r data.table lapply 或 for 循环创建变量或生成列

Question

我想使用 R data.table 的公式创建多个变量。我有一个变量列表，对于每个变量，我想执行计算并创建一个新变量，将相同的字符串粘贴到每个列名称上。我可以让它一次适用于一个变量，但它不适用于 lapply 或循环。我怀疑我丢失了 R data.table 和引号或变量名与字符串的内容。我需要使用“..”还是用 eval() 换行？ dplyr(或任何 tidyverse)解决方案也可以解决该问题。

这里是 mtcars 的示例代码:

library(data.table)
mtcars.dt <- setDT(mtcars)
myVars <- c("mpg", "hp", "qsec")

# Doesn't work:
for( myVar in myVars){
  mtcars.dt[, paste0(myVar, ".disp.ratio") := myVar / disp]
}

# Doesn't work:
lapply(myVars, function(myVar) mtcars.dt[, paste0(myVar, ".disp.ratio") := myVar / disp])

# Works:
mtcars.dt[, mpg.disp.ratio := mpg / disp]

# Doesn't work
for (myVar in myVars){
  mtcars.dt[, paste0(myVar, ".disp.lm.adj") := 
              myVar - 
              lm(data = .SD, formula = myVar ~ disp)$coefficients[2] * (disp - mean(disp))]
}

# Doesn't work
lapply(myVars, function(x) mtcars.dt[, paste0(x, ".disp.lm.adj") := 
                                       x - 
                                       lm(data = .SD, formula = x ~ disp)$coefficients[2] * (disp - mean(disp))])

# Works
mtcars.dt[, mpg.disp.lm.adj := 
            mpg - 
            lm(data = .SD, formula = mpg ~ disp)$coefficients[2] * (disp - mean(disp))]

对于比率计算，我得到以下错误:

Error in myVar/disp : non-numeric argument to binary operator 

对于 lm 调整，我收到以下错误:

Error in model.frame.default(formula = myVar ~ disp, data = .SD, drop.unused.levels = TRUE) : 
  variable lengths differ (found for 'disp')

Answer 1

我们可以使用get

library(data.table)
for( myVar in myVars){
   mtcars.dt[, paste0(myVar, ".disp.ratio") := get(myVar) / disp]
  }

或者转换为symbol后用eval换行

for( myVar in myVars){
   mtcars.dt[, paste0(myVar, ".disp.ratio") := eval(as.name(myVar)) / disp]
  }

---

或者另一种选择是在.SDcols中指定，循环遍历.SD(Data.table的子集，进行转换并通过赋值创建新变量( :=)

mtcars.dt[, paste0(myVars, ".disp.ratio") := lapply(.SD, `/`, disp), 
             .SDcols = myVars]

---

对于第二种情况，我们可以使用paste创建公式

for (myVar in myVars) {
  mtcars.dt[, paste0(myVar, ".disp.lm.adj") := 
              get(myVar) - 
              lm(data = .SD, formula = paste(myVar,  "~ disp"))$coefficients[2] *
               (disp - mean(disp))]
}