FloatFormatter does not round the data correctly for integer columns when using _set_fitted_parameters

rdt/transformers/numerical.py

@@ -236,8 +236,9 @@ def _set_fitted_parameters(
             self._min_value = min(min_max_values)
             self._max_value = max(min_max_values)
 
-        if rounding_digits:
+        if rounding_digits is not None:
             self._rounding_digits = rounding_digits
+            self.learn_rounding_scheme = True
 
         if self.null_transformer.models_missing_values():
             self.output_columns.append(column_name + '.is_null')

tests/integration/transformers/test_numerical.py

@@ -287,6 +287,26 @@ def test__support__nullable_numerical_pandas_dtypes(self):
                 reverse_transformed[column].round(expected_rounding_digits[column]),
             )
 
+    def test__set_fitted_parameter_rounding_to_integer(self):
+        """Test the ``_set_fitted_parameters`` method with rounding_digits set to 0."""
+        # Setup
+        data = pd.DataFrame({
+            'col 1': 100 * np.random.random(10),
+        })
+        transformer = FloatFormatter()
+
+        # Run
+        transformer._set_fitted_parameters(
+            column_name='col 1',
+            null_transformer=NullTransformer(),
+            rounding_digits=0,
+            dtype='float',
+        )
+        reverse_transformed_data = transformer.reverse_transform(data)
+
+        # Assert
+        pd.testing.assert_frame_equal(reverse_transformed_data, data.round(0))
+
 
 class TestGaussianNormalizer:
     def test_stats(self):

tests/unit/transformers/test_numerical.py

@@ -748,6 +748,7 @@ def test__set_fitted_parameters(self):
         assert transformer._max_value == 100.0
         assert transformer._rounding_digits == rounding_digits
         assert transformer._dtype == dtype
+        assert transformer.learn_rounding_scheme is True
 
     def test__set_fitted_parameters_from_column(self):
         """Test ``_set_fitted_parameters`` sets the required parameters for transformer."""