def std_conversion(period_std, base_period):
    """
    one_period_len standard deviation (or standard error) approximation

    Parameters
    ----------
    period_std: pd.DataFrame
        DataFrame containing standard deviation or standard error values
        with column headings representing the return period.
    base_period: string
        The base period length used in the conversion
        It must follow pandas.Timedelta constructor format (e.g. '1 days',
        '1D', '30m', '3h', '1D1h', etc)

    Returns
    -------
    pd.DataFrame
        DataFrame in same format as input but with one-period
        standard deviation/error values.
    """
    period_len = period_std.name
    conversion_factor = (pd.Timedelta(period_len) /
                         pd.Timedelta(base_period))
    return period_std / np.sqrt(conversion_factor)
def std_conversion ( period_std , base_period ) : period_len = period_std . name conversion_factor = ( pd . Timedelta ( period_len ) / pd . Timedelta ( base_period ) ) return period_std / np . sqrt ( conversion_factor )
one_period_len standard deviation (or standard error) approximation

    Parameters
    ----------
    period_std: pd.DataFrame
        DataFrame containing standard deviation or standard error values
        with column headings representing the return period.
    base_period: string
        The base period length used in the conversion
        It must follow pandas.Timedelta constructor format (e.g. '1 days',
        '1D', '30m', '3h', '1D1h', etc)

    Returns
    -------
    pd.DataFrame
        DataFrame in same format as input but with one-period
        standard deviation/error values.