Question

我有一个日期列和价格列：

date = c(2012/12/12 00:00:00.000, 2012/12/12 00:00:00.000, 2012/12/12 00:00:00.000, 2012/12/19 00:00:00.000, 2012/12/19 00:00:00.000, 2013/01/02 00:00:00.000, 2013/01/09 00:00:00.000, 2013/01/19 00:00:00.000, 2013/02/05 00:00:00.000, 2013/02/19 00:00:00.000, 2013/02/26 00:00:00.000, 2013/03/05 00:00:00.000, 2013/03/12 00:00:00.000, 2013/03/20 00:00:00.000, 2013/03/26 00:00:00.000, 2013/04/02 00:00:00.000, 2013/04/09 00:00:00.000, 2013/04/16 00:00:00.000, 2013/04/23 00:00:00.000, 2013/04/30 00:00:00.000, 2013/05/08 00:00:00.000, 2013/06/04 00:00:00.000, 2013/06/29 00:00:00.000, 2013/07/29 00:00:00.000, 2013/08/26 00:00:00.000, 2013/09/19 00:00:00.000, 2013/10/14 00:00:00.000, 2013/10/21 00:00:00.000, 2013/10/30 00:00:00.000, 2013/11/05 00:00:00.000, 2013/11/13 00:00:00.000, 2013/11/20 00:00:00.000, 2013/11/26 00:00:00.000, 2013/12/03 00:00:00.000, 2013/12/10 00:00:00.000, 2013/12/19 00:00:00.000, 2013/12/26 00:00:00.000, 2014/01/03 00:00:00.000, 2014/01/09 00:00:00.000, 2014/01/24 00:00:00.000, 2014/01/31 00:00:00.000, 2014/02/06 00:00:00.000, 2014/02/13 00:00:00.000, 2014/02/20 00:00:00.000, 2014/03/01 00:00:00.000, 2014/03/08 00:00:00.000, 2014/03/14 00:00:00.000, 2014/03/28 00:00:00.000, 2014/04/03 00:00:00.000, 2014/04/10 00:00:00.000, 2014/04/25 00:00:00.000, 2014/05/02 00:00:00.000, 2014/05/09 00:00:00.000, 2014/06/28 00:00:00.000, 2014/07/05 00:00:00.000, 2014/07/23 00:00:00.000)

price = rep(23.5, 56)

每个日期都是交易日期，价格只是产品的价格。我想计算过去12周的花费金额。这意味着每次有交易日期，我都会向后计算12周。我可以计算累积金额：

df = data.table（日期=日期，价格=价格） df [，quantity.csum：= cumsum（price）]

我觉得这很简单，但我找不到办法在12周内（或者我以后决定的任何一周）。

有人能帮助我吗？

谢谢！

Answer 1

定义一个“期间”列，用于定义您要考虑和使用的时间段，例如aggregate

date <- c("2012/12/12 00:00:00.000", "2012/12/12 00:00:00.000", 
          "2012/12/12 00:00:00.000", "2012/12/19 00:00:00.000", "2012/12/19 00:00:00.000", 
          "2013/01/02 00:00:00.000", "2013/01/09 00:00:00.000", "2013/01/19 00:00:00.000", 
          "2013/02/05 00:00:00.000", "2013/02/19 00:00:00.000", "2013/02/26 00:00:00.000", 
          "2013/03/05 00:00:00.000", "2013/03/12 00:00:00.000", "2013/03/20 00:00:00.000")
price <- rep(23.5, 14)
period <- c(rep("period1",5), rep(c("period2", "period3", "period4"), each=3))
df <- data.frame(date=date, price=price, period=period)
df
                      date price  period
1  2012/12/12 00:00:00.000  23.5 period1
2  2012/12/12 00:00:00.000  23.5 period1
3  2012/12/12 00:00:00.000  23.5 period1
4  2012/12/19 00:00:00.000  23.5 period1
5  2012/12/19 00:00:00.000  23.5 period1
6  2013/01/02 00:00:00.000  23.5 period2
7  2013/01/09 00:00:00.000  23.5 period2
8  2013/01/19 00:00:00.000  23.5 period2
9  2013/02/05 00:00:00.000  23.5 period3
10 2013/02/19 00:00:00.000  23.5 period3
11 2013/02/26 00:00:00.000  23.5 period3
12 2013/03/05 00:00:00.000  23.5 period4
13 2013/03/12 00:00:00.000  23.5 period4
14 2013/03/20 00:00:00.000  23.5 period4

aggregate(price~period, data=df, sum)
   period price
1 period1 117.5
2 period2  70.5
3 period3  70.5
4 period4  70.5

编辑：

df <- data.frame(date=date, price=price)
df$date1 <- as.Date(df$date)
df[df$date1 >= "2012-12-12" & df$date1 <= "2012-12-19", "period"] <- "period 1"
df[df$date1 >= "2013-01-02" & df$date1 <= "2013-02-19", "period"] <- "period 2"
df[df$date1 >= "2013-02-26" & df$date1 <= "2013-03-20", "period"] <- "period 3"

aggregate(price~period, data=df, sum)

编辑2：

twelve_weeks <- 7*12 # Seven days in one week
df$date1 - twelve_weeks # Vector containing dates twelve
                        # weeks before each transaction dates

根据日期添加列值

1 个答案: