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60 lines
2 KiB
Python
60 lines
2 KiB
Python
"""
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The data held on file for MHS is fairly incomplete, where not every single property has an observation
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"""
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from tqdm import tqdm
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import pandas as pd
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from docutils.utils.math.tex2mathml_extern import blahtexml
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asset_list = pd.read_excel(
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"/Users/khalimconn-kowlessar/Documents/hestia/Customers/MHS/MHS HOMES (Full Asset List) - for analysis.xlsx",
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sheet_name="Data"
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)
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# When this list was checked, an observation was made per postcode, and so we need to extrapolate those findings
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inspections_observatons = asset_list[["UPRN", "Postcode", "ManagementGroup", "WFT Findings"]].copy()
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populated = []
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for _, group in tqdm(inspections_observatons.groupby("Postcode"),
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total=len(inspections_observatons.groupby("Postcode"))):
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if all(pd.isnull(group["WFT Findings"])):
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group["WFT Findings"] = "Property not inspected"
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populated.append(group)
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continue
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fill_observation = group["WFT Findings"].values[0]
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if pd.isnull(fill_observation):
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group["WFT Findings"] = group["WFT Findings"].fillna("Property not inspected")
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populated.append(group)
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continue
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group = group.reset_index(drop=True)
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group_filled = []
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for idx, x in group.iterrows():
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if idx == 0:
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group_filled.append(x)
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continue
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new_value = x["WFT Findings"]
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if not pd.isnull(new_value):
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fill_observation = new_value
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x["WFT Findings"] = fill_observation
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group_filled.append(x)
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group_filled = pd.DataFrame(group_filled)
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populated.append(group_filled)
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populated = pd.concat(populated)
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missed = populated[~populated["UPRN"].isin(asset_list["UPRN"].values)]
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asset_list = asset_list.drop(columns=["WFT Findings"]).merge(
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populated.drop(columns=["Postcode", "ManagementGroup"]), how="left", on="UPRN"
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)
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# Store the data
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asset_list.to_excel(
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"/Users/khalimconn-kowlessar/Documents/hestia/Customers/MHS/MHS HOMES (Full Asset List) - for programme build.xlsx"
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)
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