data.table和表意外行为 [英] data.table and table unexpected behavior

问题描述

资料来自另一个我正在玩的问题：

The data comes from another question I was playing around with:

dt <- data.table(user=c(rep(3, 5), rep(4, 5)),
                 country=c(rep(1,4),rep(2,6)),
                 event=1:10, key="user")
#    user country event
#1:     3       1     1
#2:     3       1     2
#3:     3       1     3
#4:     3       1     4
#5:     3       2     5
#6:     4       2     6
#7:     4       2     7
#8:     4       2     8
#9:     4       2     9
#10:    4       2    10

这是令人惊讶的行为： p>

And here's the surprising behavior:

dt[user == 3, as.data.frame(table(country))]
#  country Freq
#1       1    4
#2       2    1

dt[user == 4, as.data.frame(table(country))]
#  country Freq
#1       2    5

dt[, as.data.frame(table(country)), by = user]
#   user country Freq
#1:    3       1    4
#2:    3       2    1
#3:    4       1    5
#             ^^^ - why is this 1 instead of 2?!

感谢mnel和Victor K.自然的跟进是 - 不应该是2，这是一个bug？我预期

Thanks mnel and Victor K. The natural follow-up is - shouldn't it be 2, i.e. is this a bug? I expected

dt[, blah, by = user]

返回相同的结果到

rbind(dt[user == 3, blah], dt[user == 4, blah])

/ p>

Is that expectation incorrect?

推荐答案

惯用的data.table方法是使用.N

The idiomatic data.table approach is to use .N

 dt[ , .N, by = list(user, country)]

这会更快，它也会保留国家作为与原来相同的类。

This will be far quicker and it will also retain country as the same class as in the original.

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