我最近发布了一个类似的问题在这里,但那个问题有点过于简单。因此,我们再来一次:
假设我有一个数据框(以下是dput输出),其中包含许多不同变量(例如此例中的5个,在实际数据中还有更多)的时间序列数据:
date a b c d e
1 2009-10-01 00:00:00 10 20 30 40 50
2 2009-10-01 01:00:00 11 21 31 41 51
3 2009-10-01 02:00:00 12 22 32 42 52
4 2009-10-01 03:00:00 13 23 33 43 53
5 2009-10-01 04:00:00 14 24 34 44 54
6 2009-10-01 05:00:00 15 25 35 45 55
7 2009-10-01 06:00:00 16 26 36 46 56
8 2009-10-01 07:00:00 17 27 37 47 57
9 2009-10-01 08:00:00 18 28 38 48 58
10 2009-10-01 09:00:00 19 29 39 49 59
11 2009-10-01 10:00:00 20 30 40 50 60
12 2009-10-01 11:00:00 21 31 41 51 61
13 2009-10-01 12:00:00 22 32 42 52 62
14 2009-10-01 13:00:00 23 33 43 53 63
15 2009-10-01 14:00:00 24 34 44 54 64
16 2009-10-01 15:00:00 25 35 45 55 65
17 2009-10-01 16:00:00 26 36 46 56 66
18 2009-10-01 17:00:00 27 37 47 57 67
19 2009-10-01 18:00:00 28 38 48 58 68
20 2009-10-01 19:00:00 29 39 49 59 69
21 2009-10-01 20:00:00 30 40 50 60 70
22 2009-10-01 21:00:00 31 41 51 61 71
23 2009-10-01 22:00:00 32 42 52 62 72
24 2009-10-01 23:00:00 33 43 53 63 73
25 2009-10-02 00:00:00 34 44 54 64 74
还有另一个数据框“events”,通过开始和结束日期(这里是3个,实际数据中可能有更多)定义了不同的时间段:
id start stop
1 AGH 2009-10-01 02:00:00 2009-10-01 04:00:00
2 TRG 2009-10-01 03:00:00 2009-10-01 10:00:00
3 ZUH 2009-10-01 03:00:00 2009-10-01 20:00:00
我希望能够获得一个不同事件中变量平均值的表格,如下所示:
id avg(y.a) avg(y.b) avg(y.c) avg(y.d) avg(y.e)
1 AGH 13.0 23.0 33.0 43.0 53.0
2 TRG 16.5 26.5 36.5 46.5 56.5
3 ZUH 21.5 31.5 41.5 51.5 61.5
我从之前的帖子中学到,我可以使用sqldf包和一个相当简单的SQL语句来实现这个功能:
means <- sqldf("
+ SELECT x.id, avg(y.a), avg(y.b), avg(y.c), avg(y.d), avg(y.e)
+ FROM events as x, data as y
+ WHERE y.date between x.start and x.stop
+ GROUP BY x.id
+ ")
然而,由于真实数据包含许多需要平均的列,在我处理的各个文件中命名方式也不同,将所有列名输入SQL语句有点繁琐。因此,我更喜欢在R中找到解决方案,可以通过数字(data [2:100])简单地引用列。然而,困难在于时间段是不连续和重叠的,并且id是字符字符串。如何实现这一点的任何想法都将不胜感激! dput(data)
structure(list(date = structure(c(1254348000, 1254351600, 1254355200,
1254358800, 1254362400, 1254366000, 1254369600, 1254373200, 1254376800,
1254380400, 1254384000, 1254387600, 1254391200, 1254394800, 1254398400,
1254402000, 1254405600, 1254409200, 1254412800, 1254416400, 1254420000,
1254423600, 1254427200, 1254430800, 1254434400), class = c("POSIXct",
"POSIXt"), tzone = "Europe/Berlin"), a = 10:34, b = 20:44, c = 30:54,
d = 40:64, e = 50:74), .Names = c("date", "a", "b", "c",
"d", "e"), row.names = c(NA, -25L), class = "data.frame")
将事件传输到dput
structure(list(id = structure(1:3, .Label = c("AGH", "TRG", "ZUH"
), class = "factor"), start = structure(c(1254355200, 1254358800,
1254358800), class = c("POSIXct", "POSIXt"), tzone = "Europe/Berlin"),
stop = structure(c(1254362400, 1254384000, 1254420000), class = c("POSIXct",
"POSIXt"), tzone = "Europe/Berlin")), .Names = c("id", "start",
"stop"), row.names = c(NA, -3L), class = "data.frame")
sprintf
有趣得多。(G. Grothendieck是一位比我更有能力的R程序员,他编写了该软件包...需要加载。 - IRTFM