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涉及因素的data.table赋值

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我正在使用 data.table (1.8.9)和 := 运算符来更新另一个表中的值 . 要更新的表(dt1)有许多因子列,带有更新的表(dt2)具有类似的列,其值可能不存在于另一个表中 . 如果dt2中的列是字符,我会收到一条错误消息,但是当我将它们分解时,我会得到不正确的值 .

如何在不将所有因子首先转换为字符的情况下更新表格?

这是一个简化的例子:

library(data.table)

set.seed(3957)

## Create some sample data
## Note column y is a factor
dt1<-data.table(x=1:10,y=factor(sample(letters,10)))
dt1

##      x y
##  1:  1 m
##  2:  2 z
##  3:  3 t
##  4:  4 b
##  5:  5 l
##  6:  6 a
##  7:  7 s
##  8:  8 y
##  9:  9 q
## 10: 10 i

setkey(dt1,x)

set.seed(9068)

## Create a second table that will be used to update the first one.
## Note column y is not a factor
dt2<-data.table(x=sample(1:10,5),y=sample(letters,5))
dt2

##    x y
## 1: 2 q
## 2: 7 k
## 3: 3 u
## 4: 6 n
## 5: 8 t

## Join the first and second tables on x and attempt to update column y
## where there is a match
dt1[dt2,y:=i.y]

## Error in `[.data.table`(dt1, dt2, `:=`(y, i.y)) : 
##   Type of RHS ('character') must match LHS ('integer'). To check and
## coerce would impact performance too much for the fastest cases. Either
## change the type of the target column, or coerce the RHS of := yourself
## (e.g. by using 1L instead of 1)

## Create a third table that is the same as the second, except y
## is also a factor
dt3<-copy(dt2)[,y:=factor(y)]

## Join the first and third tables on x and attempt to update column y
## where there is a match
dt1[dt3,y:=i.y]
dt1

##      x y
##  1:  1 m
##  2:  2 i
##  3:  3 m
##  4:  4 b
##  5:  5 l
##  6:  6 b
##  7:  7 a
##  8:  8 l
##  9:  9 q
## 10: 10 i

## No error message this time, but it is using the levels and not the labels
## from dt3.  For example, row 2 should be q but it is i.

data.table help file的第3页说:

当LHS是因子列且RHS是因子级别缺少项目的字符向量时,与基本方法不同,新级别会自动添加(通过引用,有效) .

这使得它看起来像我试过的应该工作,但显然我错过了一些东西 . 我想知道这是否与这个类似的问题有关:

rbindlist two data.tables where one has factor and other has character type for a column

1 回答

  • 1

    这是一个解决方法:

    dt1[dt2, z := i.y][!is.na(z), y := z][, z := NULL]
    

    请注意 z 是一个字符列,第二个赋值按预期工作,不确定OP为什么没有 .

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