Quantile normalizes one column in R
I have a column in my dataframe in R, data $ height. The values range from 0 to 400. I want to normalize the values in the column so that the resulting values are between 0-1 and are quantiles, that is, the median value in the dataset should reflect 0.5 as the newer value.
Guess how to do it.
source to share
The R function ppoints
is a common way of matching values at their percentile ranks.
See its argument a
-
The setting a=1
takes the lowest value at 0 and the highest value at 1
The value a=0
takes the smallest value at 1 / (n + 1) and the largest value at n / (n + 1)
By default it has value = 3/8 (if n is 10 or less) or = 1/2 (when n is greater than 10)
This function is used by other functions in R. For example, it is called qqnorm
to execute ordinary quantum-quantile plots.
source to share
Do you want some rank
, for example, as in
> set.seed(1)
> exdf <- data.frame(height = runif(5, min=0, max=400))
> exdf$r1 <- (rank(exdf$height) - 1) / (length(exdf$height)-1)
> exdf$r2 <- (rank(exdf$height)-1/2) / length(exdf$height)
> exdf
height r1 r2
1 106.20347 0.25 0.3
2 148.84956 0.50 0.5
3 229.14135 0.75 0.7
4 363.28312 1.00 0.9
5 80.67277 0.00 0.1
source to share