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fixing bug where all weights are 0, due to no house numbers
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@ -456,6 +456,9 @@ class SearchEpc:
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epc_data["weight"] = 1 / (epc_data["house_number_distance"] + 1)
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# If we have a home without a house number, fill that weight with average
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epc_data["weight"] = epc_data["weight"].fillna(epc_data["weight"].mean())
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# Finally, we might not have any house numbers whatsoever so everything could be
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# missing, so we fill with 1
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epc_data["weight"] = epc_data["weight"].fillna(1)
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epc_built_form = self._estimate_str(key="built-form", estimation_data=epc_data)
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epc_property_type = self._estimate_str(key="property-type", estimation_data=epc_data)
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@ -137,6 +137,7 @@ def app():
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# Get aggregate performance figures
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results_df = pd.DataFrame(results)
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results_df["tenure"] = results_df["tenure"].replace("Rented (social)", "rental (social)")
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avg_numeric_succes = results_df["numeric_success"].median()
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avg_categorical_sucess = results_df["categorical_success"].median()
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