def METHOD_NAME(local_path: Path) -> pd.DataFrame:
    """Load snapshot data (as a dataframe) for current dataset.
    Parameters
    ----------
    local_path : Path or str
        Path to local snapshot file.
    Returns
    -------
    data : pd.DataFrame
        Snapshot data.
    """
    # Unzip data into a temporary folder.
    with tempfile.TemporaryDirectory() as temp_dir:
        z = zipfile.ZipFile(local_path)
        z.extractall(temp_dir)
        (filename,) = list(filter(lambda x: "(Normalized)" in x, os.listdir(temp_dir)))
        # Load data from main file.
        try:
            data = pd.read_csv(os.path.join(temp_dir, filename), encoding="latin-1")
        except pd.errors.ParserError:
            # Some files are impossible to parse (e.g. faostat_wcad) because column "Note" is poorly formatted.
            # Instead of skipping problematic rows, load the file skipping that problematic column.
            columns = pd.read_csv(
                os.path.join(temp_dir, filename), encoding="latin-1", on_bad_lines="skip", nrows=0
            ).columns
            columns = columns.drop("Note")
            data = pd.read_csv(os.path.join(temp_dir, filename), encoding="latin-1", usecols=columns)
    return data