根据 R data.table/frame 中的组按日期汇总份额/行数

Question

我想计算上一年按组 B (country) 的组 A (industry) 的唯一值的出现次数的平方和（分别为行数）。

计算示例第 5 行：2x A + 1x B + 1x C = 2^2+1^2+^+1^2 = 6（不包括第 1 行的 A，因为它超过一年，也不包括第 6 行的 A，因为它在另一个国家/地区） .

我设法按行计算数字，但未能将其移至聚合日期级别：

dt[, count_by_industry:= sapply(date, function(x) length(industry[between(date, x - lubridate::years(1), x)])), 
    by = c("country", "industry")]

该解决方案理想地扩展到具有约 200 万行和大约 10k 日期和组元素的真实数据（因此有 data.table 标签）。

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示例数据

ID    <- c("1","2","3","4","5","6")
Date <- c("2016-01-02","2017-01-01", "2017-01-03", "2017-01-03", "2017-01-04","2017-01-03")
Industry <- c("A","A","B","C","A","A")
Country <- c("UK","UK","UK","UK","UK","US")
Desired <- c(1,4,3,3,6,1)

library(data.table)
dt <- data.frame(id=ID, date=Date, industry=Industry, country=Country, desired_output=Desired)
setDT(dt)[, date := as.Date(date)]

Answer 1

从一开始就适应：

dt[, output:= sapply(date, function(x) sum(table(industry[between(date, x - lubridate::years(1), x)]) ^ 2)), 
   by = c("country")]
dt
   id       date industry country desired_output output
1:  1 2016-01-02        A      UK              1      1
2:  2 2017-01-01        A      UK              4      4
3:  3 2017-01-03        B      UK              3      3
4:  4 2017-01-03        C      UK              3      3
5:  5 2017-01-04        A      UK              6      6
6:  6 2017-01-03        A      US              1      1