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()
和 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()
函数与 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 {
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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 或 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
而 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 v
与 mget
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 unname
d 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
))