fix(convert_salary_excel): pair count/index columns by category name, not adjacency (#219)

The sequential scan assumed count/index pairs are always adjacent.
Interleaved columns like Count_A, Count_B, Index_A, Index_B produced
wrong pairings (Count_B ↔ Index_A), silently corrupting data.

Now columns are grouped by type, then matched by the category name
derived from stripping type words. Unmatched columns fall back to
standalone value columns using the original header name.

tests/test_convert_salary_excel.py

@@ -157,5 +157,30 @@ class DetectColumnTypeTests(unittest.TestCase):
         self.assertEqual(companies[0]["categories"]["salary_index"], {"index": 105.5})
 
 
+    def test_parse_sheet_pairs_interleaved_count_index_columns_by_name(self):
+        ws = FakeWorksheet([
+            ("Company", "Antal kvinder", "Antal mænd", "Kvinder indeks", "Mænd indeks"),
+            ("Example Corp", 15, 20, 95.0, 108.0),
+        ])
+
+        companies = parse_sheet(ws)
+
+        categories = companies[0]["categories"]
+        self.assertEqual(categories["kvinder"], {"count": 15, "index": 95.0})
+        self.assertEqual(categories["mænd"], {"count": 20, "index": 108.0})
+
+    def test_parse_sheet_non_adjacent_columns_no_cross_match(self):
+        ws = FakeWorksheet([
+            ("Company", "Count_A", "Count_B", "Index_A", "Index_B"),
+            ("Example Corp", 10, 20, 100.0, 200.0),
+        ])
+
+        companies = parse_sheet(ws)
+
+        categories = companies[0]["categories"]
+        self.assertEqual(categories["a"], {"count": 10, "index": 100.0})
+        self.assertEqual(categories["b"], {"count": 20, "index": 200.0})
+
+
 if __name__ == "__main__":
     unittest.main()