如何在循环调用中使用 data.table 生成变量的线性组合和更新表? [英] How to generate a linear combination of variables and update table using data.table in a loop call?

问题描述

set.seed(123)
df <- data.frame(what_ever = rnorm(5, 50, 1),
                 this_is = rnorm(5, 30, 1),
                 wtf_nnn = rnorm(5, 20, 1),
                 hat_ever = rnorm(5, 50, 1),
                 who_is = rnorm(5, 30, 1),
                 mmm_nnn = rnorm(5, 20, 1)                 
                 )


library(data.table)
DT <- data.table(df)

str(DT)
Classes ‘data.table’ and 'data.frame':  5 obs. of  6 variables:

如何在 data.table 中生成新变量这是以下使用循环的结果?

How can I generate new variables in the data.table that are the result of the following using a loop?

New_Var_1 = what_ever/hat_ever
New_Var_2 = this_is/who_is
New_Var_3 = wtf_nnn/mmm_nnn

我在这里对列名进行排序

nm <- names(df)
nm1 <- nm[1:3]
nm2 <- nm[4:6]

我想以这种方式更新DT，并且循环通过t

i <- 1

New_Var_names <- paste("New_Var_", i, sep = "")
New_Var <- sprintf("%s/%s", nm1[i], nm2[i])

3 次尝试均无效.

DT[,New_Var_names := New_Var]
DT[,cat(New_Var_names) := cat(New_Var)]
DT[,eval(New_Var_names) := eval(New_Var)]

推荐答案

我建议使用带有 for-loop 的 set 来执行此操作，但在当前稳定 (CRAN) 版本 1.8.10，set 不添加新列.所以，我会做这样的事情:

I'd recommend to use set with a for-loop to do this, but on the current stable (CRAN) version 1.8.10, set doesn't add new columns. So, I'd do something like:

require(data.table)
out_names <- paste("newvar", 1:3, sep="_")
DT[, c(out_names) := 0]

invar1 <- names(DT)[1:3]
invar2 <- names(DT)[4:6]

for (i in seq_along(invar1)) {
    set(DT, i=NULL, j=out_names[i], value=DT[[invar1[i]]]/DT[[invar2[i]]])
}

<小时>

在当前的开发版本(1.8.11)中，set可以添加新的列.因此，您不需要使用 := 进行分配.那就是:

---

In the current devel version (1.8.11), set can add new columns. So in that, you don't need the assignment using :=. That is:

require(data.table)
out_names <- paste("newvar", 1:3, sep="_")

invar1 <- names(DT)[1:3]
invar2 <- names(DT)[4:6]

for (i in seq_along(invar1)) {
    set(DT, i=NULL, j=out_names[i], value=DT[[invar1[i]]]/DT[[invar2[i]]])
}

<小时>

为了完整性，另一种方法是:

---

For completeness, another way is :

EVAL = function(...)eval(parse(text=paste0(...)))  # helper function

New_Var_names <- paste("New_Var_", i, sep = "")
New_Var <- sprintf("%s/%s", nm1[i], nm2[i])

for (i in 1:3)
    EVAL("DT[,", New_Var_names[i], ":=", New_Var[i], "]")

这更通用，因为您还可以更改 sprintf 中的运算符 / 并更改 by= 子句等.如果有帮助的话，它类似于构造动态 SQL 语句.如果要记录正在执行的动态查询，可以在 EVAL 的定义中添加 cat.

This is more general in that you can also vary the operator / in the sprintf and vary the by= clause too, etc. It's similar to constructing a dynamic SQL statement, if that helps. If you wanted to log the dynamic query being executed, you could add a cat in your definition of EVAL.

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