temp.dat$date.time <- date.time.
Then you can "rm(date.time)", because the above command makes a copy as a column of the data.frame temp.dat.
I have not been working with POSIXt, so I can't answer your question about how to get monthly means, other than to ask if you know about subscripting with a logical vector, "aggregate" and "tapply"?
hope this helps. spencer graves
Andy Bunn wrote:
I know that R is very advanced when it comes to DateTime handling. I am not quite as advanced as R however.
I just downloaded a stupendously ugly dataset of hourly air temperature from 1985 to 2003. It has a great many NAs. I want to extract mean, median, max, and min monthly values.
So far I have read it in as object. Date and Time are factors and Temp is an int.
summary(temp.dat)
Date Time Temp 01/01/1986: 24 03:00 : 6457 Min. : -22.00 01/01/1987: 24 04:00 : 6457 1st Qu.: 23.00 01/01/1988: 24 05:00 : 6457 Median : 34.00 01/01/1989: 24 06:00 : 6457 Mean : 34.35 01/01/1990: 24 10:00 : 6457 3rd Qu.: 45.00 01/01/1992: 24 11:00 : 6457 Max. : 89.00 (Other) :154794 (Other):116196 NA's :52178.00
I then made a POSIXt object for the dates and times.
date.time <- strptime(paste(temp.dat$Date, temp.dat$Time), "%m/%d/%Y
%H:")
class(date.time)
[1] "POSIXt" "POSIXlt"
date.time[1]
[1] "1985-10-01 01:00:00"
Now I'm stuck.
Questions:
What's the best class for reuniting the temperature data with the dates? A time series? A list?
Depending on the answer, what's the best way to extract, say, the mean temperatures for Sepetmber?
Thanks in advance, Andy
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