Pandas FutureWarning: Length 1 tuple will be returned (#1374)

* warning fix

* add groupby_list method

* lint

* formatting

* add unit test

sdv/constraints/base.py

@@ -14,6 +14,7 @@
 from sdv.constraints.errors import (
     AggregateConstraintsError, ConstraintMetadataError, MissingConstraintColumnError)
 from sdv.errors import ConstraintsNotMetError
+from sdv.utils import groupby_list
 
 LOGGER = logging.getLogger(__name__)
 
@@ -497,7 +498,7 @@ def sample(self, table_data):
                 Table data with additional ``constraint_columns``.
         """
         condition_columns = [c for c in self.constraint_columns if c in table_data.columns]
-        grouped_conditions = table_data[condition_columns].groupby(condition_columns)
+        grouped_conditions = table_data[condition_columns].groupby(groupby_list(condition_columns))
         all_sampled_rows = []
         for group, dataframe in grouped_conditions:
             if not isinstance(group, tuple):

sdv/sequential/par.py

@@ -15,7 +15,7 @@
 from sdv.metadata.single_table import SingleTableMetadata
 from sdv.single_table import GaussianCopulaSynthesizer
 from sdv.single_table.base import BaseSynthesizer
-from sdv.utils import cast_to_iterable
+from sdv.utils import cast_to_iterable, groupby_list
 
 LOGGER = logging.getLogger(__name__)
 
@@ -134,8 +134,7 @@ def add_constraints(self, constraints):
     def _validate_context_columns(self, data):
         errors = []
         if self.context_columns:
-            errors = []
-            for sequence_key_value, data_values in data.groupby(self._sequence_key):
+            for sequence_key_value, data_values in data.groupby(groupby_list(self._sequence_key)):
                 for context_column in self.context_columns:
                     if len(data_values[context_column].unique()) > 1:
                         errors.append((

sdv/single_table/base.py

@@ -23,7 +23,7 @@
 from sdv.single_table.errors import InvalidDataError
 from sdv.single_table.utils import check_num_rows, handle_sampling_error, validate_file_path
 from sdv.utils import (
-    is_boolean_type, is_datetime_type, is_numerical_type, validate_datetime_format)
+    groupby_list, is_boolean_type, is_datetime_type, is_numerical_type, validate_datetime_format)
 
 LOGGER = logging.getLogger(__name__)
 COND_IDX = str(uuid.uuid4())
@@ -893,7 +893,7 @@ def _sample_with_conditions(self, conditions, max_tries_per_batch, batch_size,
         condition_columns = list(conditions.columns)
         conditions.index.name = COND_IDX
         conditions = conditions.reset_index()
-        grouped_conditions = conditions.groupby(condition_columns)
+        grouped_conditions = conditions.groupby(groupby_list(condition_columns))
 
         # sample
         all_sampled_rows = []
@@ -935,7 +935,9 @@ def _sample_with_conditions(self, conditions, max_tries_per_batch, batch_size,
                 )
                 all_sampled_rows.append(sampled_rows)
             else:
-                transformed_groups = transformed_conditions.groupby(transformed_columns)
+                transformed_groups = transformed_conditions.groupby(
+                    groupby_list(transformed_columns)
+                )
                 for transformed_group, transformed_dataframe in transformed_groups:
                     if not isinstance(transformed_group, tuple):
                         transformed_group = [transformed_group]

sdv/utils.py

@@ -164,3 +164,8 @@ def load_data_from_csv(filepath, pandas_kwargs=None):
     pandas_kwargs = pandas_kwargs or {}
     data = pd.read_csv(filepath, **pandas_kwargs)
     return data
+
+
+def groupby_list(list_to_check):
+    """Return the first element of the list if the length is 1 else the entire list."""
+    return list_to_check[0] if len(list_to_check) == 1 else list_to_check

tests/unit/constraints/test_base.py

@@ -1006,3 +1006,12 @@ def test_sample(self):
         })
         instance._reject_sample.assert_any_call(num_rows=5, conditions={'b': 1})
         pd.testing.assert_frame_equal(transformed_data, expected_result)
+
+    @patch('warnings.warn')
+    def test_groupby_removed_warning(self, mock_warn):
+        """Test that the pandas warning is no longer raised."""
+        # Run
+        self.test_sample()
+
+        # Assert
+        mock_warn.assert_not_called()