Hi all, I have a large dataset with ~8600 observations that I want to compress to weekly means. There are 9 variables (columns), and I have already added a "week" column with 51 weeks. I have been looking at the functions: aggregate, tapply, apply, etc. and I am just not savvy enough with R to figure this out on my own, though I'm sure it's fairly easy. I also have the Dates (month/day/year) for all of the observations, but I figured just having a week column may be easier. If someone wanted to show me how to organize this data using a date function and aggregating by month that would be useful too!
Here's an example of the data set, with only 5 of the variables and 10 of 8600 obs.: week rainfall windspeed winddir temp oakdepth 1 1 0.20000000 0.89000 245.9200 1.150000 4.400000 2 1 0.00000000 0.84000 292.8800 1.190000 5.300000 3 1 0.20000000 0.74000 258.5400 1.360000 6.000000 4 1 0.00000000 0.93000 3.7000 1.430000 4.400000 5 1 0.20000000 0.69000 37.8200 1.560000 5.200000 6 1 0.00000000 0.80000 17.2900 1.690000 4.400000 7 1 0.20000000 0.70000 28.7300 1.880000 5.000000 8 1 0.20000000 1.12000 294.3700 1.930000 6.000000 9 1 0.00000000 1.21000 274.9700 1.800000 4.400000 10 1 0.00000000 1.31000 279.2400 1.860000 5.800000 ...so after about 170 observations it changes to week 2, and so on. I've tried something like this, but its only one variable's mean, and I would rather have the rows=weeks and columns= the different variables. < tapply(metdata$rainfall,metdata$week,FUN=mean) 1 2 3 4 5 6 0.080952381 0.101190476 0.379761905 0.179761905 0.000000000 0.295238095 7 8 9 10 11 12 0.146428571 0.015476190 0.163888889 0.098809524 0.065476190 0.215476190 Hope this is enough information and that I'm not just re-asking an old question. Thanks so much in advance for any help. -- View this message in context: http://r.789695.n4.nabble.com/Need-to-aggregate-large-dataset-by-week-tp4376154p4376154.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.