Remove isordered trait (#19)

* Remove 'isordered' trait

* Update CI

Author: eliascarv

.github/dependabot.yml

@@ -0,0 +1,11 @@
+# To get started with Dependabot version updates, you'll need to specify which
+# package ecosystems to update and where the package manifests are located.
+# Please see the documentation for all configuration options:
+# https://docs.github.com/github/administering-a-repository/configuration-options-for-dependency-updates
+
+version: 2
+updates:
+  - package-ecosystem: "github-actions" # See documentation for possible values
+    directory: "/" # Location of package manifests
+    schedule:
+      interval: "weekly"

.github/workflows/CI.yml

@@ -28,16 +28,16 @@ jobs:
         arch:
           - x64
     steps:
-      - uses: actions/checkout@v3
-      - uses: julia-actions/setup-julia@v1
+      - uses: actions/checkout@v4
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.version }}
           arch: ${{ matrix.arch }}
-      - uses: julia-actions/cache@v1
+      - uses: julia-actions/cache@v2
       - uses: julia-actions/julia-buildpkg@v1
       - uses: julia-actions/julia-runtest@v1
       - uses: julia-actions/julia-processcoverage@v1
-      - uses: codecov/codecov-action@v3
+      - uses: codecov/codecov-action@v4
         with:
           files: lcov.info
           token: ${{ secrets.CODECOV_TOKEN }}

ext/DataScienceTraitsCategoricalArraysExt.jl

@@ -10,6 +10,4 @@ using CategoricalArrays
 DataScienceTraits.scitype(::Type{<:CategoricalValue}) = DataScienceTraits.Categorical
 DataScienceTraits.elscitype(::Type{<:CategoricalArray}) = DataScienceTraits.Categorical
 
-DataScienceTraits.isordered(array::CategoricalArray) = isordered(array)
-
 end

src/DataScienceTraits.jl

@@ -148,18 +148,6 @@ Convert the scientific type of elements of the iterable `itr` to `S`, ignoring m
 """
 coerce(::Type{S}, itr) where {S<:SciType} = map(x -> ismissing(x) ? missing : sciconvert(S, x), itr)
 
-"""
-    isordered(itr)
-
-Checks whether the categorical variables of the iterable `itr` are ordered.
-"""
-function isordered(itr)
-  if !(elscitype(itr) <: Categorical)
-    throw(ArgumentError("iterable elements are not categorical"))
-  end
-  false
-end
-
 #---------
 # EXPORTS
 #---------

test/runtests.jl

@@ -127,15 +127,6 @@ const DST = DataScienceTraits
     @test elscitype(DST.coerce(DST.Categorical, (1.0, 2.0, 3.0))) <: DST.Categorical
   end
 
-  @testset "isordered" begin
-    @test !DST.isordered([1, 2, 3])
-    @test !DST.isordered(['a', 'b', 'c'])
-    @test !DST.isordered(("a", "b", "c"))
-
-    # throws
-    @test_throws ArgumentError DST.isordered([1.0, 2.0, 3.0])
-  end
-
   @testset "missing values" begin
     @test scitype(Missing) <: DST.Unknown
     @test scitype(Union{Float64,Missing}) <: DST.Continuous
@@ -235,9 +226,6 @@ const DST = DataScienceTraits
     @test elscitype(CA) <: DST.Categorical
     @test elscitype(carr) <: DST.Categorical
     @test elscitype(categorical([1, missing, 3])) <: DST.Categorical
-    @test !DST.isordered(carr)
-    carr = categorical([1, 3, 2], ordered=true)
-    @test DST.isordered(carr)
   end
 
   @testset "Colors" begin