Summing a data frame R based on a date range in a second data frame

Question

I have two data frames: one that includes data by day, and one that includes data at irregular multi-day time intervals. For instance:

Data frame precip_rangewith precipitation data at irregular time intervals:

start_date<-as.Date(c("2010-11-01", "2010-11-04", "2010-11-10"))
end_date<-as.Date(c("2010-11-03", "2010-11-09", "2010-11-12"))
precipitation<-(c(12, 8, 14))
precip_range<-data.frame(start_date, end_date, precipitation)

And a data frame precip_dailywith daily precipitation data:

day<-as.Date(c("2010-11-01", "2010-11-02", "2010-11-03", "2010-11-04", "2010-11-05",
                  "2010-11-06", "2010-11-07", "2010-11-08", "2010-11-09", "2010-11-10",
                  "2010-11-11", "2010-11-12"))
precip<-(c(3, 1, 2, 1, 0.25, 1, 3, 0.33, 0.75, 0.5, 1, 2))
precip_daily<-data.frame(day, precip)

In this example, precip_dailyrepresents the daily rainfall estimated by the model and precip_rangerepresents the measured cumulative precipitation for specific date ranges. I am trying to compare the simulated with the measured data, which requires synchronization of time periods.

, precip precip_daily ( precip) start_date end_date precip_range. ?

Answer 1

start_dates precip_range breaks to cut() .

rng <- cut(precip_daily$day, 
    breaks=c(precip_range$start_date, max(precip_range$end_date)), 
    include.lowest=T)

, data.frame. . ,

cbind(precip_daily, rng)

#           day precip        rng
# 1  2010-11-01   3.00 2010-11-01
# 2  2010-11-02   1.00 2010-11-01
# 3  2010-11-03   2.00 2010-11-01
# 4  2010-11-04   1.00 2010-11-04
# 5  2010-11-05   0.25 2010-11-04
# 6  2010-11-06   1.00 2010-11-04
# 7  2010-11-07   3.00 2010-11-04
# 8  2010-11-08   0.33 2010-11-04
# 9  2010-11-09   0.75 2010-11-04
# 10 2010-11-10   0.50 2010-11-10
# 11 2010-11-11   1.00 2010-11-10
# 12 2010-11-12   2.00 2010-11-10

, .

aggregate(cbind(count=1, sum=precip_daily$precip)~rng, FUN=sum)

#          rng count  sum
# 1 2010-11-01     3 6.00
# 2 2010-11-04     6 6.33
# 3 2010-11-10     3 3.50

(, )

Answer 2

library(zoo)
library(data.table)
temp <- merge(precip_daily, precip_range, by.x = "day", by.y = "start_date", all.x = T)
temp$end_date <- na.locf(temp$end_date)
setDT(temp)[, list(Sum = sum(precip), Count = .N), by = end_date]

##     end_date  Sum Count
## 1: 2010-11-03 6.00     3
## 2: 2010-11-09 6.33     6
## 3: 2010-11-12 3.50     3