在 data.table 中按组划分的分位数

Question

我想对每组进行分位数切割（切割成 n 个点数相等的箱）

qcut = function(x, n) {
  quantiles = seq(0, 1, length.out = n+1)
  cutpoints = unname(quantile(x, quantiles, na.rm = TRUE))
  cut(x, cutpoints, include.lowest = TRUE)
}

library(data.table)
dt = data.table(A = 1:10, B = c(1,1,1,1,1,2,2,2,2,2))
dt[, bin := qcut(A, 3)]
dt[, bin2 := qcut(A, 3), by = B]

dt
A     B    bin        bin2
 1:  1 1  [1,4]    [6,7.33]
 2:  2 1  [1,4]    [6,7.33]
 3:  3 1  [1,4] (7.33,8.67]
 4:  4 1  [1,4]   (8.67,10]
 5:  5 1  (4,7]   (8.67,10]
 6:  6 2  (4,7]    [6,7.33]
 7:  7 2  (4,7]    [6,7.33]
 8:  8 2 (7,10] (7.33,8.67]
 9:  9 2 (7,10]   (8.67,10]
10: 10 2 (7,10]   (8.67,10]

这里没有分组的剪辑是正确的——数据在 bin 中。但是分组的结果是错误的。

我该如何解决这个问题？

Answer 1

这是处理因子的错误。请检查它是否已知（或在开发版本中已修复），否则将其报告给 data.table 错误跟踪器。

qcut = function(x, n) {
  quantiles = seq(0, 1, length.out = n+1)
  cutpoints = unname(quantile(x, quantiles, na.rm = TRUE))
  as.character(cut(x, cutpoints, include.lowest = TRUE))
}

dt[, bin2 := qcut(A, 3), by = B]
#     A B    bin        bin2
# 1:  1 1  [1,4]    [1,2.33]
# 2:  2 1  [1,4]    [1,2.33]
# 3:  3 1  [1,4] (2.33,3.67]
# 4:  4 1  [1,4]    (3.67,5]
# 5:  5 1  (4,7]    (3.67,5]
# 6:  6 2  (4,7]    [6,7.33]
# 7:  7 2  (4,7]    [6,7.33]
# 8:  8 2 (7,10] (7.33,8.67]
# 9:  9 2 (7,10]   (8.67,10]
#10: 10 2 (7,10]   (8.67,10]