Fix 1163

Determine level column order based on digit in header (e.g., level008)

TM1py/Services/HierarchyService.py

@@ -488,12 +488,20 @@ def update_or_create_hierarchy_from_dataframe(
         # identify level columns
         level_columns = []
         level_weight_columns = []
+
         # sort to assure right order of levels
-        for column in sorted(df.columns, reverse=True):
+        sorted_level_columns = sorted(
+            [col for col in df.columns if any(char.isdigit() for char in col)],  # Filter columns with digits
+            key=lambda x: int(''.join(filter(str.isdigit, x))),  # Sort based on numeric part
+            reverse=True  # Descending order
+        )
+
+        # Process sorted columns
+        for column in sorted_level_columns:
             if column.lower().startswith('level') and column[5:8].isdigit():
-                if len(column) == 8:
+                if len(column) == 8:  # "LevelXXX"
                     level_columns.append(column)
-                elif len(column) == 15 and column.lower().endswith('_weight'):
+                elif len(column) == 15 and column.lower().endswith('_weight'):  # "LevelXXX_weight"
                     level_weight_columns.append(column)
 
         # case: no level weight columns. All weights are 1
@@ -503,9 +511,6 @@ def update_or_create_hierarchy_from_dataframe(
                 level_weight_columns.append(level_weight_column)
                 df[level_weight_column] = 1
 
-        if not len(level_columns) == len(level_weight_columns):
-            raise ValueError("Number of level columns must be equal to number of level weight columns")
-
         if verify_edges:
             self._validate_edges(df=df[[element_column, *level_columns]])
 

Tests/HierarchyService_test.py

@@ -3,6 +3,7 @@
 from contextlib import suppress
 from pathlib import Path
 
+import pandas as pd
 from mdxpy import MdxBuilder, MdxHierarchySet
 from pandas import DataFrame
 
@@ -513,6 +514,33 @@ def test_update_or_create_hierarchy_from_dataframe(self):
             hierarchy_name=self.region_dimension_name)
         self._verify_region_dimension(hierarchy)
 
+    def test_update_or_create_hierarchy_from_dataframe_non_standard_level_order(self):
+        columns = [self.region_dimension_name, "ElementType", "Alias:a", "Currency:s", "population:n", "Level001",
+                   "level000", "level001_weight", "level000_weight"]
+        data = [
+            ['France', "Numeric", "Frankreich", "EUR", 60_000_000, "Europe", "World", 1, 1],
+            ['Switzerland', 'Numeric', "Schweiz", "CHF", 9_000_000, "Europe", "World", 1, 1],
+            ['Germany', 'Numeric', "Deutschland", "EUR", 84_000_000, "Europe", "World", 1, 1],
+        ]
+        df = DataFrame(data=data, columns=columns)
+
+        df = pd.DataFrame(df[[self.region_dimension_name, "ElementType", "Alias:a", "Currency:s", "population:n", "level000",
+                 "Level001", "level000_weight", "level001_weight"]])
+        print(df.to_markdown())
+        self.tm1.hierarchies.update_or_create_hierarchy_from_dataframe(
+            dimension_name=self.region_dimension_name,
+            hierarchy_name=self.region_dimension_name,
+            df=df,
+            element_column=self.region_dimension_name,
+            element_type_column="ElementType",
+            unwind=True
+        )
+
+        hierarchy = self.tm1.hierarchies.get(
+            dimension_name=self.region_dimension_name,
+            hierarchy_name=self.region_dimension_name)
+        self._verify_region_dimension(hierarchy)
+
     def test_update_or_create_hierarchy_from_dataframe_existing_attributes(self):
         columns = [self.region_dimension_name, "ElementType", "Currency:s", "population:n", "level001",
                    "level000", "level001_weight", "level000_weight"]