Dear all
I have a dataframe containing hourly data of 3 parameters.
I would like to create a dataframe containg daily mean values of these
parameters. Additionally I want to keep information about time of
measurement ("year","month","day").
With the function tapply I can average over a column of the dataframe.
I can repeat the function 2 time and merge the vectors. In this way I
obtain my new dataframe (see below).If I want to add the column day,
month and year I can repeat tapply other three time. This system works.
Question: is there a function that average in a single step over the 3
columns?
Thanks a lot for your answer!
Regards
Mike Campana
#### read the data
setwd("c:/R")
data <- NULL
data <- as.data.frame(read.table(file="Montreal.txt",header=F,skip=15))
colnames(data)
<-c("year","month","day","hour","min","temp","press","ozone")
### create mean value
temp_daily <-
tapply(data$temp,data$year*10000+data$month*100+data$day,FUN=mean)
press_daily <-
tapply(data$press,data$year*10000+data$month*100+data$day,FUN=mean)
ozone_daily <-
tapply(data$ozone,data$year*10000+data$month*100+data$day,FUN=mean)
### merge the data
newdata <- as.data.frame (cbind(temp_daily,temp_daily,temp_daily))
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