在处理NaN时，data.table“list”与“：=”

Noticed some weird behavior of data.table, hopefully someone who understands data.table better than I can explain.

注意到data.table的一些奇怪的行为，希望有人比我能解释的更了解data.table。

Say I have this data.table:

说我有这个data.table：

library(data.table)
DT <- data.table(
  C1 = c(rep("A", 4), rep("B",4), rep("C", 4)),
  C2 = c(rep("a", 3), rep("b",3), rep("c",3), rep("d",3)),
  Val = c(1:5, NaN, NaN, 8,9,10,NaN,12))

DT
    C1 C2 Val
 1:  A  a   1
 2:  A  a   2
 3:  A  a   3
 4:  A  b   4
 5:  B  b   5
 6:  B  b NaN
 7:  B  c NaN
 8:  B  c   8
 9:  C  c   9
10:  C  d  10
11:  C  d NaN
12:  C  d  12

Now, in my mind, the following two methods should generate the same results, but they do not.

现在，在我看来，以下两种方法应该生成相同的结果，但它们不会。

TEST1 <- DT[, agg := min(Val, na.rm = TRUE), by = c('C1', 'C2')]
TEST1 <- data.table(unique(TEST1[, c('C1','C2','agg'), with = FALSE]))

TEST2 <- DT[, list(agg = min(Val, na.rm = TRUE)), by = c('C1', 'C2')]

TEST1
   C1 C2 agg
1:  A  a   1
2:  A  b   4
3:  B  b   5
4:  B  c   8
5:  C  c   9
6:  C  d  10


TEST2
   C1 C2 agg
1:  A  a   1
2:  A  b   4
3:  B  b   5
4:  B  c NaN
5:  C  c   9
6:  C  d  10

As you can see, using " := " generates a minimum value for (C1 = B, C2 = c) of 8. Whereas the list command results in an NaN. Funnily enough, for (C1 = B,C2 = b) and (C1 = C, C2 = d), which also have NaNs, the list command does produce a value. I believe this to be because in the instance where the NaN is first before a value for a given C1 C2 combination, the NaN results. Whereas in the other two examples the NaN comes after a value.

如您所见，使用“：=”会为（C1 = B，C2 = c）生成最小值8.而list命令会生成NaN。有趣的是，对于（C1 = B，C2 = b）和（C1 = C，C2 = d），它们也有NaNs，list命令确实产生一个值。我相信这是因为在NaN首先在给定C1 C2组合的值之前的情况下，NaN结果。而在另外两个例子中，NaN来自一个值。

Why does this occur?

为什么会这样？

I note that if the NaN are replaced with NA then values are generated with no problems.

我注意到如果用NA替换NaN，则生成的值没有问题。

1 个解决方案

#1

Fixed this issue, #1461 just now in devel, v1.9.7 with commit 2080.

修复了这个问题，＃1461刚刚开发，v1.9.7，提交2080。

require(data.table) # v1.9.7, commit 2080+
DT <- data.table(
     C1 = c(rep("A", 4), rep("B",4), rep("C", 4)),
     C2 = c(rep("a", 3), rep("b",3), rep("c",3), rep("d",3)),
     Val = c(1:5, NaN, NaN, 8,9,10,NaN,12))

DT[, list(agg = min(Val, na.rm = TRUE)), by = c('C1', 'C2')]
#    C1 C2 agg
# 1:  A  a   1
# 2:  A  b   4
# 3:  B  b   5
# 4:  B  c   8
# 5:  C  c   9
# 6:  C  d  10