✨ Add support for single vector

Author: EssamWisam

Project.toml

@@ -26,7 +26,7 @@ ScientificTypes = "3.0"
 StatsBase = "0.34"
 TableOperations = "1.2"
 Tables = "1.11"
-julia = "1.6"
+julia = "1.10"
 
 [extras]
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"

src/generic.jl

@@ -16,7 +16,7 @@ logic?"
     - X: A table where the elements of the categorical features have [scitypes](https://juliaai.github.io/ScientificTypes.jl/dev/) 
     `Multiclass` or `OrderedFactor`
     - features=[]: A list of names of categorical features given as symbols to exclude or include from encoding,
-      according to the value of `ignore`
+      according to the value of `ignore`, or a single symbol (which is treated as a vector with one symbol),
       or a callable that returns true for features to be included/excluded
     - ignore=true: Whether to exclude or includes the features given in features
     - ordered_factor=false: Whether to encode OrderedFactor or ignore them
@@ -40,8 +40,12 @@ function generic_fit(X,
     feat_names = Tables.schema(X).names
 
     #2.  Modify column_names based on features 
+    if features isa Symbol
+        features = [features]
+    end
+    
     if features isa AbstractVector{Symbol}
-         # Original behavior for vector of symbols
+        # Original behavior for vector of symbols
         feat_names =
             (ignore) ? setdiff(feat_names, features) : intersect(feat_names, features)
     else

test/generic.jl

@@ -182,4 +182,20 @@ end
     # Test 3: predicate with ordered_factor=true picks up ordered factors (e.g., :E)
     cache3 = dummy_encoder_fit(X, predicate; ignore=false, ordered_factor=true)
     @test Set(cache3[:encoded]) == Set([:A, :C, :E])
+end
+
+@testset "Single Symbol and list of one symbol equivalence" begin
+     X = dataset_forms[1]
+    feat_names = Tables.schema(X).names
+
+    # Test 1: Single Symbol
+    single_symbol = :A
+    cache1 = dummy_encoder_fit(X, single_symbol; ignore=true, ordered_factor=false)
+    @test !(:A in cache1[:encoded])
+    # Test 2: List of one symbol
+    single_symbol_list = [:A]
+    cache2 = dummy_encoder_fit(X, single_symbol_list; ignore=true, ordered_factor=false)
+    @test !(:A in cache2[:encoded])
+    # Test 3: Both should yield the same result
+    @test cache1[:encoded] == cache2[:encoded]
 end