custom_metrics.py

@metric("median")
def median_metric(data: DataFrame) -> Optional[Union[float, int]]:
    """Computes the median of a data series.
    Args:
        data: Data series.
    Returns:
        DataFrame median value or None if DataFrame is empty.
    """
    series = df_to_series(data)
    if len(series) == 0:
        return None

    return series.median()


@metric("min")
def min_metric(data: DataFrame) -> Optional[Union[float, int]]:
    """Computes the minimum of a data series.
    Args:
        data: Data series.
    Returns:
        DataFrame minimum value or None if DataFrame is empty.
    """
    series = df_to_series(data)
    if len(series) == 0:
        return None

    return series.min()


@metric("max")
def max_metric(data: DataFrame) -> Optional[Union[float, int]]:
    """Computes the maximum of a data series.
    Args:
        data: Data series.
    Returns:
        DataFrame maximum value or None if DataFrame is empty.
    """
    series = df_to_series(data)
    if len(series) == 0:
        return None

    return series.max()


@metric("std")
def std_metric(data: DataFrame) -> Optional[float]:
    """Computes the standard deviation on a data series.
    Args:
        data: Data series.
    Returns:
        Standard deviation of series or None if DataFrame is empty.
    """
    series = df_to_series(data)
    if len(series) == 0:
        return None

    return series.std()