Doing a merge between a populated data.table and another one that is empty introduces one NA row in the resulting data.table:
a = data.table(c=c(1,2),key='c')
b = data.table(c=3,key='c')
b=b[c!=3]
b
# Empty data.table (0 rows) of 1 col: c
merge(a,b,all=T)
# c
# 1: NA
# 2: 1
# 3: 2
Why? I expected that it would return only the rows of data.table a
, as it does with merge.data.frame:
> merge.data.frame(a,b,all=T,by='c')
# c
#1 1
#2 2
The example in the question is far too simple to show the problem, hence the confusion and discussion. Using two one-column data.table
s isn't enough to show what merge
does!
Here's a better example :
> a = data.table(P=1:2,Q=3:4,key='P')
> b = data.table(P=2:3,R=5:6,key='P')
> a
P Q
1: 1 3
2: 2 4
> b
P R
1: 2 5
2: 3 6
> merge(a,b) # correct
P Q R
1: 2 4 5
> merge(a,b,all=TRUE) # correct.
P Q R
1: 1 3 NA
2: 2 4 5
3: 3 NA 6
> merge(a,b[0],all=TRUE) # incorrect result when y is empty, agreed
P Q R
1: NA NA NA
2: NA NA NA
3: 1 3 NA
4: 2 4 NA
> merge.data.frame(a,b[0],all=TRUE) # correct
P Q R
1 1 3 NA
2 2 4 NA
Ricardo got to the bottom of this and fixed it in v1.8.9. From NEWS :
merge no longer returns spurious NA row(s) when y is empty and all.y=TRUE (or all=TRUE), #2633. Thanks to Vinicius Almendra for reporting. Test added.