对具有变量列名称的数据表执行操作 [英] Operations on data table with variable column name
问题描述
我试图对作为变量传递的 data.table
的列执行操作。
这里是一个玩具示例:
)
set.seed(2)
DT< - data.table(replicate(3,runif(4)))
> DT
V1 V2 V3
V1 V2 V3
1:0.1848823 0.9438393 0.4680185
2:0.7023740 0.9434750 0.5499837
3:0.5733263 0.1291590 0.5526741
4:0.1680519 0.8334488 0.2388948
假设感兴趣的列作为变量的值传递:
> print(target.column< - sample(colnames(DT),1))
[1]V3
因此,我想对列 V3
执行一些操作,为了简单起见,将值置于0.5。我已经成功地通过使用可怕的粘贴
, parse
和 eval
:
> eval(parse(text = paste0(DT [,target.column,< 0.5,target.column,:= 0.5,])))
V1 V2 V3
1 :0.1848823 0.9438393 0.5000000
2:0.7023740 0.9434750 0.5499837
3:0.5733263 0.1291590 0.5526741
4:0.1680519 0.8334488 0.5000000
但在我的其他尝试中未能成功:
DT [eval(target.column) 0.5,eval(target.column):= 0.5,]
V1 V2 V3
1:0.1848823 0.9438393 0.4680185
2:0.7023740 0.9434750 0.5499837
3:0.5733263 0.1291590 0.5526741
4:0.1680519 0.8334488 0.2388948
> DT [as.name(target.column) 0.5,as.name(target.column):= 0.5,]
V1 V2 V3
1:0.1848823 0.9438393 0.4680185
2:0.7023740 0.9434750 0.5499837
3:0.5733263 0.1291590 0.5526741
4:0.1680519 0.8334488 0.2388948
> DT [deparse(substitute(target.column))& 0.5,deparse(substitute(target.column)):= 0.5,]
V1 V2 V3
1:0.1848823 0.9438393 0.4680185
2:0.7023740 0.9434750 0.5499837
3:0.5733263 0.1291590 0.5526741
4:0.1680519 0.8334488 0.2388948
我在SO和ol的interweb没有找到任何有用的东西...是否有一个data.table方法来做这个?
可以使用
DT [get(target.column)< .5,(target.column):= .5]
p>
I am trying to perform operations on a data.table
's column that is passed as a variable.
Here is a toy example:
library(data.table)
set.seed(2)
DT <- data.table(replicate(3, runif(4)))
> DT
V1 V2 V3
1: 0.1848823 0.9438393 0.4680185
2: 0.7023740 0.9434750 0.5499837
3: 0.5733263 0.1291590 0.5526741
4: 0.1680519 0.8334488 0.2388948
Say the column of interest is passed as the value of a variable:
> print(target.column <- sample(colnames(DT), 1))
[1] "V3"
So I would like to perform some operation on column V3
, say, flooring the value at 0.5 for simplicity. I have successfully made this work by using the dreaded paste
, parse
and eval
:
> eval(parse(text = paste0("DT[", target.column, " < 0.5, ", target.column, " := 0.5, ]")))
V1 V2 V3
1: 0.1848823 0.9438393 0.5000000
2: 0.7023740 0.9434750 0.5499837
3: 0.5733263 0.1291590 0.5526741
4: 0.1680519 0.8334488 0.5000000
But have been unsuccessful in my other attempts:
> DT[eval(target.column) < 0.5, eval(target.column) := 0.5, ]
V1 V2 V3
1: 0.1848823 0.9438393 0.4680185
2: 0.7023740 0.9434750 0.5499837
3: 0.5733263 0.1291590 0.5526741
4: 0.1680519 0.8334488 0.2388948
> DT[as.name(target.column) < 0.5, as.name(target.column) := 0.5, ]
V1 V2 V3
1: 0.1848823 0.9438393 0.4680185
2: 0.7023740 0.9434750 0.5499837
3: 0.5733263 0.1291590 0.5526741
4: 0.1680519 0.8334488 0.2388948
> DT[deparse(substitute(target.column)) < 0.5, deparse(substitute(target.column)) := 0.5, ]
V1 V2 V3
1: 0.1848823 0.9438393 0.4680185
2: 0.7023740 0.9434750 0.5499837
3: 0.5733263 0.1291590 0.5526741
4: 0.1680519 0.8334488 0.2388948
I have looked for solutions on SO and the ol' interweb have not been able to find anything useful... is there a "data.table" way to do this?
You can use
DT[ get(target.column) < .5, (target.column) := .5]
which gives the desired result.
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