def ensure_series_data_type()

in src/smclarify/bias/metrics/common.py [0:0]

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

def ensure_series_data_type(series: pd.Series, values: Optional[List[Any]] = None) -> Tuple[DataType, pd.Series]:
    """
    Determine the type of the given data series using set of rules, and then do necessary type conversion
    to ensure the series data type.
    :param series: data for facet/label/predicted_label columns
    :param values: list of facet or label values provided by user
    :return: A tuple of DataType and the converted data series
    """
    data_type = series_datatype(series, values)
    if data_type == DataType.CATEGORICAL:
        return data_type, series.astype("category")
    elif data_type == DataType.CONTINUOUS:
        if values:
            if not (isinstance(values[0], int) or isinstance(values[0], float)):
                try:
                    values[0] = float(values[0])
                except ValueError:
                    raise ValueError(
                        "Facet/label value provided must be a single numeric threshold for continuous data"
                    )
        return data_type, pd.to_numeric(series)
    raise ValueError("Data series is invalid or can't be classified as neither categorical nor continous.")