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fixing missed matches
This commit is contained in:
Khalim Conn-Kowlessar
parent
cb9399a704
commit
51c2d04a6d
1 changed files with 59 additions and 21 deletions
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@ -741,26 +741,53 @@ def main():
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# We now merge on the coordinator data so that against each property, we can map the measures
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retrofit_packages_board = pd.read_excel(
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os.path.join(CUSTOMER_FOLDER_PATH, "Stonewater_SHDF_3_0_Board_work_in_progress_- 22.10.24.xlsx"),
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os.path.join(CUSTOMER_FOLDER_PATH, "Stonewater 3.0 Updated SAP Pre & Modelled 29.10.24.xlsx"),
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header=4
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)
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retrofit_packages_board = retrofit_packages_board[~pd.isnull(retrofit_packages_board["Name"])]
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# Take just the rows that have been surveyed
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retrofit_packages_board = retrofit_packages_board[
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retrofit_packages_board["RA"].isin(["Invoiced", "Completed"])
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]
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# Replace \n with ""
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extracted_data["Postcode"] = extracted_data["Postcode"].str.replace("\n", "")
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manual_filters = {
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"Flat 21 Walmer Street": "StonewaterSurveys_14/91-1-Flat 21 Walmer Street-HR4 9JD",
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"6 Cornewall Close": "StonewaterSurveys_14/aa 6, Cornewall Close, Moccas, HEREFORD, HR2 9LG",
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"1 Cluny Way": "12-1-1 Cluny Way-SG15 6ZB",
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"2 Bromyard Road": "StonewaterSurveys_4/192-9-2 Bromyard Road-WR15 8BZ",
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'Flat 18, 1 Raglan Court': "StonewaterSurveys_13/60-3-18 Raglan Court, 1 Raglan Court-MK41 8QT",
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'14 Raglan Court, 1 Devizes Avenue': 'StonewaterSurveys_12/55-3-14 Raglan Court, Devizes Avenue-MK41 8QT',
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'19 South Road': 'StonewaterSurveys_4/19 The Oaks, South Road, SMETHWICK, B67 7BY',
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'Flat 12 Pelican Lane': 'StonewaterSurveys_1/121-3-Flat 12 Lynton Court, Pelican Lane-RG14 1NN',
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'Flat C, 44 St Leonards Avenue': 'StonewaterSurveys_11/427-2-44c St. Leonards Avenue-MK42 0RB',
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}
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# We now match this retrofit packages board to the extracted data
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matching_lookup = []
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for _, home in tqdm(retrofit_packages_board.iterrows(), total=len(retrofit_packages_board)):
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# Handle the case that has the wrong postcode in the asset data
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if home["Name"] == "Flat 21 Walmer Street":
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filtered = extracted_data[
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extracted_data["survey_folder"] == "StonewaterSurveys_14/91-1-Flat 21 Walmer Street-HR4 9JD"
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].copy()
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if home["Address ID"] == 6111566:
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blah
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# 6118117, 6118744, 6117091
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if home["Name"] in manual_filters:
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filtered = extracted_data[extracted_data["survey_folder"] == manual_filters[home["Name"]]].copy()
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else:
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filtered = extracted_data[extracted_data["Postcode"].str.lower() == home["Postcode"].lower()].copy()
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filtered["survey_folder"].values
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# We check that home["Name"] is contained in the survey_folder, after removing punctuation and spaces
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filtered = filtered[filtered["survey_folder"].str.replace(r"[^\w\s]", "").str.contains(
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home["Name"].replace(r"[^\w\s]", ""), case=False
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)]
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# We check that home["Name"] is contained in the survey_folder, after removing punctuation and spaces
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to_filter = filtered["survey_folder"].str.replace(r"[^\w\s]", "").str.contains(
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home["Name"].replace(r"[^\w\s]", "").replace("Flat", "").lstrip(), case=False
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)
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if to_filter.sum() == 0:
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to_filter = filtered["survey_folder"].str.replace(r"[^\w\s]", "").str.replace(",", "").str.replace(".",
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"").str.contains(
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home["Name"].replace(r"[^\w\s]", "").replace(",", ""), case=False
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)
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filtered = filtered[to_filter]
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if filtered.empty:
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continue
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@ -769,7 +796,7 @@ def main():
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matching_lookup.append(
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{
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"survey_folder": filtered["survey_folder"].values[0],
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"Osm. ID": home["Osm. ID"],
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"Address ID": home["Address ID"],
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"Name": home["Name"]
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}
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)
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@ -797,15 +824,23 @@ def main():
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matching_lookup.append(
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{
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"survey_folder": filtered["survey_folder"].values[0],
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"Osm. ID": home["Osm. ID"],
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"Address ID": home["Address ID"],
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"Name": home["Name"]
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}
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)
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matching_lookup = pd.DataFrame(matching_lookup)
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# Find Osmosis IDs that are in the packages board but not in the matching looking
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# missing_osm_ids = set(retrofit_packages_board["Osm. ID"]) - set(matching_lookup["Osm. ID"])
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# missing_osm_ids = list(missing_osm_ids)
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missing_ids = set(retrofit_packages_board["Address ID"]) - set(matching_lookup["Address ID"])
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missing_ids = list(missing_ids)
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print(len(missing_ids))
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if missing_ids:
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# We check that the missing ids have no data yet
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missing_data = retrofit_packages_board[retrofit_packages_board["Address ID"].isin(missing_ids)][
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["Name", "Address ID", "Archetype ID"]]
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extracted_data[extracted_data["survey_folder"].str.contains("23 Monmouth")]["survey_folder"].values
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matching_lookup[matching_lookup["survey_folder"].str.contains("23 Monmouth")]
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if matching_lookup["Osm. ID"].duplicated().sum():
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raise Exception("Duplicate Osm. IDs")
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@ -834,7 +869,6 @@ def main():
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retrofit_packages_board[
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[
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"Name",
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"Osm. ID",
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"Address ID",
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"Archetype ID",
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"Arch. Group Rank", "Archetype Representative",
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@ -848,6 +882,14 @@ def main():
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how="left"
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)
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# Create a section for costs
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for measure in measure_columns:
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stonewater_data[f"Cost of {measure}"] = None
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stonewater_data["Total Cost of Measures"] = None
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stonewater_data["Contingency Cost"] = None
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stonewater_data["Total Cost of Measures inc Contingency"] = None
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# We've appended the recommended packages and modelled SAP ratings to the data
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# We also want to append the windows data
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windows_data = pd.read_excel(
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@ -878,12 +920,8 @@ def main():
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windows_data["Years since fitted/renewed"] = (pd.Timestamp.now() - windows_data[
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"Fitted/renewed date"]).dt.days / 365
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# TODO: Flag if a package includes windows
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# Save this as a csv
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# extracted_data.to_csv("Wave 3 Summary Data - first 200 files.csv", index=False)
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missed = [f for f in survey_folders if f not in extracted_data["survey_folder"].tolist()]
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stonewater_data["Package Includes Windows"] = ~pd.isnull(stonewater_data["Window Upgrade"])
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stonewater_data = stonewater_data.merge(windows_data, on="Osm. ID", how="left")
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# if __name__ == "__main__":
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# main()
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