Finding Quantiles in Julia
I Need a Function Like Xtile in Stata, That Given a Vector, It Returns Which Quantile Each Obs Belongs To. So If the Function Is Defined as Function...
I need a function like xtile in Stata, that given a vector, it returns which quantile each obs belongs to. So if the function is defined as
function xtile(vector; q= 4) #q = 4 by default returns quartiles
*** returns a vector with the same size as "vector", indicating which quantile each obs belongs to.
end
I want to use it in:
@pipe df |> transform(:height => xtile => :quantiles)
I know Stella.jl provides such functionality. But I can't install that package and now I'm wondering if there is another package for it. Or maybe I can implement it myself.
2 Answers
While using the CategoricalArrays package is a good solution and has the added benefit of actually showing what the quantiles mean, it is very easy to implement xtile using just the Julia standard library:
using Statistics
function xtile(x; n=4)
q = quantile(x, LinRange(0, 1, n + 1))
map(v -> min(searchsortedlast(q, v), n), x)
end
A ready-made solution can be found with the cut method provided by the CategoricalArrays.jl package, as long as you are okay with an AbstractVector of Strings:
using CategoricalArrays
x = rand(10);
cut(x, 4)
# 10-element CategoricalArray{String,1,UInt32}:
# "Q4: [0.565838, 0.85564]"
# "Q2: [0.333373, 0.393529)"
# "Q4: [0.565838, 0.85564]"
# "Q3: [0.393529, 0.565838)"
# "Q1: [0.0381196, 0.333373)"
# "Q3: [0.393529, 0.565838)"
# "Q4: [0.565838, 0.85564]"
# "Q1: [0.0381196, 0.333373)"
# "Q1: [0.0381196, 0.333373)"
# "Q2: [0.333373, 0.393529)"
If you want the quantiles as numbers, you can get the level codes by broadcasting levelcode:
a = cut(x, 4);
levelcode.(a)
# 10-element Array{Int64,1}:
# 4
# 2
# 4
# 3
# 1
# 3
# 4
# 1
# 1
# 2
This can be easily converted to a function that works in a pipe:
xtile(x; n=4) = levelcode.(cut(x, n));
xtile(x)
# 10-element Array{Int64,1}:
# 4
# 2
# 4
# 3
# 1
# 3
# 4
# 1
# 1
# 2
xtile(x, n=5)
# 10-element Array{Int64,1}:
# 4
# 2
# 5
# 4
# 1
# 3
# 5
# 2
# 1
# 3
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