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First region implemented

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Khalim Conn-Kowlessar 2024-11-16 15:55:19 +00:00
parent dc1cf6d604
commit c13c84b98c
1 changed files with 47 additions and 11 deletions
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58
etl/customers/stonewater/Wave 3 Preparation.py
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@ -1729,25 +1729,61 @@ def propsed_wave_3_sample():
missed_addressids = region_assets[pd.isnull(region_assets["Confidence Tier"])]["Address ID"].unique().tolist()
# This means that this archetype was never surveyed and so we need to find a sufficiently similar property
final_missed_matches = []
for a_id in missed_addressids:
property = asset_list[asset_list["Address ID"] == a_id].squeeze()
surveyed_same_postcode = survey_results_with_original_features[
# TODO: This is quite strict for the moment - we might want to relax this by creating reduced versions
# of the wall, roof and heating features, splitting them on the colons and taking the first part
surveyed_similar = survey_results_with_original_features[
(survey_results_with_original_features["Postcode"] == property["Postcode"]) &
(survey_results_with_original_features["Property Type"] == property["Property Type"])
(survey_results_with_original_features["Property Type"] == property["Property Type"]) &
(survey_results_with_original_features["Wall Type"] == property["Wall Type"]) &
(survey_results_with_original_features["Roof Type"] == property["Roof Type"]) &
(survey_results_with_original_features["Heating"] == property["Heating"])
]
if surveyed_similar.empty:
surveyed_similar = survey_results_with_original_features[
(survey_results_with_original_features["Postal Region"] == property["Postal Region"]) &
(survey_results_with_original_features["Property Type"] == property["Property Type"]) &
(survey_results_with_original_features["Wall Type"] == property["Wall Type"]) &
(survey_results_with_original_features["Roof Type"] == property["Roof Type"]) &
(survey_results_with_original_features["Heating"] == property["Heating"])
]
surveyed_same_region = survey_results_with_original_features[
(survey_results_with_original_features["Postal Region"] == property["Postal Region"]) &
(survey_results_with_original_features["Property Type"] == property["Property Type"])
]
if surveyed_similar.empty:
final_missed_matches.append(
{
"Address ID": a_id,
"Confidence Tier": "5 - no similar property, needs survey to confirm"
}
)
continue
same_postcode = survey_results[
survey_results["Archetype ID"].isin(missed_archetypes) &
(survey_results["Postal Region"] == region)
][["Archetype ID", "Current EPC Band"]].drop_duplicates()
raise NotImplementedError("Implement me")
pd.isnull(region_assets["Current EPC Band"]).sum()
final_missed_matches = pd.DataFrame(final_missed_matches)
region_assets = region_assets.merge(
final_missed_matches,
on="Address ID",
how="left",
suffixes=("", "_method3")
)
region_assets["Confidence Tier"] = region_assets["Confidence Tier"].fillna(
region_assets["Confidence Tier_method3"]
)
region_assets = region_assets.drop(columns=["Confidence Tier_method3"])
region_assets["Current EPC Band"] = np.where(
region_assets["Confidence Tier"] == "5 - no similar property, needs survey to confirm",
"Unknown", region_assets["Current EPC Band"]
)
if pd.isnull(region_assets["Current EPC Band"]).sum():
raise Exception("Something went wrong")
# if __name__ == "__main__":
# main()