code: def summary_df_from_array(results_array, names, axis=0, **kwargs):
      
      assert axis == 0 or axis == 1
      df = pd.DataFrame(results_array)
      if axis == 1:
          df = df.T
      df.columns = names
      return summary_df(df, **kwargs)
docs: Make a panda data frame of the mean and std devs of an array of results,
      including the uncertainties on the values.
  
      This function converts the array to a DataFrame and calls summary_df on it.
  
      Parameters
      ----------
      results_array: 2d numpy array
      names: list of str
          Names for the output df's columns.
      axis: int, optional
          Axis on which to calculate summary statistics.
  
      Returns
      -------
      df: MultiIndex DataFrame
          See summary_df docstring for more details.