Question

我想计算两个日期之间变量的平均值，下面是可重现的数据框。

year <- c(1996,1996,1996,1996,1996,1996,1996,1996,1996,1996,1996,1996,
      1996,1996,1996,1996,1996,1996,1996,1996,1996,1996,1996,1996,
      1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,
      1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997)
month <- c("JAN","FEB","MAR","APR","MAY","JUN","JUL","AUG","SEP","OCT","NOV","DEC")
station <- c("A","A","A","A","A","A","A","A","A","A","A","A",
         "B","B","B","B","B","B","B","B","B","B","B","B")

concentration <- as.numeric(round(runif(48,20,40),1))

df <- data.frame(year,month,station,concentration)


id <- c(1,2,3,4)
station1996 <- c("A","A","B","B")
station1997 <- c("B","A","A","B")
start <- c("06/01/1996","07/01/1996","07/01/1996","08/01/1996")
end <- c("04/01/1997","04/01/1997","04/01/1997","05/01/1997")

participant <- data.frame(id,station1996,station1997,start,end)
participant$start <- as.Date(participant$start, format = "%m/%d/%Y")
participant$end <- as.Date(participant$end, format = "%m/%d/%Y")

所以我有两个数据集如下

df
   year month station concentration
1  1996   JAN       A          24.4
2  1996   FEB       A          37.0
3  1996   MAR       A          39.5
4  1996   APR       A          28.0
...
45 1997   SEP       B          37.7
46 1997   OCT       B          35.2
47 1997   NOV       B          26.8
48 1997   DEC       B          40.0

participant
  id station1996 station1997      start        end
1  1           A           B 1996-06-01 1997-04-01
2  2           A           A 1996-07-01 1997-04-01
3  3           B           A 1996-07-01 1997-04-01
4  4           B           B 1996-08-01 1997-05-01

对于每个id，我想计算开始日期和结束日期（月份）之间的平均浓度。注意到该站可能会在不同年份之间发生变化。

例如，对于id = 1，我想计算1996年6月和1997年APR之间的平均浓度。这应该基于1996年6月至1996年12月在A站和1997年1月至1997年APR的浓度。乙

有人可以帮忙吗？

非常感谢。

Answer 1

这是一个data.table解决方案。基本思路是将每个yearmon的起始范围内的所有日期枚举为id，然后将其用作浓度表df的索引。这有点令人费解，所以希望有人会出现并向您展示一种更简单的方式。

library(data.table)
library(zoo)          # for as.yearmon(...)
setDT(df)             # convert to data.table
setDT(participant)
df[, yrmon:= as.yearmon(paste(year,month,sep="-"), format="%Y-%B")]   # add year-month column
p.melt <- reshape(participant, varying=2:3, direction="long", sep="", timevar="year")
x <- participant[, .(date=seq(start,end,by="month")), by=id]
x[, c("year","yrmon"):=.(year(date),as.yearmon(date))]           # add year and year-month
x[p.melt, station:=station, on=c("id","year")]                   # add station
x[df, conc:= concentration, on=c("yrmon","station"), nomatch=0]  # add concentration
setorder(x,id)    # not necessary, but makes it easier to interpret x
result <- x[, .(mean.conc=mean(conc)), by=id]                    # mean(conc) by id
result
#    id mean.conc
# 1:  1  28.61818
# 2:  2  28.56000
# 3:  3  28.44000
# 4:  4  29.60000

所以，首先我们将所有内容转换为data.tables。然后，我们将yrmon列添加到df以便稍后进行索引。然后我们通过将p.melt重新整形为长格式来创建participant，以便工作站位于一列中，指示符（1996或1997）位于单独的列中。然后我们创建一个临时表x，其中包含每个id的日期序列，并为每个日期添加年份和年份。然后我们将其与p.melt和id上的year合并，以将电台列添加到x。然后，我们使用yrmon和station将x与df合并，以获得适当的集中度。然后，我们只需使用conc在id中按x汇总mean(...)。

如何计算两个日期之间变量的平均值

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