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setting up ha24 matching

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Khalim Conn-Kowlessar 2023-12-27 13:29:29 +00:00
parent c7972fc88d
commit 975a9fa9a0
1 changed files with 51 additions and 0 deletions
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51
etl/eligibility/ha_15_32/ha24_app.py
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@ -54,6 +54,21 @@ def load_data():
np.where(asset_list["row_colour_name"] == "green", "identified potential eco", "maybe in the future")
)
# The third column is listed as "Address" but it's actually the postcode". We have two Address columns so we
# change just the third
asset_list.columns.values[2] = "Postcode"
# Split up the address on commas, which is useful for matching later
split_addresses = asset_list['Address'].str.split(',', expand=True)
split_addresses.columns = ['temp', 'address2', 'address3', 'address4', 'address5', 'address6']
asset_list = pd.concat([asset_list, split_addresses], axis=1)
# There is no commas separating house number and address 1
split_addresses2 = asset_list['temp'].str.split(' ', expand=True)
split_addresses2.columns = ['HouseNo', 'part1', 'part2', "part3", "part4"]
# We could re-concatenate but we only care about HouseNo for the moment
asset_list = pd.concat([asset_list, split_addresses2[["HouseNo"]]], axis=1)
# Read in surveys
survey_workbook = openpyxl.load_workbook(f'etl/eligibility/ha_15_32/HESTIA - HA 24 ECO4 SURVEY LIST.xlsx')
survey_sheet = survey_workbook.active
@ -69,5 +84,41 @@ def load_data():
survey_colors.append(row_color)
survey_list = pd.DataFrame(survey_rows, columns=[cell.value for cell in survey_sheet[1]])
survey_list["row_colour"] = survey_colors
survey_list["survey_key"] = ["survey_" + str(i) for i in range(0, len(survey_list))]
# Tidy up the street/block name a bit
survey_list["Street / Block Name"] = survey_list["Street / Block Name"].str.replace("/", ", ")
survey_list["Street / Block Name"] = survey_list["Street / Block Name"].str.lower()
# Drop all None rows
survey_list = survey_list.dropna(how='all')
survey_list["survey_key"] = ["survey_" + str(i) for i in range(0, len(survey_list))]
matched = []
for _, row in tqdm(survey_list.iterrows(), total=len(survey_list)):
house_number = row["NO."]
if isinstance(house_number, str):
house_number = house_number.lower()
# Filter on the first line of the address
df = asset_list[asset_list["Address"].str.lower().str.contains(row["Street / Block Name"].lower())].copy()
# df = df[df["Postcode"].str.lower().str.contains(row["Post Code"].lower())]
df = df[df["Address"].str.lower().str.contains(str(house_number))]
if df.shape[0] != 1:
df = df[df["HouseNo"] == str(house_number)]
if df.shape[0] != 1:
df = df[df["Postcode"].str.lower().str.contains(row["Post Code"].lower())]
if df.shape[0] != 1:
raise ValueError("Investigate")
matched.append(
{
"survey_key": row["survey_key"],
"matched_address": df["Address"].values[0],
"survey_house_no": row["NO."],
"survey_street_name": row["Street / Block Name"],
"survey_postcode": row["Post Code"],
"survey_status": row["INSTALLED OR CANCELLED"]
}
)