dplyr 总结:相当于“.drop=FALSE"在输出中保留零长度的组 [英] dplyr summarise: Equivalent of ".drop=FALSE" to keep groups with zero length in output

问题描述

当将 summarise 与 plyr 的 ddply 函数一起使用时，默认情况下会删除空类别.您可以通过添加 .drop = FALSE 来更改此行为.但是，这在将 summarise 与 dplyr 一起使用时不起作用.有没有其他方法可以在结果中保留空类别?

When using summarise with plyr's ddply function, empty categories are dropped by default. You can change this behavior by adding .drop = FALSE. However, this doesn't work when using summarise with dplyr. Is there another way to keep empty categories in the result?

这里有一个虚假数据的例子.

Here's an example with fake data.

library(dplyr)

df = data.frame(a=rep(1:3,4), b=rep(1:2,6))

# Now add an extra level to df$b that has no corresponding value in df$a
df$b = factor(df$b, levels=1:3)

# Summarise with plyr, keeping categories with a count of zero
plyr::ddply(df, "b", summarise, count_a=length(a), .drop=FALSE)

  b    count_a
1 1    6
2 2    6
3 3    0

# Now try it with dplyr
df %.%
  group_by(b) %.%
  summarise(count_a=length(a), .drop=FALSE)

  b     count_a .drop
1 1     6       FALSE
2 2     6       FALSE

不完全是我所希望的.是否有 dplyr 方法可以实现与 plyr 中的 .drop=FALSE 相同的结果?

Not exactly what I was hoping for. Is there a dplyr method for achieving the same result as .drop=FALSE in plyr?

推荐答案

自从 dplyr 0.8 group_by 获得了 .drop 参数您的要求:

Since dplyr 0.8 group_by gained the .drop argument that does just what you asked for:

df = data.frame(a=rep(1:3,4), b=rep(1:2,6))
df$b = factor(df$b, levels=1:3)

df %>%
  group_by(b, .drop=FALSE) %>%
  summarise(count_a=length(a))

#> # A tibble: 3 x 2
#>   b     count_a
#>   <fct>   <int>
#> 1 1           6
#> 2 2           6
#> 3 3           0

@Moody_Mudskipper 的回答还有一个附加说明:当一个或多个分组变量未编码为因子时，使用 .drop=FALSE 可能会产生潜在的意外结果.请参阅以下示例:

One additional note to go with @Moody_Mudskipper's answer: Using .drop=FALSE can give potentially unexpected results when one or more grouping variables are not coded as factors. See examples below:

library(dplyr)
data(iris)

# Add an additional level to Species
iris$Species = factor(iris$Species, levels=c(levels(iris$Species), "empty_level"))

# Species is a factor and empty groups are included in the output
iris %>% group_by(Species, .drop=FALSE) %>% tally

#>   Species         n
#> 1 setosa         50
#> 2 versicolor     50
#> 3 virginica      50
#> 4 empty_level     0

# Add character column
iris$group2 = c(rep(c("A","B"), 50), rep(c("B","C"), each=25))

# Empty groups involving combinations of Species and group2 are not included in output
iris %>% group_by(Species, group2, .drop=FALSE) %>% tally

#>   Species     group2     n
#> 1 setosa      A         25
#> 2 setosa      B         25
#> 3 versicolor  A         25
#> 4 versicolor  B         25
#> 5 virginica   B         25
#> 6 virginica   C         25
#> 7 empty_level <NA>       0

# Turn group2 into a factor
iris$group2 = factor(iris$group2)

# Now all possible combinations of Species and group2 are included in the output, 
#  whether present in the data or not
iris %>% group_by(Species, group2, .drop=FALSE) %>% tally

#>    Species     group2     n
#>  1 setosa      A         25
#>  2 setosa      B         25
#>  3 setosa      C          0
#>  4 versicolor  A         25
#>  5 versicolor  B         25
#>  6 versicolor  C          0
#>  7 virginica   A          0
#>  8 virginica   B         25
#>  9 virginica   C         25
#> 10 empty_level A          0
#> 11 empty_level B          0
#> 12 empty_level C          0

Created on 2019-03-13 by the reprex package (v0.2.1)

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