Get the sum of a specific number of following rows in R - r

Question

I have to solve this specific problem in R. I have a large list, containing columns and rows in this format:
Day_and_Time Rain1_mm/min Rain2_mm/min
01.12.10 18:01 0 0
.............. .... ...
02.12.10 01:00 0.03 0
02.12.10 01:01 0.03 0
02.12.10 01:02 0.01 0
02.12.10 01:03 0.05 0
02.12.10 01:04 0.03 0.1
02.12.10 01:05 0.04 0
.............. .... ...
02.12.10 18:00 0 0
What I want to do is to write a function that sums up six following rows and return the result as a new row. This means that at the end I have a new list - looking like this for example:
Day_and_Time Rain1_mm/5min Rain2_mm/5min
.............. .... ...
02.12.10 01:05 0.19 0.1
02.12.10 01:10 .... ...
.............. .... ...
Is it possible to do this? The goal is to transform the unit [mm/min] from the first and second column to [mm/5min].
Thank you very much!

Answer 1

Assuming that you read the data in your .csv file as a data frame df, one approach to your problem is to use rollapply from the zoo package to give you a rolling sum:
library(zoo)
ind_keep <- seq(1,floor(nrow(df)/5)*5, by=5) ## 1.
out <- sapply(df[,-1], function(x) rollapply(x,6,sum)) ## 2.
out <- data.frame(df[ind_keep+5,1],out[ind_keep,]) ## 3.
colnames(out) <- c("Day_and_time","Rain1_mm/5min","Rain2_mm/5min") ## 4.
Notes:
Here, we define the indices corresponding to every 5 minutes where we want to keep the rolling sum over the next 5 minutes.
Apply a rolling sum function for each column.
Use sapply over all columns of df that is not the first column. Note that the column indices specified in df[,-1] can be adjusted so that you process only certain columns.
The function to apply is rollapply from the zoo package. The additional arguments are the width of the window 5 and the sum function so that this performs a rolling sum.
At this point, out contains the rolling sums (over 5 minutes) at each minute, but we only want those every 5 minutes. Therefore,
Combines the Day_and_time column from the original df with out keeping only those columns every 5 minutes. Note that we keep the last Day_and_Time in each window.
This just renames the columns.
Using MikeyMike's data, which is
Day_and_Time rain1 rain2
1 2010-02-12 01:00:00 0.03 0.00
2 2010-02-12 01:01:00 0.03 0.00
3 2010-02-12 01:02:00 0.01 0.00
4 2010-02-12 01:03:00 0.05 0.00
5 2010-02-12 01:04:00 0.03 0.10
6 2010-02-12 01:05:00 0.04 0.00
7 2010-02-12 01:06:00 0.02 0.10
8 2010-02-12 01:07:00 0.10 0.10
9 2010-02-12 01:08:00 0.30 0.00
10 2010-02-12 01:09:00 0.01 0.00
11 2010-02-12 01:10:00 0.00 0.01
this gives:
print(out)
## Day_and_time Rain1_mm/5min Rain2_mm/5min
##1 2010-02-12 01:05:00 0.19 0.10
##2 2010-02-12 01:10:00 0.47 0.21
Note the difference in the result, this approach assumes you want overlapping windows since you specified that you want to sum the six numbers between the closed interval [i,i+5] at each 5 minute mark.
To extend the above to a window in the closed interval [i, i+nMin] at each nMin mark:
library(zoo)
nMin <- 10 ## for example 10 minutes
ind_keep <- seq(1, floor(nrow(df)/nMin)*nMin, by=nMin)
out <- sapply(df[,-1], function(x) rollapply(x, nMin+1, sum))
out <- data.frame(df[ind_keep+nMin, 1],out[ind_keep,])
colnames(out) <- c("Day_and_time",paste0("Rain1_mm/",nMin,"min"),paste0("Rain2_mm/",nMin,"min"))
For this to work, the data must have at least 2 * nMin + 1 rows
Hope this helps.

Answer 2

Assuming you want the groups to be 0 - 5 minutes, 6 - 10 minutes, etc. this should give you what you're looking for:
library(data.table)
setDT(df)[,.(day_time = max(Day_and_Time),
rain1_sum=sum(rain1),
rain2_sum=sum(rain2)),
by=.(floor(as.numeric(Day_and_Time)/360))]
floor day_time rain1_sum rain2_sum
1: 3516540 2010-02-12 01:05:00 0.19 0.10
2: 3516541 2010-02-12 01:10:00 0.43 0.21
Data:
df <- structure(list(Day_and_Time = structure(c(1265954400, 1265954460,
1265954520, 1265954580, 1265954640, 1265954700, 1265954760, 1265954820,
1265954880, 1265954940, 1265955000), class = c("POSIXct", "POSIXt"
), tzone = ""), rain1 = c(0.03, 0.03, 0.01, 0.05, 0.03, 0.04,
0.02, 0.1, 0.3, 0.01, 0), rain2 = c(0, 0, 0, 0, 0.1, 0, 0.1,
0.1, 0, 0, 0.01)), .Names = c("Day_and_Time", "rain1", "rain2"
), row.names = c(NA, -11L), class = c("data.table", "data.frame"
), .internal.selfref = <pointer: 0x0000000000240788>)