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Combining aggregated data in R

Following my previous question

In my previous question

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

Where OutdoorAVE is the monthly average of the daily minimum and maximum outdoor temperatures. What I want to have at the end looks 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 don’t know enough R about how to do this. Any help is appreciated.

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3 answers

Try aveand, for example 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)

It 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
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, RSQLite , SQL. , .

+2

zoo/xts. , Month , zoo/xts.

require(xts) # loads zoo too
Lines1 <- "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"
con <- textConnection(Lines1)
z <- read.zoo(con, header=TRUE, sep=",",
    format="%m/%d/%Y %H:%M", FUN=as.POSIXct)
close(con)

zz <- merge(z, Month=.indexmon(z),
    OutdoorAVE=ave(z[,1], .indexmon(z), FUN=mean))
zz
#                     Outdoor Indoor Month OutdoorAVE
# 2000-01-01 01:00:00      30     25     0   31.33333
# 2000-01-01 02:00:00      31     26     0   31.33333
# 2000-01-01 03:00:00      33     24     0   31.33333
# 2000-02-01 01:00:00      29     25     1   31.66667
# 2000-02-01 02:00:00      27     26     1   31.66667
# 2000-02-01 03:00:00      39     24     1   31.66667
# 2000-12-01 02:00:00      27     26    11   31.33333
# 2000-12-01 03:00:00      39     24    11   31.33333
# 2000-12-31 23:00:00      28     25    11   31.33333

: , .

Lines2 <- "Date,Month,OutdoorAVE
01/01/2000,Jan,31.33
02/01/2000,Feb,31.67
12/01/2000,Dec,31.33"
con <- textConnection(Lines2)
z2 <- read.zoo(con, header=TRUE, sep=",", format="%m/%d/%Y",
    FUN=as.POSIXct, colClasses=c("character","NULL","numeric"))
close(con)

zz2 <- na.locf(merge(z1, Month=.indexmon(z1), OutdoorAVE=z2))[index(z1)]
# same output as zz (above)
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