我想知道每个id_b的主导类是什么。要计算它，我需要找出每个id_bsizeperclass之和。无论哪个类最大，都是分配给id_b的新的主导类。
下面的脚本做了我想做的事情，但感觉很笨重，过于复杂。我以前很少使用嵌套数据，所以我不确定我是否使用了最好的方法。有人能想出一种更整洁的方法来在tidyverse或data.table中实现相同的输出吗？
谢谢！
library(tidyverse)
# sample data
set.seed(123)
input <- tibble(id_a = c(letters[seq(1,10)]),
size = runif(10, min = 10, max = 50),
class = c("x","x","y","x","y",
"y","x","y","x","x"),
id_b = c("A1","A1","B1","B1","B1",
"C1","C1","C1","D1","E1"))
print(input)
id_a size class id_b
<chr> <dbl> <chr> <chr>
1 a 23.6 x A1
2 b 43.6 x A1
3 c 23.9 y B1
4 d 23.4 x B1
5 e 29.1 y B1
6 f 45.7 y C1
7 g 44.6 x C1
8 h 25.6 y C1
9 i 41.1 x D1
10 j 48.4 x E1
# nest input to create a nested tibble for each id_b
input_nest <- input %>% group_by(id_b) %>% nest()
# calculate dominant class
input_nest_dominant <- input_nest %>% mutate(DOMINANT_CLASS = lapply(data, function(x){
# group each nested tibble by class, and calculate total size. Then find the biggest size and extract
# the class value
output <- x %>% group_by(class) %>%
summarise(total_size = sum(size)) %>%
top_n(total_size, n = 1) %>%
pull(class)
return(output)
} ))
# unnest to end up with a tibble
input_nest_dominant_clean <- input_nest_dominant %>%
unnest(cols = c(DOMINANT_CLASS)) %>%
select(-data) %>%
ungroup()
print(input_nest_dominant_clean)
id_b DOMINANT_CLASS
<chr> <chr>
1 A1 x
2 B1 y
3 C1 y
4 D1 x
5 E1 x
在这个例子中，您根本不需要nest，只需使用group_by和summarize计算即可。
input %>%
group_by(id_b, class) %>%
summarize(size = sum(size)) %>%
group_by(id_b) %>%
summarize(DOMINANT_CLASS = class[which.max(size)])
#> # A tibble: 5 x 2
#> id_b DOMINANT_CLASS
#> <chr> <chr>
#> 1 A1 x
#> 2 B1 y
#> 3 C1 y
#> 4 D1 x
#> 5 E1 x
这里是一个基本的R解决方案，它使用了两次aggregate，即
agg <-aggregate(size ~ class + id_b, input, FUN = sum)
output <- aggregate(agg[-2],agg[2],FUN = max)[-3]
或更紧凑的
output <- aggregate(.~id_b,
aggregate(size ~ class + id_b,
input,
FUN = function(v) sum(v)),
FUN = function(v) tail(sort(v),1))[-3]
使得
> output
id_b class
1 A1 x
2 B1 y
3 C1 y
4 D1 x
5 E1 x
您只需进行1次排序，即可删除所有重复项。类似于：
input %>% arrange(desc(size)) %>% filter(!duplicated(id_b)) %>% arrange(id_b)
# A tibble: 5 x 4
id_a size class id_b
<chr> <dbl> <chr> <chr>
1 b 41.5 x A1
2 e 47.6 y B1
3 h 45.7 y C1
4 i 32.1 x D1
5 j 28.3 x E1
如果id_b的顺序不重要，可以省略最后一个arrange
或在基地R:
input = input[order(-input$size),]
input[!duplicated(input$id_b),]