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是因子列时,RHS是带有项目的字符向量 从因子级别中丢失,新级别是自动的 与基本方法不同,(通过引用,有效地)添加。
这使得它看起来像我尝试过应该工作,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
答案 0 :(得分:1)
这是一种解决方法:
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。