如何計算兩個日期之間的變量平均值

Question

我想計算兩個日期之間的變量平均值，以下是可重現的數據框。

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")

所以我有兩個數據集如下

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

對於每個ID，我想計算開始日期和結束日期（月份）之間的平均濃度。 注意，該站可能會在幾年之間變化。

例如，對於id = 1，我想計算1996年6月到1997年4月之間的平均濃度。這應該基於A站從1996年6月到1996年12月以及B站從1997年1月到1997年4月的濃度。

有人可以幫忙嗎？

非常感謝你。

Answer 1

這是一個data.table解決方案。 基本思想是將每個id的開始-結束范圍內的所有日期枚舉為yearmon ，然后將其用作濃度表df的索引。 這有點令人費解，所以希望有人會來給您展示一種更簡單的方法。

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

因此，首先我們將所有內容都轉換為data.tables。 然后，我們將yrmon列添加到df以便以后進行索引。 然后，我們通過將participant重塑為長格式來創建p.melt ，以便站點位於一列中，而指標（1996或1997）位於單獨的列中。 然后，我們創建一個臨時表x ，其中每個id帶有日期序列，並為每個日期添加year和yrmon。 然后，將其與id和year p.melt合並，以將樁號列添加到x 。 然后，使用yrmon和station將x與df合並以獲得適當的濃度。 然后我們簡單地使用mean(...)在x通過id聚合conc 。