That�s ingenious, but I would hesitate to rely on a specific mapping between
strings and integers. (I usually read data frames with stringsAsFactors=FALSE
or coerce to character later: I don�t think it takes more memory.) Maybe create
another column with the coefficients. What if gender is part of another formula?
Regards,
Jorgen Harmse.
From: CALUM POLWART <polc1...@gmail.com>
Date: Saturday, November 4, 2023 at 18:23
To: avi.e.gr...@gmail.com <avi.e.gr...@gmail.com>
Cc: Jorgen Harmse <jhar...@roku.com>, r-help@r-project.org
<r-help@r-project.org>, mkzama...@gmail.com <mkzama...@gmail.com>
Subject: [EXTERNAL] 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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