r - 将函数应用于数据框列表中的每个因子级别

Question

我的数据框具有多个级别的因素race和group，下面是最小的示例:

   id     race group
1   1    White     1
2   2    White     1
3   3    White     1
4   4    White     1
5   5    White     1
6   6    White     2
7   7    White     2
8   8    White     2
9   9    White     2
10 10    Black     1
11 11    Black     1
12 12    Black     1
13 13    Black     2
14 14    Black     2
15 15    Black     2
16 16    Black     2
17 17 Hispanic     1
18 18 Hispanic     1
19 19 Hispanic     1
20 20 Hispanic     1
21 21 Hispanic     1
22 22 Hispanic     2
23 23 Hispanic     2
24 24 Hispanic     2
25 25 Hispanic     2

我可以使用“White”对每个race级别进行分组的单个数据帧，然后使用以下函数按group拆分数据。

filter.race <- function(x, y) { f <- subset(x, race == "White" | race == y)
    f <- split(f, f$group)
    f} 

返回结果:

filter.race(df, "Black")

$`1`
   id  race group
1   1 White     1
2   2 White     1
3   3 White     1
4   4 White     1
5   5 White     1
10 10 Black     1
11 11 Black     1
12 12 Black     1

$`2`
   id  race group
6   6 White     2
7   7 White     2
8   8 White     2
9   9 White     2
13 13 Black     2
14 14 Black     2
15 15 Black     2
16 16 Black     2

filter.race(df, "Hispanic")

$`1`
   id     race group
1   1    White     1
2   2    White     1
3   3    White     1
4   4    White     1
5   5    White     1
17 17 Hispanic     1
18 18 Hispanic     1
19 19 Hispanic     1
20 20 Hispanic     1
21 21 Hispanic     1

$`2`
   id     race group
6   6    White     2
7   7    White     2
8   8    White     2
9   9    White     2
22 22 Hispanic     2
23 23 Hispanic     2
24 24 Hispanic     2
25 25 Hispanic     2

但是，我正在尝试找到一种方法来将此函数应用于数据帧的所有级别，而不是多次单独指定 y 。

示例数据:

dput(df)
structure(list(id = 1:25, race = structure(c(3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L), .Label = c("Black", "Hispanic", "White"), class = "factor"), 
    group = c(1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 
    2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L)), .Names = c("id", 
"race", "group"), class = "data.frame", row.names = c(NA, -25L
))

Answer 1

考虑by(面向对象的包装器tapply)最初和在race和group中划分子集每次迭代rbind每个相应组的White。对于White组织本身，unique可以消除重复数据。

df_list <- by(df, df[c("race", "group")], function(sub) {    
    unique(
           rbind(subset(df, race == "White" & group == sub$group[1]),
                 sub)
    )
})

# race: Black
# group: 1
# id  race group
# 1   1 White     1
# 2   2 White     1
# 3   3 White     1
# 4   4 White     1
# 5   5 White     1
# 10 10 Black     1
# 11 11 Black     1
# 12 12 Black     1
# ------------------------------------------------------------ 
# race: Hispanic
# group: 1
# id     race group
# 1   1    White     1
# 2   2    White     1
# 3   3    White     1
# 4   4    White     1
# 5   5    White     1
# 17 17 Hispanic     1
# 18 18 Hispanic     1
# 19 19 Hispanic     1
# 20 20 Hispanic     1
# 21 21 Hispanic     1
# ------------------------------------------------------------ 
# race: White
# group: 1
# id  race group
# 1  1 White     1
# 2  2 White     1
# 3  3 White     1
# 4  4 White     1
# 5  5 White     1
# ------------------------------------------------------------ 
#   race: Black
# group: 2
# id  race group
# 6   6 White     2
# 7   7 White     2
# 8   8 White     2
# 9   9 White     2
# 13 13 Black     2
# 14 14 Black     2
# 15 15 Black     2
# 16 16 Black     2
# ------------------------------------------------------------ 
# race: Hispanic
# group: 2
# id     race group
# 6   6    White     2
# 7   7    White     2
# 8   8    White     2
# 9   9    White     2
# 22 22 Hispanic     2
# 23 23 Hispanic     2
# 24 24 Hispanic     2
# 25 25 Hispanic     2
# ------------------------------------------------------------ 
# race: White
# group: 2
# id  race group
# 6  6 White     2
# 7  7 White     2
# 8  8 White     2
# 9  9 White     2