取第二行的V8值，或lag()获取第一行的V7值：

library(dplyr)

df_processed <- df %>%
  group_by(V4) %>%
  mutate(
    V7 = first(V7), # 或 V7 = lag(V7, default = first(V7))
    V8 = last(V8)   # 或 V8 = lead(V8, default = last(V8))
  ) %>%
  ungroup() %>% # 可选：移除分组
  group_by(V4) # 可选：恢复分组结构

以上两种方法均可得到符合需求的输出结果。

内容的提问来源于stack exchange，提问作者user2300940