问题描述
假设我有以下 data.table
:
dt <- data.table(id = c(rep(1, 5), rep(2, 4)),
sex = c(rep("H", 5), rep("F", 4)),
fruit = c("apple", "tomato", "apple", "apple", "orange", "apple", "apple", "tomato", "tomato"),
key = "id")
id sex fruit
1: 1 H apple
2: 1 H tomato
3: 1 H apple
4: 1 H apple
5: 1 H orange
6: 2 F apple
7: 2 F apple
8: 2 F tomato
9: 2 F tomato
每行代表以下事实:某人(由 id
和性别
)吃了一个水果
。我想计算每个性爱
吃掉每个个水果
的次数。我可以这样:
Each row represents the fact that someone (identified by it's id
and sex
) ate a fruit
. I want to count the number of times each fruit
has been eaten by sex
. I can do it with :
dt[ , .N, by = c("fruit", "sex")]
其中给出:
fruit sex N
1: apple H 3
2: tomato H 1
3: orange H 1
4: apple F 2
5: tomato F 2
问题是,通过这种方式,我失去了<$ sex == F
的c $ c> orange ,因为此计数为0。有没有办法进行这种聚合而不会丢失组合的零计数?
The problem is, by doing it this way I'm losing the count of orange
for sex == "F"
, because this count is 0. Is there a way to do this aggregation without loosing combinations of zero counts?
要完全清楚,期望的结果如下:
To be perfectly clear, the desired result would be the following:
fruit sex N
1: apple H 3
2: tomato H 1
3: orange H 1
4: apple F 2
5: tomato F 2
6: orange F 0
非常感谢!
推荐答案
最简单的方法似乎是在传递给 i =
,将 by = .EACHI
设置为遍历它们:
Seems like the most straightforward approach is to explicitly supply all category combos in a data.table passed to i=
, setting by=.EACHI
to iterate over them:
setkey(dt, sex, fruit)
dt[CJ(sex, fruit, unique = TRUE), .N, by = .EACHI]
# sex fruit N
# 1: F apple 2
# 2: F orange 0
# 3: F tomato 2
# 4: H apple 3
# 5: H orange 1
# 6: H tomato 1
这篇关于与data.table聚合时保持零计数组合的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!