Fix get_elements_dataframe with attribute same name

TM1py/Services/ElementService.py

@@ -429,6 +429,18 @@ def get_elements_dataframe(self, dimension_name: str = None, hierarchy_name: str
 
         cell_service = self._get_cell_service()
 
+        # override column names. hierarchy name with dimension and prefix attributes
+        element_attributes = self.get_element_attributes(dimension_name, hierarchy_name)
+        column_renaming = dict()
+        if attribute_column_prefix or attribute_suffix:
+            column_renaming = {
+                ea.name: f"{attribute_column_prefix}{ea.name}" + (
+                    f":{ea.attribute_type.lower()[0]}"
+                    if attribute_suffix
+                    else "")
+                for ea
+                in element_attributes}
+
         # responses are similar but not equivalent.
         # Therefor only use execute_mdx_dataframe when use_blob is True
         if use_blob:
@@ -455,14 +467,21 @@ def get_elements_dataframe(self, dimension_name: str = None, hierarchy_name: str
                 columns='}ElementAttributes_' + dimension_name,
                 values='Value',
                 aggfunc='first',
-                sort=False).reset_index()
+                sort=False)
+
+            # override column names. hierarchy name with dimension and prefix attributes
+            df_data.columns = [column_renaming.get(col, col) for col in df_data.columns]
+            df_data = df_data.reset_index()
 
             # Drop the group key
             df_data = df_data.fillna("").drop(columns='_group')
 
         else:
             df_data = cell_service.execute_mdx_dataframe_shaped(mdx, **kwargs)
 
+            # override column names. hierarchy name with dimension and prefix attributes
+            df_data.columns = [df_data.columns[0]] + [column_renaming.get(col, col) for col in df_data.columns[1:]]
+
         if levels_dict:
             # rename level names to conform sto standard levels "1" -> "level001"
             df_data.rename(columns=levels_dict, inplace=True)
@@ -494,21 +513,6 @@ def get_elements_dataframe(self, dimension_name: str = None, hierarchy_name: str
             for col in alias_attributes:
                 df_data[col] = np.where(df_data[col] == '', df_data[dimension_name], df_data[col])
 
-        # override column names. hierarchy name with dimension and prefix attributes
-        column_renaming = dict()
-        if attribute_column_prefix or attribute_suffix:
-            column_renaming = {
-                ea.name: f"{attribute_column_prefix}{ea.name}" + (
-                    f":{ea.attribute_type.lower()[0]}"
-                    if attribute_suffix
-                    else "")
-                for ea
-                in element_attributes}
-
-        column_renaming[hierarchy_name] = dimension_name
-
-        df_data.rename(columns=column_renaming, inplace=True)
-
         # shift levels to right hand side
         if not skip_parents:
             # skip max level (= leaves)

Tests/ElementService_test.py

@@ -33,6 +33,7 @@ def setUp(self):
 
         self.dimension_name = pure_dimension_name
         self.dimension_with_hierarchies_name = pure_dimension_name + '_with_hierarchies'
+        self.dimension_with_same_attribute_name = pure_dimension_name + '_attribute_same_name'
         self.hierarchy_name = pure_dimension_name
         self.attribute_cube_name = '}ElementAttributes_' + pure_dimension_name
         self.dimension_does_not_exist_name = pure_dimension_name + "_does_not_exist"
@@ -79,9 +80,15 @@ def setUp(self):
 
         self.create_or_update_dimension_with_hierarchies()
 
+        d.name = self.dimension_with_same_attribute_name
+        h = d.get_hierarchy(d.name)
+        h.add_element_attribute(name=self.dimension_with_same_attribute_name, attribute_type="String")
+        self.tm1.dimensions.update_or_create(d)
+
     def tearDown(self):
         self.tm1.dimensions.delete(self.dimension_name)
         self.tm1.dimensions.delete(self.dimension_with_hierarchies_name)
+        self.tm1.dimensions.delete(self.dimension_with_same_attribute_name)
 
     def create_or_update_dimension_with_hierarchies(self):
         dimension = Dimension(self.dimension_with_hierarchies_name)
@@ -575,6 +582,39 @@ def run_test_get_elements_dataframe_not_elements(self, use_blob: bool):
 
         self.assertTrue(df.equals(reference_df))
 
+    @skip_if_no_pandas
+    def test_get_elements_dataframe_attribute_same_name(self):
+        self.run_test_get_elements_dataframe_attribute_same_name(False)
+
+    @skip_if_no_pandas
+    def test_get_elements_dataframe_attribute_same_name_use_blob(self):
+        self.run_test_get_elements_dataframe_attribute_same_name(True)
+
+    def run_test_get_elements_dataframe_attribute_same_name(self, use_blob: bool):
+        df = self.tm1.elements.get_elements_dataframe(
+            dimension_name=self.dimension_with_same_attribute_name,
+            hierarchy_name=self.dimension_with_same_attribute_name,
+            skip_consolidations=True,
+            attributes=None,
+            attribute_column_prefix="Attribute ",
+            skip_parents=True,
+            level_names=None,
+            parent_attribute=None,
+            skip_weights=False,
+            use_blob=use_blob)
+
+        expected_columns = (
+            self.dimension_with_same_attribute_name,
+            'Type',
+            'Attribute Previous Year',
+            'Attribute Next Year',
+            'Attribute Financial Year',
+            'Attribute ' + self.dimension_with_same_attribute_name
+            ,)
+
+        self.assertEqual((5, 6), df.shape)
+        self.assertEqual(expected_columns, tuple(df.columns))
+
     @skip_if_no_pandas
     def test_get_elements_dataframe_not_elements(self):
         self.run_test_get_elements_dataframe_not_elements(use_blob=False)