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如何在不使用 For 循环语句的情况下计算累积加热度天数？我是 R 新手，不太确定如何完成这项工作。

我想做这个：

for(i in 1:nrow(df)) {
    df$cumHDD <- df$HeatingDegreeDay[i] + df$cumHDD[i-1]
     i <- i+1
}

下面是我的数据。

    SiteID SubstrateID  WinterID       Date HeatingDegreeDay cumHDD
1   NW_SB           B 2002_2003 2002-11-01        0.0000000      0
2   NW_SB           B 2002_2003 2002-11-02        0.0000000      0
3   NW_SB           B 2002_2003 2002-11-03        0.0000000      0
4   NW_SB           B 2002_2003 2002-11-04        0.0000000      0
5   NW_SB           B 2002_2003 2002-11-05        0.0000000      0
6   NW_SB           B 2002_2003 2002-11-06        0.0000000      0
7   NW_SB           B 2002_2003 2002-11-07        0.0000000      0
8   NW_SB           B 2002_2003 2002-11-08        0.0000000      0
9   NW_SB           B 2002_2003 2002-11-09        0.0000000      0
10  NW_SB           B 2002_2003 2002-11-10        0.0000000      0
11  NW_SB           B 2002_2003 2002-11-11        0.0000000      0
12  NW_SB           B 2002_2003 2002-11-12        0.0000000      0
13  NW_SB           B 2002_2003 2002-11-13        0.0000000      0
14  NW_SB           B 2002_2003 2002-11-14        0.0000000      0
15  NW_SB           B 2002_2003 2002-11-15        0.0000000      0
16  NW_SB           B 2002_2003 2002-11-16        0.0000000      0
17  NW_SB           B 2002_2003 2002-11-17        0.0000000      0
18  NW_SB           B 2002_2003 2002-11-18        0.0000000      0
19  NW_SB           B 2002_2003 2002-11-19        0.3724242      0
20  NW_SB           B 2002_2003 2002-11-20        0.0000000      0
21  NW_SB           B 2002_2003 2002-11-21        0.0000000      0
22  NW_SB           B 2002_2003 2002-11-22        0.0000000      0
23  NW_SB           B 2002_2003 2002-11-23        0.2773077      0
24  NW_SB           B 2002_2003 2002-11-24        0.2679310      0
25  NW_SB           B 2002_2003 2002-11-25        0.0000000      0

所以，对于我上面的数据，当它正确完成时，它应该是这样的：

SiteID SubstrateID  WinterID       Date HeatingDegreeDay cumHDD
1   NW_SB           B 2002_2003 2002-11-01        0.0000000      0
2   NW_SB           B 2002_2003 2002-11-02        0.0000000      0
3   NW_SB           B 2002_2003 2002-11-03        0.0000000      0
4   NW_SB           B 2002_2003 2002-11-04        0.0000000      0
5   NW_SB           B 2002_2003 2002-11-05        0.0000000      0
6   NW_SB           B 2002_2003 2002-11-06        0.0000000      0
7   NW_SB           B 2002_2003 2002-11-07        0.0000000      0
8   NW_SB           B 2002_2003 2002-11-08        0.0000000      0
9   NW_SB           B 2002_2003 2002-11-09        0.0000000      0
10  NW_SB           B 2002_2003 2002-11-10        0.0000000      0
11  NW_SB           B 2002_2003 2002-11-11        0.0000000      0
12  NW_SB           B 2002_2003 2002-11-12        0.0000000      0
13  NW_SB           B 2002_2003 2002-11-13        0.0000000      0
14  NW_SB           B 2002_2003 2002-11-14        0.0000000      0
15  NW_SB           B 2002_2003 2002-11-15        0.0000000      0
16  NW_SB           B 2002_2003 2002-11-16        0.0000000      0
17  NW_SB           B 2002_2003 2002-11-17        0.0000000      0
18  NW_SB           B 2002_2003 2002-11-18        0.0000000      0
19  NW_SB           B 2002_2003 2002-11-19        0.3724242      0.3724242
20  NW_SB           B 2002_2003 2002-11-20        0.0000000      0.3724242
21  NW_SB           B 2002_2003 2002-11-21        0.0000000      0.3724242
22  NW_SB           B 2002_2003 2002-11-22        0.0000000      0.3724242
23  NW_SB           B 2002_2003 2002-11-23        0.2773077      0.6497319
24  NW_SB           B 2002_2003 2002-11-24        0.2679310      0.9176629
25  NW_SB           B 2002_2003 2002-11-25        0.0000000      0.9176629

我可以在ddply声明中这样做吗？我还有其他一些功能要做，并且认为在ddply.

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1 回答 1

4

您需要为此使用cumsum：

mydata$cumHDD<-with(mydata,cumsum(HeatingDegreeDay))

假设 mydata 是您的数据。

使用 mtcars 数据的示例ddply

library(plyr)
mydata<-mtcars
k<-ddply(mydata,.(cyl),summarize,cummpg=cumsum(mpg))

头(k,10)

cyl cummpg
1    4   22.8
2    4   47.2
3    4   70.0
4    4  102.4
5    4  132.8
6    4  166.7
7    4  188.2
8    4  215.5
9    4  241.5
10   4  271.9
于 2013-08-20T17:54:30.327 回答