[R] separating data into columns

[sheck at ucar.edu]

Hi All-

I have been trying to separate data into columns - specifically the 
date - and then aggregate the rest of the data to calculate summer 
hourly means. However, now I would like to calculate hourly means just 
over one day at a time.  And, I am not able to figure out how to do 
this. I read some help files that I think indicated that I can only use 
the method below for months, years and quarters. Perhaps just 
separating the date into the following columns would work - Yr Mon Day 
Hr Min???

I originally used "zoo" and "chron" as follows for the monthly means:


library(zoo)
library(chron)

z <- read.zoo("C:/R/SPL JJA 2006 2008.txt", header = TRUE, na.strings = -999,
format = "%y%m%d%H%M", FUN = as.chron,
colClasses = c("character", rep("numeric", 10)))

mph <- z[months(time(z)) %in% c("Jun", "Jul", "Aug"),]
mphagg <- aggregate(mph, hours, mean)


Here is a sample data set:

YYMMDDhhmm   Precip  mph   Deg    DegF   Fuel   Rel   volts   DegMx  
mphgust wm
0606010000   0.00    4.6   97.5   42.1   -999   39.5   -999   -999    
5.2    0.3
0606010005   0.00    4.6   97.6   42.0   -999   38.8   -999   -999    
5.7    0.3
0606010010   0.00    2.6   97.6   41.9   -999   36.9   -999   -999    
3.5    0.3
0606010015   0.00    2.3   97.6   41.8   -999   37.1   -999   -999    
3.7    0.3
0606010020   0.00    1.8   97.6   41.5   -999   36.3   -999   -999    
1.8    0.3
0606010025   0.00    1.8   97.6   41.1   -999   36.1   -999   -999    
1.8    0.3
0606010030   0.00    1.8   97.6   40.8   -999   36.1   -999   -999    
1.8    0.3
0606010035   0.00    1.8   97.6   40.4   -999   35.3   -999   -999    
1.8    0.3
0606010040   0.00    1.8   97.7   40.1   -999   36.0   -999   -999    
1.8    0.3
0606010045   0.00    1.8   97.7   39.7   -999   36.7   -999   -999    
1.8    0.3
0606010050   0.00    1.8   97.7   39.3   -999   37.3   -999   -999    
1.8    0.3
0606010055   0.00    1.8   97.7   38.9   -999   38.0   -999   -999    
1.8    0.3
0606010100   0.00    1.8   97.7   38.6   -999   38.9   -999   -999    
1.8    0.3

Any help is appreciated-

Thanks-

Sherri Heck
University of Colorado