Aggregate15 minute data to hourly

Question

I have a data frame that looks like this:

     Timedate              TotalSolar_MW
20  2013-06-01 04:45:00     13.0
21  2013-06-01 05:00:00     41.7
22  2013-06-01 05:15:00     81.8
23  2013-06-01 05:30:00    153.0
24  2013-06-01 05:45:00    270.7
25  2013-06-01 06:00:00    429.3
26  2013-06-01 06:15:00    535.4

"Timedate" is POSIXlt, and "Total_Solar" is numeric. The time steps are in 15 minute intervals from June 1, 0:00 to June 24, 24:00.

Now I want to aggregate the quarter hourly data to hourly steps e.g. 2013-06-01 06:00:00 934.8MW (81.8MW + 153.0MW + 270.7MW + 429.3MW; from 05:15 to 06:00)

I tried this with:

 Sum <-aggregate(Total_Solar_Gesamt$TotalSolar_MW, 
          list(as.POSIXlt(Total_Solar_Gesamt$Timedate)$hour), FUN=sum)

But it returns the aggregated hourly data of the whole data frame and gives me a new data.frame with 24 rows and the summed up MW for every hour.

How can I change the structure, only to reduce from a quarter hourly to an hourly interval? I tried a for loop but this also didn't work. Also subset didn't work for me.

Answer 1

When working with time series, I suggest you work with xts package for this, and for example hourly.apply:

 library(xts)
 dat.xts <- xts(Total_Solar_Gesamt$TotalSolar_MW,
                as.POSIXct(otal_Solar_Gesamt$Timedate))
 hourly.apply(dat.xts,sum)

More general you can use period.apply which is (lapply equivalent) , for example to aggregate your data each 2 hours you can do the following:

 ends <- endpoints(zoo.data,'hours',2) 
 period.apply(dat.xts,ends ,sum)