def _get_inferred_data_column(column):
    """
    Calculate the m/m/m/m for column values.
    :param dict column: Column data
    :return dict column: Column data - modified
    """
    try:
        with warnings.catch_warnings():
            warnings.simplefilter("ignore")
            # Get the values for this column
            values = column["values"]
            # Make sure that age and values are numpy arrays
            _values = np.array(copy.copy(values), dtype=float)
            # If we have values, keep going
            if len(_values) != 0:
                # Remove the NaNs from the values list.
                _values = _values[np.where(~np.isnan(_values))[0]]
                # Use the values to create new entries and data
                column.update(__get_inferred_data_res_2(_values))

            # Even though we're not calculating resolution, still add it with "NaN" placeholders.
            column["hasResolution"] = __get_inferred_data_res_2(None, calc=False)

    except KeyError as e:
        logger_inferred_data.debug("get_inferred_data_column: KeyError: {}".format(e))
    except Exception as e:
        logger_inferred_data.debug("get_inferred_data_column: Exception: {}".format(e))

    return column
Calculate the m/m/m/m for column values.
    :param dict column: Column data
    :return dict column: Column data - modified