在 tidyr/dplyr 中添加零计数行的正确习惯用法 [英] Proper idiom for adding zero count rows in tidyr/dplyr

问题描述

假设我有一些看起来像这样的计数数据:

Suppose I have some count data that looks like this:

library(tidyr)
library(dplyr)

X.raw <- data.frame(
    x = as.factor(c("A", "A", "A", "B", "B", "B")),
    y = as.factor(c("i", "ii", "ii", "i", "i", "i")),
    z = 1:6)
X.raw
#   x  y z
# 1 A  i 1
# 2 A ii 2
# 3 A ii 3
# 4 B  i 4
# 5 B  i 5
# 6 B  i 6

我想整理和总结如下:

X.tidy <- X.raw %>% group_by(x,y) %>% summarise(count=sum(z))
X.tidy
# Source: local data frame [3 x 3]
# Groups: x
#
#   x  y count
# 1 A  i     1
# 2 A ii     5
# 3 B  i    15

我知道对于 x=="B" 和 y=="ii" 我们观察到计数为零，而不是缺失值.即现场工作人员实际上在那里，但是因为没有正数，所以没有将行输入到原始数据中.我可以通过这样做显式添加零计数:

I know that for x=="B" and y=="ii" we have observed count of zero, rather than a missing value. i.e. the field worker was actually there, but because there wasn't a positive count no row was entered into the raw data. I can add the zero count explicitly by doing this:

X.fill <- X.tidy %>% spread(y, count, fill=0) %>% gather(y, count, -x)
X.fill
# Source: local data frame [4 x 3]
# 
#   x  y count
# 1 A  i     1
# 2 B  i    15
# 3 A ii     5
# 4 B ii     0

但这似乎有点迂回的做事方式.他们是不是更简洁的成语?

But that seems a little bit of a roundabout way of doing things. Is their a cleaner idiom for this?

澄清一下:我的代码已经做了我需要它做的事情，使用spread然后gather，所以我感兴趣的是找到一条更直接的路线内 tidyr 和 dplyr.

Just to clarify: My code already does what I need it to do, using spread then gather, so what I'm interested in is finding a more direct route within tidyr and dplyr.

推荐答案

自从 dplyr 0.8 你可以通过设置参数 .drop = FALSE<group_by 中的/code>:

Since dplyr 0.8 you can do it by setting the parameter .drop = FALSE in group_by:

X.tidy <- X.raw %>% group_by(x, y, .drop = FALSE) %>% summarise(count=sum(z))
X.tidy
# # A tibble: 4 x 3
# # Groups:   x [2]
#   x     y     count
#   <fct> <fct> <int>
# 1 A     i         1
# 2 A     ii        5
# 3 B     i        15
# 4 B     ii        0

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