每行对多个变量的乘积求和

Question

我有一个data.table如下：

library(data.table)
set.seed(1)
DT <- data.table(panelID = sample(50,50),                                                    # Creates a panel ID
                      Country = c(rep("Albania",30),rep("Belarus",50), rep("Chilipepper",20)),       
                      some_NA = sample(0:5, 6),                                             
                      some_NA_factor = sample(0:5, 6),         
                      Group = c(rep(1,20),rep(2,20),rep(3,20),rep(4,20),rep(5,20)),
                      Time = rep(seq(as.Date("2010-01-03"), length=20, by="1 month") - 1,5),
                      norm = round(runif(100)/10,2),
                      Income = sample(0:5, 6),
                      Happiness = sample(10,10),
                      Sex = round(rnorm(10,0.75,0.3),2),
                      Age = sample(100,100),
                      Educ = round(rnorm(10,0.75,0.3),2))           
DT [, uniqueID := .I]                                                                        # Creates a unique ID     
DT[DT == 0] <- NA                                                                            # 
DT$some_NA_factor <- factor(DT$some_NA_factor)

现在，我想（出于某些人为原因）使用 data.table 对每次观察的收入和教育以及性别和年龄的乘积求和。请注意，我的实际数据有更多变量，其中一些是 NA。我试过了：

DT<- setDT(DT)[, newvar:= sum((Income *Educ),
   (Sex * Age), na.rm=TRUE)]

但这需要列的总和。我也试过：

DT<- setDT(DT)[, newvar:= rowSums((Income *Educ),
   (Sex * Age), na.rm=TRUE)]

但这不起作用：

Error in base::rowSums(x, na.rm = na.rm, dims = dims, ...) : 
  'x' must be an array of at least two dimensions

在 data.table 中执行此操作的正确方法是什么？

Answer 1

DT[, newvar := rowSums(data.table(Income*Educ, Sex * Age), na.rm=TRUE)]

# ALternatively:
DT[, newvar := {x = Income*Educ; y = Sex * Age; fifelse(is.na(x), y, fifelse(is.na(y), x, x + y ))}]

注：

setDT() 只有在 data.frame 还不是 data.table 时才需要。 <-（在 data.table.

中使用 := 时不需要分配结果

每行对多个变量的乘积求和

Summing the products of multiple variables per row

r

sum

rows

data.table