Thanks for everyone's input so far, it is greatly appreciated. But I've got one last task I could use some advice on
Here are the first few lines of my data set: site,time_local,time_utc,reef_type_code,sensor_type,sensor_depth_m,temperature_c 06,2006-04-09 10:20:00,2006-04-09 20:20:00,BAK,sb39, 2, 29.63 06,2006-04-09 10:40:00,2006-04-09 20:40:00,BAK,sb39, 2, 29.56 06,2006-04-09 11:00:00,2006-04-09 21:00:00,BAK,sb39, 2, 29.51 06,2006-04-09 11:20:00,2006-04-09 21:20:00,BAK,sb39, 10, 29.53 06,2006-04-09 11:40:00,2006-04-09 21:40:00,BAK,sb39, 2, 29.57 06,2006-04-09 12:00:00,2006-04-09 22:00:00,BAK,sb39, 2, 29.60 06,2006-04-09 12:20:00,2006-04-09 22:20:00,BAK,sb39, 2, 29.66 06,2006-04-09 12:40:00,2006-04-09 22:40:00,BAK,sb39, 2, 29.68 06,2006-04-09 13:00:00,2006-04-09 23:00:00,BAK,sb39, 10, 29.68 06,2006-04-09 13:20:00,2006-04-09 23:20:00,BAK,sb39, 2, 29.71 06,2006-04-09 13:40:00,2006-04-09 23:40:00,BAK,sb39, 2, 29.68 06,2006-04-09 14:00:00,2006-04-10 00:00:00,BAK,sb39, 10, 29.49 06,2006-04-09 14:20:00,2006-04-10 00:20:00,BAK,sb39, 2, 29.31 06,2006-04-09 14:40:00,2006-04-10 00:40:00,BAK,sb39, 10, 29.27 My goal was to extract all of the 10m data (all of the "10"'s from the "sensor_depth_m" column) and than calculate daily averages. With the help from this forum I came up with this: library(zoo) Data=read.table("06_BottomMountThermistors.csv",sep=",",header=TRUE,as.is =TRUE) Ten=subset(Data,sensor_depth_m==10L) z=zoo(Ten$temperature_c,Ten$time_local) Warning message: In zoo(Ten$temperature_c, Ten$time_local) : some methods for zoo objects do not work if the index entries in order.by are not unique ag=aggregate(zoo,as.Date,mean) write.csv(ag,file="LTER_6_10m.csv") Which works fine. I'm not sure why I get the error concerning unique entries as all of the 10m "time local" data is sequential and thus unique. Certainly some of the "temperature_c" data is repeated, but my understanding of a zoo object is that I have the "time_local" column set up as the order.by index. So any thoughts on the warning message and my understanding of zoo objects would be appreciated. But the last task I have for this data is to average several of these data sets together. My thoughts were to run the code as above for 6 different sites (column 1 is the "site" index). I still think in excel, so I was planning on lining up all 6 sites in a spreadsheet so that the dates (daily means from the above code) line up, and then just averaging the data like so: Date, Site1, Site2, Site3, Site4, Site5, Site6 Average 2006-04-09 ,20,19,20,19,14,12,average(Site1-6) 2006-04-10,12,13,14,15,16,12 ,average(Site1-6) 2006-04-11,12,12,12,13,12,12 , average(Site1-6) 2006-04-12,12,13,13,12,12,12, average(Site1-6) But I figure R can do this for me, so why bother going back to excel when R is turning out to be a way better way to work with this kind of data. I tried using merge, but I don't think this is the right command. So is there anyway I can have R take 6 different data sets, line them up by date, and pull a grand average by day for all 6 sites? Thanks again for all of your help. You guys rock! [[alternative HTML version deleted]]
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