这个答案假定你在寻找区间，而不是寻找大于给定计数阈值的数字的累积和。
cut + table在以下情况下非常有用：

table(cut(x, breaks = y))

  (0,10]  (10,20]  (20,30]  (30,40]  (40,50]  (50,60]  (60,70]  (70,80]  (80,90] (90,100] 
      51       66       36       44       54       49       55       46       58       41

findInterval + table将给予相同的结果

table(findInterval(x, y,  left.open = TRUE))

数据类型

set.seed(505)
x <- c(sample(1:100, 500, replace = T))
y <- seq(0,100, by = 10)

如果我没理解错的话，这可能行得通：

x <- c(sample(1:100, 500, replace = T))
y <- seq(0,100, by = 10)

is_bigger_than <- function(y){
  data.frame(y, n = sum(x > y,na.rm = TRUE))
}
    
purrr::map_df(y,is_bigger_than)

     y   n
1    0 500
2   10 450
3   20 403
4   30 359
5   40 305
6   50 264
7   60 201
8   70 155
9   80 100
10  90  52
11 100   0

对于base R，这是一种方法

rbind(Total = y, Count = rowSums(sapply(x, ">", y)))
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11]
Total    0   10   20   30   40   50   60   70   80    90   100
Count  500  444  381  329  279  241  198  150  104    52     0