在 R 中编写相关代码。我有一个数据框（称为 realData），其中有 10 个名为“RealAttribute_X”的变量，其中 X 是 1 到 10（含）之间的数字。 每栏包含十个属性之一：“智力”、“吸引力”、“魅力”、“野心”、“懒惰”、“慷慨”、“快乐”、“友善”、“傲慢”、“冷静”。属性随机分配给 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。属性及其可选值是：智力=“非常不聪明”、“中等不聪明”、“稍微不聪明”、“稍微聪明”、“中等聪明”、“非常聪明” 吸引力=“非常丑”，“中等丑”，“稍微丑”，“稍微好看”，“中等好看”，“非常好看” 懒惰=“非常懒”、“中等懒”、“稍微懒”、“稍微努力”、“中等努力”、“非常努力” 友善 =“非常疏远”、“中等疏远”、“稍微疏远”、“稍微友好”、“一般友好”、“非常友好” charisma =“非常迟钝”、“中等迟钝”、“稍微迟钝”、“稍微有魅力”、“中等魅力”、“非常有魅力” 平静 =“非常紧张”、“中等紧张”、“有点紧张”、“稍微平静”、“中等平静”、“非常平静” 慷慨=“非常小气”，“中等小气”，“稍微小气”，“稍微慷慨”，“中等慷慨”，“非常慷慨” Joyfullness =“非常阴郁”、“中等阴郁”、“稍微阴郁”、“稍微快乐”、“中等快乐”、“非常快乐” arrogance =“非常傲慢”、“适度傲慢”、“稍微傲慢”、“稍微谦虚”、“适度谦虚”、“非常谦虚” 雄心壮志=“非常没有雄心”，“一般没有雄心”，“稍微没有雄心”，“稍微有雄心”，“中等雄心”，“非常雄心勃勃”
我正在尝试用 R 编写一段代码，创建 10 个新列，每个属性对应一个（“智力”、“吸引力”、“魅力”、“野心”、“懒惰”、“慷慨”、“快乐”、“友善”、“傲慢”、“冷静”），在现有数据框中找到包含相关属性的正确变量，并将该属性的值分配给正确的新变量。
例如，这是数据帧的前四行：
RealAttribute_1：“丑陋”、“很沉闷”、“很遥远”、“很快乐”
因此前四行的最终结果应如下所示：
智力：“非常聪明”、“中等智力”、“非常聪明”、“中等智力”
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“情报”列。 我也尝试过：
realData <- realData %>%
rowwise() %>%
mutate(Intelligence = intelligence_values[match(c_across(starts_with("RealAttribute")), intelligence_values)])
但出现以下错误：
c_across()mutate()filter()group_by()运行 rlang::last_trace() 后：
c_across()mutate()filter()group_by()\-base::eval(cols[[col]], .data, parent.frame())
+-base::match(c_across(starts_with("RealAttribute")), intelligence_values)
\-dplyr::c_across(starts_with("RealAttribute"))
运行 rlang::last_trace(drop = FALSE) 以查看 4 个隐藏帧。
有什么想法出了什么问题或者我应该怎么写吗？ 预先感谢！
如果答案的形式始终是副词属性，那么听起来您不需要引用另一个表格。您可以像这样重塑数据：
library(tidyverse)
dt |>
pivot_longer(-session_id) |>
separate(value, c("degree", "attribute"), sep = " ", extra = "merge") %>%
select(-name) %>%
pivot_wider(names_from = attribute, values_from = degree)
结果
# A tibble: 6 × 18
session_id ugly nervous generous arrogant unambitious dull intelligent joyful distant lazy gloomy calm ambitious modest `good-looking` `hard working` charismatic
<chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 17472631 Modera… Very Slightly Moderat… Slightly Slig… Very Very Very Slig… NA NA NA NA NA NA NA
2 17472632 Modera… NA Slightly NA NA Very Moderately NA Slight… Very Very Mode… Slightly Sligh… NA NA NA
3 17472633 NA NA Very Moderat… Moderately Very Very Sligh… Very NA NA Very NA NA Slightly Slightly NA
4 17472635 Slight… NA Very Very NA NA Moderately Very Modera… Mode… NA Mode… Moderate… NA NA NA Moderately
5 17472636 NA NA Moderat… NA NA NA Moderately Moder… Slight… NA NA Very Very Very Very Moderately Moderately
6 17472638 NA Modera… Moderat… NA NA NA Moderately NA Very Very Moder… NA Slightly Moder… Slightly NA Moderately