使用 recode() 和通过 paste() 生成的变量名

问题描述

我正在尝试将包含答案标签的变量作为字符重新编码为数值。为此,我正在使用 dplyr 的 recode()

为了自动执行此操作,我想使用 paste() 生成变量名称,但显然 recode() 无法从 paste 获取输出

我已经尝试过 noquote()as.name() 但对于这两个 R 告诉我重新编码不能使用类“noquote”/“name”的对象。

示例:

item1 <- c("Don't agree at all","Totally agree")
item2 <- c("Indifferent","Totally agree")

for (i in 1:2) {
recode(paste("item",i,sep=""),"Totally agree"=1,"Indifferent"=2,"Don't agree at all"=3)
}

然后我会期待

> item1
  [1] 3 1

我该如何解决这个问题?

更新

我找到了一种解决方法,首先将相关列提取到另一个数据框中,然后将 recode() 函数sapply() 一起应用。现在我可以重新合并数据帧了。

解决方法

关于“但显然 recode() 无法从粘贴中获取输出。”:这与 try { # find element in here WebElement gear = table_row.findElement(By.cssSelector("div.x-grid3-col-5 i.fa-gear")); gear.click(); }catch(StaleElementReferenceException e){ # repeat a gain when it catch the error WebElement gear = table_row.findElement(By.cssSelector("div.x-grid3-col-5 i.fa-gear")); gear.click(); } 无关,但(几乎)any R 函数以这种方式工作。 recode 返回一个字符串,而 paste 期望一个向量作为它的第一个参数......(值得注意的例外,其中包括:recode 我们可以传递一个字符串 库名作为对象)。

如果您坚持使用“for 循环”方法,您可以做的是使用 library 和类似 assign 的组合:

eval(sym("a string"))

结果:

item1 <- c("Don't agree at all","Totally agree")
item2 <- c("Indifferent","Totally agree")


library(dplyr)
for (i in 1:2) {
  assign(paste("item",i,sep=""),recode(eval(sym(paste("item",sep=""))),"Totally agree"=1,"Indifferent"=2,"Don't agree at all"=3))
}

[1] 3 1

item1

[1] 2 1

编辑:

一种可能更直接、更“dplyr”-y 的方法可能是这样的:

item2

tdd <- data.frame(item1,item2) %>% mutate_at(vars(starts_with("item")),~recode(.,"Don't agree at all"=3)) 现在是:

tdd
tdd
,

您只需将命名向量 vmget 中的变量列表一起放入 Map 并对其进行子集化。

v <- c("Totally agree"=1,"Don't agree at all"=3)

Map(function(x,y) unname(y[x]),mget(ls(pattern="^item")),list(v))
# $item1
# [1] 3 1
# 
# $item2
# [1] 2 1

或者,假设您有一个这样的数据框,

head(dat1)
#   id         item1              item2         x
# 1  1 Totally agree      Totally agree 0.0356312
# 2  2 Totally agree      Totally agree 1.3149588
# 3  3 Totally agree        Indifferent 0.9781675
# 4  4 Totally agree        Indifferent 0.8817912
# 5  5   Indifferent        Indifferent 0.4822047
# 6  6   Indifferent Don't agree at all 0.9657529

那么你可以用类似的方式来做这件事。我们甚至可以简化代码,因为我们不再需要 Map 来返回 unnamed 个对象。

v1 <- c("Totally agree"=1,"Don't agree at all"=3)

item_nm <- c("item1","item2")
dat1[item_nm] <- Map(`[`,list(v1),dat2[item_nm])
dat1
#    id item1 item2          x
# 1   1     1     1  0.0356312
# 2   2     1     1  1.3149588
# 3   3     1     2  0.9781675
# 4   4     1     2  0.8817912
# 5   5     2     2  0.4822047
# 6   6     2     3  0.9657529
# 7   7     2     3 -0.8145709
# 8   8     1     1  0.2839578
# 9   9     3     1 -0.1616986
# 10 10     3     3  1.9355718

每个 Map 迭代都会回收第二个参数(即 list(v1,v1) 也可以工作)。

更一般地,对于您想以数字方式重新编码的每一列,在 list 的第二个参数中多 Map 一个向量。

head(dat2)
#   id         item1  item2         x
# 1  1 Totally agree Always 0.0356312
# 2  2 Totally agree Always 1.3149588
# 3  3 Totally agree   Both 0.9781675
# 4  4 Totally agree   Both 0.8817912
# 5  5   Indifferent   Both 0.4822047
# 6  6   Indifferent  Never 0.9657529

v2 <- c("Always"=1,"Both"=2,"Never"=3)

dat2[item_nm] <- Map(`[`,list(v1,v2),dat2[item_nm])
dat2
#    id item1 item2          x
# 1   1     1     1  0.0356312
# 2   2     1     1  1.3149588
# 3   3     1     2  0.9781675
# 4   4     1     2  0.8817912
# 5   5     2     2  0.4822047
# 6   6     2     3  0.9657529
# 7   7     2     3 -0.8145709
# 8   8     1     1  0.2839578
# 9   9     3     1 -0.1616986
# 10 10     3     3  1.9355718

数据:

dat1 <- structure(list(id = 1:10,item1 = c("Totally agree","Totally agree","Indifferent","Don't agree at all","Don't agree at all"
),item2 = c("Totally agree","Don't agree at all"),x = c(0.0356311982051355,1.31495884897891,0.978167526364279,0.881791226863203,0.482204688262918,0.965752878105794,-0.814570938270238,0.283957806364306,-0.161698647607024,1.93557176599585)),class = "data.frame",row.names = c(NA,-10L
))

dat2 <- structure(list(id = 1:10,item2 = c("Always","Always","Both","Never","Never"),-10L
))