[R] I need to create new variables based on two numeric variables and one dichotomize conditional category variables.
@vi@e@gross m@iii@g oii gm@ii@com
@vi@e@gross m@iii@g oii gm@ii@com
Sun Nov 5 05:27:16 CET 2023
There are many techniques Callum and yours is an interesting twist I had not considered.
Yes, you can specify what integer a factor uses to represent things but not what I meant. Of course your trick does not work for some other forms of data like real numbers in double format. There is a cost to converting a column to a factor that is recouped best if it speeds things up multiple times.
The point I was making was that when you will be using group_by, especially if done many times, it might speed things up if the column is already a normal factor, perhaps just indexed from 1 onward. My guess is that underneath the covers, some programs implicitly do such a factor conversion if needed. An example might be aspects of the ggplot program where you may get a mysterious order of presentation in the graph unless you create a factor with the order you wish to have used and avoid it making one invisibly.
From: CALUM POLWART <polc1410 using gmail.com>
Sent: Saturday, November 4, 2023 7:14 PM
To: avi.e.gross using gmail.com
Cc: Jorgen Harmse <JHarmse using roku.com>; r-help using r-project.org; mkzaman.m using gmail.com
Subject: Re: [R] I need to create new variables based on two numeric variables and one dichotomize conditional category variables.
I might have factored the gender.
I'm not sure it would in any way be quicker. But might be to some extent easier to develop variations of. And is sort of what factors should be doing...
# make dummy data
gender <- c("Male", "Female", "Male", "Female")
WC <- c(70,60,75,65)
TG <- c(0.9, 1.1, 1.2, 1.0)
myDf <- data.frame( gender, WC, TG )
# label a factor
myDf$GF <- factor(myDf$gender, labels= c("Male"=65, "Female"=58))
# do the maths
myDf$LAP <- (myDf$WC - as.numeric(myDf$GF))* myDf$TG
#show results
head(myDf)
gender WC TG GF LAP
1 Male 70 0.9 58 61.2
2 Female 60 1.1 65 64.9
3 Male 75 1.2 58 87.6
4 Female 65 1.0 65 64.0
(Reality: I'd have probably used case_when in tidy to create a new numeric column)
The equation to
calculate LAP is different for male and females. I am giving both equations
below.
LAP for male = (WC-65)*TG
LAP for female = (WC-58)*TG
My question is 'how can I calculate the LAP and create a single new column?
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