docs: 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