提取与 R 中列范围之外的字符串匹配的值

问：

在 R 中编写相关代码。我有一个数据帧（称为 realData），其中包含 10 个名为“RealAttribute_X”的变量，其中 X 是 1 到 10（包括）之间的数字。 每列包含十个属性之一：“智慧”、“吸引力”、“魅力”、“野心”、“懒惰”、“慷慨”、“快乐”、“友好”、“傲慢”、“冷静”。这些属性被随机分配给 10 个“RealAttribute_X”中的 1 个。

dt<-structure(list(session_id = c("17472631", "17472632", "17472633", 
"17472635", "17472636", "17472638"), RealAttribute_1 = c("Moderately ugly", 
"Very dull", "Very distant", "Very joyful", "Moderately joyful", 
"Very distant"), RealAttribute_2 = c("Very nervous", "Very gloomy", 
"Very generous", "Moderately charismatic", "Moderately hard working", 
"Moderately modest"), RealAttribute_3 = c("Slightly generous", 
"Moderately ugly", "Moderately arrogant", "Moderately calm", 
"Moderately charismatic", "Moderately charismatic"), RealAttribute_4 = c("Moderately arrogant", 
"Slightly generous", "Very dull", "Moderately distant", "Slightly distant", 
"Slightly ambitious"), RealAttribute_5 = c("Slightly unambitious", 
"Moderately calm", "Moderately unambitious", "Moderately lazy", 
"Very modest", "Moderately intelligent"), RealAttribute_6 = c("Slightly dull", 
"Slightly ambitious", "Very calm", "Moderately ambitious", "Moderately generous", 
"Moderately generous"), RealAttribute_7 = c("Very intelligent", 
"Slightly distant", "Very intelligent", "Slightly ugly", "Very good-looking", 
"Very lazy"), RealAttribute_8 = c("Very joyful", "Slightly modest", 
"Slightly joyful", "Very arrogant", "Very ambitious", "Slightly good-looking"
), RealAttribute_9 = c("Very distant", "Very lazy", "Slightly good-looking", 
"Very generous", "Moderately intelligent", "Moderately gloomy"
), RealAttribute_10 = c("Slightly lazy", "Moderately intelligent", 
"Slightly hard working", "Moderately intelligent", "Very calm", 
"Moderately nervous")), class = "data.frame", row.names = c(NA, 
-6L))

head(dt)

每个属性可以有六个值之一。属性及其可选值为：intelligence = “非常不智能”、“中度不智能”、“稍微不智能”、“稍微智能”、“中等智能”、“非常智能” 吸引力=“非常丑陋”、“中度丑陋”、“略微丑陋”、“稍微好看”、“适度好看”、“非常好看” 懒惰 = “非常懒惰”， “适度懒惰”， “稍微懒惰”， “稍微努力”， “适度努力”， “非常努力” 友好度 = “非常遥远”， “适度疏远”， “稍微疏远”， “稍微友好”， “适度友好”， “非常友好” 魅力=“非常沉闷”、“适度沉闷”、“略显沉闷”、“略显魅力”、“中等魅力”、“非常有魅力” calmness = “非常紧张”， “中度紧张”， “稍微紧张”， “稍微平静”， “适度平静”， “非常平静” 慷慨 = “非常吝啬”， “适度吝啬”， “略显吝啬”， “略显慷慨”， “适度慷慨”， “非常慷慨” joyfullness = “非常忧郁”， “适度忧郁”， “略显忧郁”， “略有喜悦”， “适度喜悦”， “非常喜悦” 傲慢=“非常傲慢”、“适度傲慢”、“略微傲慢”、“略微谦虚”、“适度谦虚”、“非常谦虚” ambition = “非常没有野心”， “适度没有野心”， “有点没有野心”， “有点雄心勃勃”， “适度雄心勃勃”， “非常雄心勃勃”

我正在尝试在 R 中编写一个代码，该代码将创建 10 个新列，每个属性（“智力”、“吸引力”、“魅力”、“野心”、“懒惰”、“慷慨”、“快乐”、“友好”、“傲慢”、“冷静”），在包含相关属性的现有数据帧中找到正确的变量，并将该属性的值分配给正确的新变量。

例如，这是 DataFrame 的前四行： RealAttribute_1：“适度丑陋”、“非常沉闷”、“非常遥远”、“非常快乐”<br RealAttribute_2：“非常紧张”、“非常阴郁”、“非常慷慨”、“中等魅力”<br RealAttribute_3：“略显慷慨”“适度丑陋”“适度傲慢”“适度冷静”<br RealAttribute_4：“适度傲慢”、“略显慷慨”、“非常沉闷”、“适度疏远”<br RealAttribute_5：“有点没有野心”，“适度冷静”，“适度没有野心”，“适度懒惰”<br RealAttribute_6：“有点沉闷”，“有点野心”，“非常冷静”，“适度雄心勃勃”<br RealAttribute_7：“非常聪明”、“有点疏远”、“非常聪明”、“有点丑”<br RealAttribute_8：“非常快乐”、“略显谦虚”、“略显快乐”、“非常傲慢”<br RealAttribute_9 “很遥远”， “很懒惰”， “稍微好看”， “很大方”<br RealAttribute_10：“稍微懒惰”“中等聪明”，“稍微勤奋”，“中等聪明”<br

因此，前四行的最终结果应如下所示： 智能：“非常智能”、“中等智能”、“非常智能”、“中等智能”<br 吸引力：“适度丑陋”、“适度丑陋”、“略微好看”、“略微丑陋”<br 懒惰：“有点懒惰”，“非常懒惰”，“稍微努力”，“适度懒惰”<br 友好度： “非常遥远”， “稍微遥远”， “非常遥远”， “适度遥远”<br 魅力：“有点沉闷”，“非常沉闷”，“非常沉闷”，“中等魅力”<br 冷静：“非常紧张”、“适度冷静”、“非常冷静”、“适度冷静”<br 慷慨： “稍微慷慨”， “稍微慷慨”， “非常慷慨”， “非常慷慨”<br 快乐：“非常高兴”， “非常阴郁”， “稍微高兴”， “非常高兴”<br 傲慢：“适度傲慢”，“略显谦虚”，“适度傲慢”，“非常傲慢”<br 野心：“有点野心”，“有点野心”，“适度没有野心”，“适度雄心勃勃”<br

我定义了所有属性值

attribute_values <- list(
  intelligence = c("Very unintelligent", "Moderately unintelligent", "Slightly unintelligent", 
                   "Slightly intelligent", "Moderately intelligent", "Very intelligent"),
  attractiveness = c("Very ugly", "Moderately ugly", "Slightly ugly", 
                     "Slightly good-looking", "Moderately good-looking", "Very good-looking"),
  laziness = c("Very lazy", "Moderately lazy", "Slightly lazy", 
               "Slightly hard working", "Moderately hard working", "Very hard working"),
  friendliness = c("Very distant", "Moderately distant", "Slightly distant", 
                   "Slightly friendly", "Moderately friendly", "Very friendly"),
  charisma = c("Very dull", "Moderately dull", "Slightly dull", 
               "Slightly charismatic", "Moderately charismatic", "Very charismatic"),
  calmness = c("Very nervous", "Moderately nervous", "Slightly nervous", 
               "Slightly calm", "Moderately calm", "Very calm"),
  generosity = c("Very stingy", "Moderately stingy", "Slightly stingy", 
                 "Slightly generous", "Moderately generous", "Very generous"),
  joyfullness = c("Very gloomy", "Moderately gloomy", "Slightly gloomy", 
                  "Slightly joyful", "Moderately joyful", "Very joyful"),
  arrogance = c("Very arrogant", "Moderately arrogant", "Slightly arrogant", 
                "Slightly modest", "Moderately modest", "Very modest"),
  ambition = c("Very unambitious", "Moderately unambitious", "Slightly unambitious", 
               "Slightly ambitious", "Moderately ambitious", "Very ambitious")
)

但是开始检查我的代码中的第一个变量（智能）：

intelligence_values <- c("Very unintelligent", "Moderately unintelligent", "Slightly unintelligent", 
                         "Slightly intelligent", "Moderately intelligent", "Very intelligent")

realData$Intelligence <- apply(dt[, grep("RealAttribute_", colnames(realData), value = TRUE)], 1, function(row) {
  match_value <- which(row %in% intelligence_values)[1]
  if (is.na(match_value)) {
    return(NA)
  } else {
    return(intelligence_values[match_value])
  }
})

此代码仅将 NA 返回到“智能”列。 我也试过：

realData <- realData %>%
  rowwise() %>%
  mutate(Intelligence = intelligence_values[match(c_across(starts_with("RealAttribute")), intelligence_values)])

但出现以下错误： 错误： !只能在数据屏蔽谓词（如 、 和 ）中使用。c_across()mutate()filter()group_by()

运行 rlang：：last_trace（） 后： <错误/rlang_error> 错误： !只能在数据屏蔽谓词（如 、 和 ）中使用。 **--- 回溯： xc_across()mutate()filter()group_by()

1. +-realData %>% rowwise（） %>% ...
2. -plyr：：突变（...）
3. -base：：eval（cols[[col]]， .data， parent.frame（））

4. \-base::eval(cols[[col]], .data, parent.frame())
   

5.   +-base::match(c_across(starts_with("RealAttribute")), intelligence_values)
   

6.   \-dplyr::c_across(starts_with("RealAttribute"))
   

运行 rlang：：last_trace（drop = FALSE） 查看 4 个隐藏帧。

任何想法，哪里出了问题，或者我应该怎么写？ 提前致谢！