r - 如何在 R 中使用复杂条件减去中位数

Question

我有数据集

df=structure(list(SKU = c(11202L, 11202L, 11202L, 11202L, 11202L, 
11202L, 11202L, 11202L, 11202L, 11202L, 11202L, 11202L, 11202L, 
11202L, 11202L, 11202L, 11202L, 11202L, 11202L, 11202L, 11202L
), stuff = c(8.85947691, 9.450108704, 10.0407405, 10.0407405, 
10.63137229, 11.22200409, 11.22200409, 11.81263588, 12.40326767, 
12.40326767, 12.40326767, 12.99389947, 13.58453126, 14.17516306, 
14.76579485, 15.94705844, 17.12832203, 17.71895382, 21.26274458, 
25.98779894, 63.19760196), action = c(0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L), 
    acnumber = c(137L, 137L, 137L, 137L, 137L, 137L, 137L, 137L, 
    137L, 137L, 137L, 137L, 137L, 137L, 137L, 137L, 137L, 137L, 
    137L, 137L, 137L), year = c(2018L, 2018L, 2018L, 2018L, 2018L, 
    2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 
    2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L)), .Names = c("SKU", 
"stuff", "action", "acnumber", "year"), class = "data.frame", row.names = c(NA, 
-21L))

操作列只有两个值 0 和 1。 正如我们所看到的，1 类别的内容有 3 个观测值，0 类别的内容有 18 个观测值。

我需要 -仅计算类别 1 的 stuff 变量的中位数(等于 25.98779894)，不带零。 正如我们所看到的，一之间有零，它们需要被删除，如果存在负值，也需要被删除。 即，就好像数据集是这样的:

structure(list(SKU = c(11202L, 11202L, 11202L, 11202L, 11202L, 
11202L, 11202L, 11202L, 11202L, 11202L, 11202L, 11202L, 11202L, 
11202L, 11202L, 11202L, 11202L, 11202L, 11202L, 11202L, 11202L
), stuff = c(8.85947691, 9.450108704, 10.0407405, 10.0407405, 
10.63137229, 11.22200409, 11.22200409, 11.81263588, 12.40326767, 
12.40326767, 12.40326767, 12.99389947, 13.58453126, 14.17516306, 
14.76579485, 15.94705844, 17.12832203, 17.71895382, 21.26274458, 
25.98779894, 63.19760196), action = c(0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 1L, NA, NA, NA, NA, NA, NA, NA, NA, 1L, 1L), 
    acnumber = c(137L, 137L, 137L, 137L, 137L, 137L, 137L, 137L, 
    137L, 137L, 137L, 137L, 137L, 137L, 137L, 137L, 137L, 137L, 
    137L, 137L, 137L), year = c(2018L, 2018L, 2018L, 2018L, 2018L, 
    2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 
    2018L, 2018L, 2018L, 2018L, 2018L, 2018L, 2018L)), .Names = c("SKU", 
"stuff", "action", "acnumber", "year"), class = "data.frame", row.names = c(NA, 
-21L))

我还需要通过类别 0 的填充变量计算最后三个观察值的中位数，该变量位于第一个观察值之前， 在我们的例子中是 12,40326767

然后从类别 1 的中位数中减去类别 0 的中位数，然后乘以 1 的数量，在本例中为 3。

(25,98779894-12,40326767)*3=40,75359381

我该如何进行此操作？

作为我期望的输出

SKU     stuff     action    acnumber    year    value
11202   8,85947691  3          137      2018    40,75359381

Answer 1

这是一个 tidyverse 解决方案:

df %>%
  group_by(SKU,acnumber,year) %>%
  summarize(value = 3*(median(stuff[action==1]) - median(stuff[match(1,action)-3:1])),
            stuff=first(stuff),
            action = sum(action)) %>%
  select(SKU,stuff,action,acnumber,year,value)

# # A tibble: 1 x 6
# # Groups:   SKU, acnumber [1]
#     SKU stuff action acnumber  year value
#   <int> <dbl>  <int>    <int> <int> <dbl>
# 1 11202  8.86      3      137  2018  40.8