implemented lighting desctipion cleaning

model_data/EpcClean.py

@@ -28,6 +28,7 @@ class EpcClean:
         "roof-description",
         "walls-description",
         "windows-description",
+        "lighting-description"
     ]
 
     def __init__(self, data: List[Dict[str, Any]]) -> None:
@@ -60,7 +61,7 @@ class EpcClean:
                     'Excelent lighting efficiency'
                 ]
             )
-        ]
+        ].copy()
         aggs["low-energy-lighting"] = aggs["low-energy-lighting"].astype(float)
 
         averages = aggs.groupby("lighting-description")["low-energy-lighting"].mean().reset_index()

model_data/epc_attributes/LightingAttributes.py

@@ -7,23 +7,27 @@ class LightingAttributes:
         self.description: str = clean_description(description.lower())
         self.averages = averages
 
-    def low_energy_proportions(self):
+    def process(self):
 
         description = self.description
 
         if 'no low energy lighting' in description:
-            return 0
+            return {"low_energy_proportion": 0}
 
         if "all fixed outlets" in description:
-            return 1
+            return {"low_energy_proportion": 1}
 
         if ('good lighting efficiency' in description) or ('excellent lighting efficiency' in description) or \
             ('below average lighting efficiency' in description):
-            return self.averages[self.averages == description]["low-energy-lighting"].values[0]
+            return {
+                "low_energy_proportion": self.averages[self.averages == description]["low-energy-lighting"].values[0]
+            }
 
         match = re.search(r'\d+', description)
         if match:
             proportion = int(match.group()) / 100.0
-            return proportion
+            return {
+                "low_energy_proportion": proportion
+            }
 
-        return 0
+        return {"low_energy_proportion": 0}