59 lines
1.9 KiB
Python
59 lines
1.9 KiB
Python
import pandas as pd
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INPUT_XLSX = "data.xlsx"
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OUTPUT_XLSX = "task1/01_clean.xlsx"
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SHEET_NAME = "addresses2019 updated"
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def main() -> None:
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df_raw = pd.read_excel(INPUT_XLSX, sheet_name=SHEET_NAME)
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required = [
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"Site Name",
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"latitude",
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"longitude",
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"Number of Visits in 2019",
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"Average Demand per Visit",
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"StDev(Demand per Visit)",
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]
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missing = [c for c in required if c not in df_raw.columns]
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if missing:
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raise ValueError(f"Missing required columns: {missing}")
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df = df_raw[required].copy()
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df = df.rename(
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columns={
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"Site Name": "site_name",
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"latitude": "lat",
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"longitude": "lon",
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"Number of Visits in 2019": "visits_2019",
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"Average Demand per Visit": "mu_clients_per_visit",
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"StDev(Demand per Visit)": "sd_clients_per_visit",
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}
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)
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df.insert(0, "site_id", range(1, len(df) + 1))
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numeric_cols = ["lat", "lon", "visits_2019", "mu_clients_per_visit", "sd_clients_per_visit"]
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for col in numeric_cols:
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df[col] = pd.to_numeric(df[col], errors="coerce")
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if df["site_name"].isna().any():
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raise ValueError("Found missing site_name values.")
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if df[numeric_cols].isna().any().any():
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bad = df[df[numeric_cols].isna().any(axis=1)][["site_id", "site_name"] + numeric_cols]
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raise ValueError(f"Found missing numeric values:\n{bad}")
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if (df["mu_clients_per_visit"] < 0).any() or (df["sd_clients_per_visit"] < 0).any():
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raise ValueError("Found negative mu/sd values; expected nonnegative.")
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if (df["visits_2019"] <= 0).any():
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raise ValueError("Found non-positive visits_2019; expected >0 for all 70 regular sites.")
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with pd.ExcelWriter(OUTPUT_XLSX, engine="openpyxl") as writer:
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df.to_excel(writer, index=False, sheet_name="sites")
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if __name__ == "__main__":
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main()
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