100% coverage

tests/performance/test_performance.py

@@ -8,7 +8,8 @@
 from rdt.performance.performance import evaluate_transformer_performance
 from rdt.performance.profiling import profile_transformer
 from rdt.transformers import get_transformers_by_type
-from rdt.transformers.categorical import CustomLabelEncoder, OrderedLabelEncoder, OrderedUniformEncoder
+from rdt.transformers.categorical import (
+    CustomLabelEncoder, OrderedLabelEncoder, OrderedUniformEncoder)
 from rdt.transformers.numerical import ClusterBasedNormalizer
 
 SANDBOX_TRANSFORMERS = [

tests/unit/transformers/test_categorical.py

@@ -299,19 +299,19 @@ def test__reverse_transform(self):
     def test__reverse_transform_nans(self):
         """Test ``_reverse_transform`` for data with NaNs."""
         # Setup
-        data = pd.Series(['a', 'b', 'c', np.nan, 'c', 'b', 'b', 'a', 'b', np.nan])
+        data = pd.Series(['a', 'b', 'NaN', np.nan, 'NaN', 'b', 'b', 'a', 'b', np.nan])
         transformer = UniformEncoder()
         transformer.dtype = object
         transformer.frequencies = {
             'a': 0.2,
             'b': 0.4,
-            'c': 0.2,
+            'NaN': 0.2,
             np.nan: 0.2
         }
         transformer.intervals = {
             'a': [0, 0.2],
             'b': [0.2, 0.6],
-            'c': [0.6, 0.8],
+            'NaN': [0.6, 0.8],
             np.nan: [0.8, 1]
         }
 
@@ -458,16 +458,20 @@ def test__transform_error(self):
         If the data being transformed is not in ``self.order`` an error should be raised.
         """
         # Setup
-        data = pd.Series([1, 2, 3, 2, 1, 4])
+        data_error = pd.Series([1, 2, 3, 2, 1, 4])
+        data = pd.Series([1, 2, 1, 2, 1, 1])
         transformer = OrderedUniformEncoder(order=[2, 1])
 
         # Run / Assert
+        transformer._fit(data)
+        transformer._transform(data)
+
         message = re.escape(
             "Unknown categories '[3, 4]'. All possible categories must be defined in the "
             "'order' parameter."
         )
         with pytest.raises(TransformerInputError, match=message):
-            transformer._transform(data)
+            transformer._transform(data_error)
 
 
 class TestFrequencyEncoder: