I would suggest using a 'for' loop
rather than an apply function. The
advantage is that you will probably
understand the loop that you write,
and it will run in roughly the same
amount of time as a complicated call
to an apply function that you don't
understand.
On 01/09/2011 18:11, LCOG1 wrote:
Hi guys,
I have a crap load of data to parse and have enjoyed creating a script that
takes this data and creates a number of useful graphics for our area. I am
unable to figure out one summary though and its all cause I dont fully
understand the apply family of functions. Consider the following:
#Create data
Df..<-rbind(data.frame(Id=1:1008,Dir=rep(c("NB","NB","SB","SB"),252),Mph=runif(1008,0,65),
Volume=runif(1008,0,19),Hour=rep(00,1008),Min5Break=rep(1:12,84),Day=rep(1,1008)),
data.frame(Id=2009:2016,Dir=rep(c("NB","NB","SB","SB"),252),Mph=runif(1008,0,65),
Volume=runif(1008,0,19),Hour=rep(01,1008),Min5Break=rep(1:12,84),Day=rep(2,1008)))
#Example calc
Results_<-list()
#Sum Volume by 5 minute break by Day by Direction
Results_$FiveMin.Direction<-tapply(Df..$Volume,list(Df..$Min5Break,Df..$Day,Df..$Hour,Df..$Dir),sum)
The data is a snap shot of what im working with and I am trying to get to
something similar to the last line where the volumes are summed. What i
want to do is to do a weighted average for the speed by 5 minute break. So
for all the speeds and volumes in a given hour of 5 minute break(12 per
hour), i would want to
sum(Volumes[1:12]*Speed[1:12]) / sum(Volumes[1:12]
The output resembling the one from the above but having these weighted
values. I am assuming the sum function in the above would be replaced by a
function doing the calculation but I am still not sure how to do this using
apply functions, so perhaps this isnt the best option.
Hope this is clear and hope you guys(and of course ladies) can offer some
guidance.
Cheers,
Josh
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Patrick Burns
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