如何基于含Proszę表头的列值条件化修改相邻行数据（R语言）

给定如下R语言数据集：

ProszęAveryextendedname <- c("A","A","A","A","B","B","B")
var2 <- c("B","B","B","B","B","B","B")
var3 <- c("B","B","B","B","B","B","B")

ProszęBveryextendedname <- c("A","A","A","A","B","B","B")
var5 <- c("B","B","B","B","B","B","B")
var6 <- c("B","B","B","B","B","B","B")

df <- data.frame(ProszęAveryextendedname , var2, var3, ProszęBveryextendedname, var5, var6)

需求：当表头包含Proszę的列中某行值为'A'时，将该行的相邻列设为NA；若值为'B'则保持原数据。

方案一：基于tidyverse实现 #

利用dplyr的批量处理能力，定位目标列后修改其相邻列：

library(tidyverse)

# 获取所有含Proszę的列的位置索引
target_cols <- grep("Proszę", names(df))

df_processed <- df %>%
  mutate(across(all_of(target_cols), ~{
    # 获取当前处理列的索引
    col_pos <- match(cur_column(), names(df))
    # 遍历当前列后的2个相邻列，按条件赋值
    for(adj_pos in (col_pos + 1):(col_pos + 2)){
      !!sym(names(df)[adj_pos]) := ifelse(.x == "A", NA, !!sym(names(df)[adj_pos]))
    }
    .x
  }))

print(df_processed)

方案二：基于迭代函数（purrr）实现 #

用purrr::walk迭代处理每个目标列及其相邻列：

library(purrr)

df_processed <- df
target_cols <- grep("Proszę", names(df))

# 逐个处理目标列
walk(target_cols, function(col_pos){
  # 提取当前目标列的判断逻辑（是否为A）
  is_A <- df_processed[[col_pos]] == "A"
  # 定位需要修改的相邻列
  adj_cols <- (col_pos + 1):(col_pos + 2)
  # 对相邻列批量赋值
  df_processed[adj_cols] <<- map(df_processed[adj_cols], ~ifelse(is_A, NA, .x))
})

print(df_processed)

方案三：基于基础R循环实现 #

用基础for循环完成逻辑判断与赋值：

df_processed <- df
target_cols <- grep("Proszę", names(df))

# 遍历每个目标列
for(col_pos in target_cols){
  # 获取当前行是否为A的逻辑向量
  is_A <- df_processed[[col_pos]] == "A"
  # 遍历后续相邻列，修改对应行的值
  for(adj_pos in (col_pos + 1):(col_pos + 2)){
    df_processed[is_A, adj_pos] <- NA
  }
}

print(df_processed)

预期输出 #

ProszęAveryextendedname var2 var3 ProszęBveryextendedname var5 var6
1                       A   NA   NA                       A   NA   NA
2                       A   NA   NA                       A   NA   NA
3                       A   NA   NA                       A   NA   NA
4                       A   NA   NA                       A   NA   NA
5                       B    B    B                       B    B    B
6                       B    B    B                       B    B    B
7                       B    B    B                       B    B    B

内容的提问来源于stack exchange，提问作者12666727b9