"""
The data held on file for MHS is fairly incomplete, where not every single property has an observation
"""
from tqdm import tqdm
import pandas as pd
from docutils.utils.math.tex2mathml_extern import blahtexml

asset_list = pd.read_excel(
    "/Users/khalimconn-kowlessar/Documents/hestia/Customers/MHS/MHS HOMES (Full Asset List) - for analysis.xlsx",
    sheet_name="Data"
)
# When this list was checked, an observation was made per postcode, and so we need to extrapolate those findings
inspections_observatons = asset_list[["UPRN", "Postcode", "ManagementGroup", "WFT Findings"]].copy()

populated = []
for _, group in tqdm(inspections_observatons.groupby("Postcode"),
                     total=len(inspections_observatons.groupby("Postcode"))):

    if all(pd.isnull(group["WFT Findings"])):
        group["WFT Findings"] = "Property not inspected"
        populated.append(group)
        continue

    fill_observation = group["WFT Findings"].values[0]
    if pd.isnull(fill_observation):
        group["WFT Findings"] = group["WFT Findings"].fillna("Property not inspected")
        populated.append(group)
        continue

    group = group.reset_index(drop=True)

    group_filled = []
    for idx, x in group.iterrows():
        if idx == 0:
            group_filled.append(x)
            continue

        new_value = x["WFT Findings"]
        if not pd.isnull(new_value):
            fill_observation = new_value

        x["WFT Findings"] = fill_observation
        group_filled.append(x)

    group_filled = pd.DataFrame(group_filled)

    populated.append(group_filled)

populated = pd.concat(populated)

missed = populated[~populated["UPRN"].isin(asset_list["UPRN"].values)]

asset_list = asset_list.drop(columns=["WFT Findings"]).merge(
    populated.drop(columns=["Postcode", "ManagementGroup"]), how="left", on="UPRN"
)

# Store the data
asset_list.to_excel(
    "/Users/khalimconn-kowlessar/Documents/hestia/Customers/MHS/MHS HOMES (Full Asset List) - for programme build.xlsx"
)