def main()

in covid19_spread/data/usa/symptom_survey/process_symptom_survey.py [0:0]

• 23 lines of code
• 7 McCabe index (conditional complexity)

def main(signal, resolution):
    source, signal = signal.split("/")
    df = get_df(source, signal, resolution)

    if resolution == "county":
        # Fill in missing counties with zeros
        cases = pd.read_csv(
            f"{SCRIPT_DIR}/../data_cases.csv", index_col="region"
        ).index.to_frame()
        cases["state"] = [x.split(", ")[-1] for x in cases.index]
        cases = cases.drop(columns="region")
        idx = pd.MultiIndex.from_product([cases.index, df["type"].unique()])
        type_ = df["type"].iloc[0]
        df = df.reset_index().set_index(["loc", "type"]).reindex(idx).fillna(0)
        df2 = get_df(source, signal, "state")
        df2 = df2.merge(cases[["state"]], left_index=True, right_on="state")[
            df2.columns
        ]
        df = pd.concat([df, df2.set_index("type", append=True)])

    df = df[[c for c in df.columns if isinstance(c, datetime)]]
    df.columns = [str(x.date()) if isinstance(x, datetime) else x for x in df.columns]

    df.round(3).to_csv(
        f"{SCRIPT_DIR}/{source}_{signal}-{resolution}.csv",
        index_label=["region", "type"],
    )