R语言数据框处理：为未选中属性列填充0的技术需求

需求说明 #

处理数据框时，需要为attr_shown列中未被选为Most_helpful或Least_helpful的属性对应列填充0。具体要求：

• 第1、2、3行的Link_to_setup_videos列填0
• 第4行的Non_mobile_device_instructions列填0

示例数据 #

df <- data.frame(
  Respondent = rep(8,4),
  Set= seq(1:4),
  Least_helpful = c("Customer service phone number", "Customer service phone number", "QR code to online chat","QR code to online chat"),
  Most_helpful = c("Non-mobile device instructions", "Non-mobile device instructions", "Non-mobile device instructions", "Mobile device instructions"),
  attr_shown = c("Non-mobile device instructions;Customer service phone number;Link to setup videos",
                 "Mobile device instructions;QR code to online chat;Link to setup videos",
                 "Non-mobile device instructions;QR code to online chat;Link to setup videos", "Mobile device instructions;Non-mobile device instructions;QR code to online chat"),
  Customer_service_phone_number = c(-1,-1,NA,NA),
  Non_mobile_device_instructions = c(1,1,1,NA),
  Link_to_setup_videos = c(NA,NA,NA,NA),
  Mobile_device_instructions = c(NA,NA,NA,1),
  QR_code_to_online_chat = c(NA,NA,-1,-1)
)

解决方案代码 #

使用dplyr包实现需求：

library(dplyr)

# 转换属性名称格式（空格替换为下划线，匹配数据框列名）
clean_attr_name <- function(attr) {
  gsub(" ", "_", attr)
}

df_processed <- df %>%
  rowwise() %>%
  # 拆分展示属性，筛选出既不是最有用也不是最没用的属性
  mutate(target_col = list(setdiff(strsplit(attr_shown, ";")[[1]], c(Most_helpful, Least_helpful)) %>% clean_attr_name())) %>%
  ungroup() %>%
  # 为目标列对应行填充0
  mutate(across(all_of(unlist(.$target_col)), 
                ~ifelse(row_number() %in% which(sapply(target_col, function(cols) cur_column() %in% cols)), 0, .))) %>%
  # 移除辅助列
  select(-target_col)

# 查看处理结果
print(df_processed)

结果验证 #

处理后的数据框满足需求：

• 第1-3行Link_to_setup_videos值为0
• 第4行Non_mobile_device_instructions值为0
• 其余原有值（1/-1）保持不变

内容的提问来源于stack exchange，提问作者Matt Gehr