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:
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如何data.table
使用循环生成以下结果的新变量?
New_Var_1 = what_ever/hat_ever
New_Var_2 = this_is/who_is
New_Var_3 = wtf_nnn/mmm_nnn
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nm <- names(df)
nm1 <- nm[1:3]
nm2 <- nm[4:6]
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i <- 1
New_Var_names <- paste("New_Var_", i, sep = "")
New_Var <- sprintf("%s/%s", nm1[i], nm2[i])
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DT[,New_Var_names := New_Var]
DT[,cat(New_Var_names) := cat(New_Var)]
DT[,eval(New_Var_names) := eval(New_Var)]
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我建议使用seta for-loop来执行此操作,但在当前稳定版(CRAN)1.8.10版中,set不添加新列.所以,我会做类似的事情:
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]]])
}
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在当前的devel版本(1.8.11)中,set可以添加新列.因此,您不需要使用分配:=.那是:
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]]])
}
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为了完整性,另一种方法是:
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], "]")
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这是更普遍的,你也可以改变运营商/在sprintf和改变by=太条款等它类似于构建一个动态SQL语句,如果没有什么帮助.如果要记录正在执行的动态查询,可以cat在定义中添加a EVAL.