各组累计 [英] Cumulative total by group

问题描述

对于以下数据集:

d = data.frame(date = as.Date(as.Date('2015-01-01'):as.Date('2015-04-10'), origin = "1970-01-01"),
               group = rep(c('A','B','C','D'), 25), value = sample(1:100))
head(d)
         date group value
1: 2015-01-01     A     4
2: 2015-01-02     B    32
3: 2015-01-03     C    46
4: 2015-01-04     D    40
5: 2015-01-05     A    93
6: 2015-01-06     B    10

.. 任何人都可以建议一种比此 data.table 更优雅的方法来按组计算累计值) 方法?

.. can anyone advise a more elegant way to calculate a cumulative total of values by group than this data.table) method?

library(data.table)
setDT(d)
d.cast = dcast.data.table(d, group ~ date, value.var = 'value', fun.aggregate = sum)
c.sum = d.cast[, as.list(cumsum(unlist(.SD))), by = group]

.. 这很笨重，并产生一个需要 dplyr::gather 或 reshape2::melt 重新格式化的平面矩阵.

.. which is pretty clunky and yields a flat matrix that needs dplyr::gather or reshape2::melt to reformat.

R 肯定能做得比这更好吗??

Surely R can do better than this??

推荐答案

如果你只想要每组的累积总和，那么你可以这样做

If you just want cumulative sums per group, then you can do

transform(d, new=ave(value,group,FUN=cumsum))

以 R 为基数.

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