如何在 R 中编写一个重新编码多个变量的 for 循环？

Question

我是一名自学成才的程序员，在 MATLAB 方面有几年的经验。我是 R 的新手，这是我在 Stack Overflow 上的第一个问题。

我正在尝试使用来自 dplyr 的 recode 重新编码数据框中的多个变量。在下面的代码中，我提供了一个 data 的 sn-p 和我想与 recode 一起使用的选项列表 opt_dass。我想将每个变量中以“dass”开头的字符串值转换为数字 - 从不 = 0，有时 = 1，等等。

我知道有多种方法可以解决这个问题，包括ifelse、lapply 和case_when。在下面的示例中，我想知道为什么会收到有关非语言对象的错误。我正在使用paste0 创建要在data 中引用的变量名。我已经阅读了大量有关如何在 R 中的 for 循环中引用列名的信息，但我仍然没有找到答案。

library(tidyverse)

data <- structure(list(id = c("1", "2", "3", "4", "5", "6", "7", "8", 
                              "9", "11"), dass1_t1 = c("Sometimes", "Often", "Often", "Almost Always", 
                                                       "Sometimes", "Sometimes", "Sometimes", "Sometimes", "Sometimes", 
                                                       "Sometimes"), dass2_t1 = c("Sometimes", "Never", "Often", "Sometimes", 
                                                                                  "Sometimes", "Never", "Sometimes", "Sometimes", "Often", "Sometimes"
                                                       ), dass3_t1 = c("Often", "Sometimes", "Never", "Never", "Never", 
                                                                       "Sometimes", "Never", "Never", "Sometimes", "Sometimes"), dass4_t1 = c("Never", 
                                                                                                                                              "Never", "Never", "Never", "Never", "Sometimes", "Never", "Never", 
                                                                                                                                              "Never", "Sometimes"), dass5_t1 = c("Almost Always", "Sometimes", 
                                                                                                                                                                                  "Never", "Sometimes", "Never", "Sometimes", "Sometimes", "Never", 
                                                                                                                                                                                  "Almost Always", "Often")), row.names = c(NA, -10L), class = "data.frame")

opt_dass <- list("Never"=0,"Sometimes"=1,"Often"=2,"Almost Always"=3) # list - chr to num

# my attempt at a for loop to recode
for (i in 1:5) {
  attach(data)
  paste0("dass_", i, "_t1") <- recode(paste0("dass_", i, "_t1"), !!!opt_dass, .default=NA_real_)
}

#> Error in paste0("dass_", i, "_t1") <- recode(paste0("dass_", i, "_t1"), : target of assignment expands to non-language object

^{由reprex package (v0.3.0) 于 2020 年 11 月 4 日创建}

额外问题：有没有办法编写一个for 循环，可以完成对具有不同选项集的多组变量进行重新编码？我有一个包含多个自我报告度量的数据集，其中不同的字符串响应具有不同的数值。我认为这将涉及一些元编程，并且很想听听您的想法！

Answer 1

首先，使用命名向量而不是命名列表

opt_dass <- c("Never"=0,"Sometimes"=1,"Often"=2,"Almost Always"=3)

那么就

mutate(data, across(starts_with("dass"), ~unname(opt_dass[.])))

输出

   id dass1_t1 dass2_t1 dass3_t1 dass4_t1 dass5_t1
1   1        1        1        2        0        3
2   2        2        0        1        0        1
3   3        2        2        0        0        0
4   4        3        1        0        0        1
5   5        1        1        0        0        0
6   6        1        0        1        1        1
7   7        1        1        0        0        1
8   8        1        1        0        0        0
9   9        1        2        1        0        3
10 11        1        1        1        1        2

Answer 2

我可能只是将它们设为因数，然后使用底层整数代码（减 1）：

data %>%
    mutate_at(.vars = vars(starts_with("dass")),
                        .funs = ~factor(x = .,levels = c("Never","Sometimes","Often","Almost Always"))) %>%
    mutate_at(.vars = vars(starts_with("dass")),
                        .funs = ~as.integer(.) - 1)

Answer 3

从宽到长重塑，重新编码，然后再从长到宽重塑：

pivot_longer(data, cols = -1) %>% 
  mutate(value = recode(value, "Never"=0,"Sometimes"=1,
                        "Often"=2,"Almost Always"=3)) %>% 
  pivot_wider(., id_cols = "id")

# # A tibble: 10 x 6
#    id    dass1_t1 dass2_t1 dass3_t1 dass4_t1 dass5_t1
#    <chr>    <dbl>    <dbl>    <dbl>    <dbl>    <dbl>
#  1 1            1        1        2        0        3
#  2 2            2        0        1        0        1
#  3 3            2        2        0        0        0
#  4 4            3        1        0        0        1
#  5 5            1        1        0        0        0
#  6 6            1        0        1        1        1
#  7 7            1        1        0        0        1
#  8 8            1        1        0        0        0
#  9 9            1        2        1        0        3
# 10 11           1        1        1        1        2

Answer 4

我真的很喜欢 qdapTools 包中的 lookup() 函数用于重新编码。以下是如何将它用于您的用例：

library(tidyverse)
library(qdapTools)

data <- structure(
  list(
    id = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "11"),
    dass1_t1 = c(
      "Sometimes", "Often", "Often", "Almost Always", "Sometimes", "Sometimes",
      "Sometimes", "Sometimes", "Sometimes", "Sometimes"
    ),
    dass2_t1 = c(
      "Sometimes", "Never", "Often", "Sometimes", "Sometimes", "Never", 
      "Sometimes", "Sometimes", "Often", "Sometimes"
    ),
    dass3_t1 = c(
      "Often", "Sometimes", "Never", "Never", "Never", "Sometimes", "Never",
      "Never", "Sometimes", "Sometimes"
    ),
    dass4_t1 = c(
      "Never", "Never", "Never", "Never", "Never", "Sometimes", "Never", 
      "Never", "Never", "Sometimes"
    ),
    dass5_t1 = c(
      "Almost Always", "Sometimes", "Never", "Sometimes", "Never", "Sometimes",
      "Sometimes", "Never", "Almost Always", "Often"
    )
  ),
  row.names = c(NA, -10L),
  class = "data.frame"
)

opt_dass <- list(
  `0` = "Never", `1` = "Sometimes", `2` = "Often", `3` = "Almost Always"
)

data %>% 
  mutate(across(dass1_t1:dass5_t1, ~ as.numeric(lookup(.x, opt_dass))))
#>    id dass1_t1 dass2_t1 dass3_t1 dass4_t1 dass5_t1
#> 1   1        1        1        2        0        3
#> 2   2        2        0        1        0        1
#> 3   3        2        2        0        0        0
#> 4   4        3        1        0        0        1
#> 5   5        1        1        0        0        0
#> 6   6        1        0        1        1        1
#> 7   7        1        1        0        0        1
#> 8   8        1        1        0        0        0
#> 9   9        1        2        1        0        3
#> 10 11        1        1        1        1        2

^{由reprex package (v0.3.0) 于 2020 年 11 月 4 日创建}

要了解有关lookup() 功能的更多信息，请查看qdapTool's reference manual。

Answer 5

您看到的错误是因为您不能使用表达式来构建 要分配给<- 左侧的变量的名称。更多 详情见this answer。

要重新编码多个变量，您可以存储重新编码映射 在一个命名列表中，其中包含您要重新编码的每个变量的元素：

recodes <- list(
  q1 = c(a = 1, b = 2, c = 3),
  q2 = c(x = 9, y = 8, z = 7)
)

tbl <- data.frame(
  id = c(1, 2, 3),
  q1 = c("b", "a", "c"),
  q2 = c("z", "z", "x")
)

tbl
#>   id q1 q2
#> 1  1  b  z
#> 2  2  a  z
#> 3  3  c  x

然后遍历数据中的变量，并选择重新编码映射 根据变量名从列表中使用：

for (variable in names(tbl)) {
  if (!variable %in% names(recodes)) {
    next # skip if the variable isn't recoded
  }
  
  new_variable <- paste0(variable, "n")
  
  old_value <- tbl[[variable]]
  new_value <- recodes[[variable]][old_value]
  
  tbl[[new_variable]] <- new_value
}

tbl
#>   id q1 q2 q1n q2n
#> 1  1  b  z   2   7
#> 2  2  a  z   1   7
#> 3  3  c  x   3   9