Hi Bruce,
>From your excel sheets, it looks like for the step1, you were just taking only
>the "Survey Time" of the first rows of unique Start_Day for each
>Location_name.
Step2 results looks the same as "res2"
If this is the case:
dat1<-
read.csv("Sample_all_3_locations.csv",header=TRUE,stringsAsFactors=FALSE,sep=",")
library(plyr)
res1<-ddply(aggregate(Survey_Time~Location_name+Start_Day,data=dat1,function(x)
head(x,1)),.(Location_name),summarize,Survey_Time=sum(Survey_Time))
res1
# Location_name Survey_Time
#1 1_f3p1_La_Campana 46.4
#2 2_f4p1_La_Campana 69.5
#3 79_f2p1_Acetuna 36.4
res2<-ddply(dat1,.(Location_name,SPEC_CODE),summarize, AI=sum(AI))
Final<- mutate(join(res1,res2),RA=10*(AI/Survey_Time))
head(Final)
# Location_name Survey_Time SPEC_CODE AI RA
#1 1_f3p1_La_Campana 46.4 Buzz 20 4.3103448
#2 1_f3p1_La_Campana 46.4 Cencen 20 4.3103448
#3 1_f3p1_La_Campana 46.4 Eptfur 215 46.3362069
#4 1_f3p1_La_Campana 46.4 Frag 3 0.6465517
#5 1_f3p1_La_Campana 46.4 Molspp 22 4.7413793
#6 1_f3p1_La_Campana 46.4 Myoele 1 0.2155172
dim(Final)
#[1] 44 5
A.K.
----- Original Message -----
From: Bruce Miller <[email protected]>
To: arun <[email protected]>
Cc:
Sent: Monday, April 22, 2013 11:32 AM
Subject: Re: More
Arun,
Attached are two Excel sheets that I manually did what I am hoping I can
automate in R for the larger data sets.
These use the same 3 locations and data I sent earlier.
Step 1 sums the total survey time for each location then step 2 sums the AI
values for he SPEC_CODE by location.
Then the calculation of Summed AI value/Summed Survey time can be completed for
each location and SPEC_Code.
Hopefully this clarifies it more.
Bruce
-- Bruce W. Miller, Ph.D.
Conservation Ecologist
Neotropical Bat Projects
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