Question

Following up my previous question about aggregating hourly data into daily data, I want to continue with (a) monthly aggregate and (b) merging the monthly aggregate into the original dataframe.

My original dataframe looks like this:

Lines <- "Date,Outdoor,Indoor
01/01/2000 01:00,30,25
01/01/2000 02:00,31,26
01/01/2000 03:00,33,24
02/01/2000 01:00,29,25
02/01/2000 02:00,27,26
02/01/2000 03:00,39,24
12/01/2000 02:00,27,26
12/01/2000 03:00,39,24
12/31/2000 23:00,28,25"

The daily aggregates have been answered in my previous question, and then I can find my way to produce the monthly aggregates from there, to something like this:

Lines <- "Date,Month,OutdoorAVE
01/01/2000,Jan,31.33
02/01/2000,Feb,31.67
12/01/2000,Dec,31.33"

Where the OutdoorAVE is the monthly average of the daily minimum and maximum outdoor temperature. What I want to have in the end is something like this:

Lines <- "Date,Outdoor,Indoor,Month,OutdoorAVE
01/01/2000 01:00,30,25,Jan,31.33
01/01/2000 02:00,31,26,Jan,31.33
01/01/2000 03:00,33,24,Jan,31.33
02/01/2000 01:00,29,25,Feb,31.67
02/01/2000 02:00,27,26,Feb,31.67
02/01/2000 03:00,39,24,Feb,31.67
12/01/2000 02:00,27,26,Dec,31.33
12/01/2000 03:00,39,24,Dec,31.33
12/31/2000 23:00,28,25,Dec,31.33"

I do not know enough R on how to do that. Any help is greatly appreciated.

Answer 1

Try ave and eg POSIXlt to extract the month:

zz <- textConnection(Lines)
Data <- read.table(zz,header=T,sep=",",stringsAsFactors=F)
close(zz)

Data$Month <- strftime(
     as.POSIXlt(Data$Date,format="%m/%d/%Y %H:%M"),
     format='%b')
Data$outdoor_ave <- ave(Data$Outdoor,Data$Month,FUN=mean)

Gives :

> Data
              Date Outdoor Indoor Month outdoor_ave
1 01/01/2000 01:00      30     25   Jan    31.33333
2 01/01/2000 02:00      31     26   Jan    31.33333
3 01/01/2000 03:00      33     24   Jan    31.33333
4 02/01/2000 01:00      29     25   Feb    31.66667
5 02/01/2000 02:00      27     26   Feb    31.66667
6 02/01/2000 03:00      39     24   Feb    31.66667
7 12/01/2000 02:00      27     26   Dec    31.33333
8 12/01/2000 03:00      39     24   Dec    31.33333
9 12/31/2000 23:00      28     25   Dec    31.33333

---

Edit : Then just calcualte Month in Data as shown above and use merge :

zz <- textConnection(Lines2) # Lines2 is the aggregated data
Data2 <- read.table(zz,header=T,sep=",",stringsAsFactors=F)
close(zz)

> merge(Data,Data2[-1],all=T)
  Month             Date Outdoor Indoor OutdoorAVE
1   Dec 12/01/2000 02:00      27     26      31.33
2   Dec 12/01/2000 03:00      39     24      31.33
3   Dec 12/31/2000 23:00      28     25      31.33
4   Feb 02/01/2000 01:00      29     25      31.67
5   Feb 02/01/2000 02:00      27     26      31.67
6   Feb 02/01/2000 03:00      39     24      31.67
7   Jan 01/01/2000 01:00      30     25      31.33
8   Jan 01/01/2000 02:00      31     26      31.33
9   Jan 01/01/2000 03:00      33     24      31.33