code: def _infer_main_columns(df, index_level='Column Name', numeric_dtypes=_numeric_dtypes):
      
      columns = df.columns.get_level_values(index_level)
      main_columns = []
      for i,dtype in enumerate(df.dtypes):
          if dtype in numeric_dtypes:
              main_columns.append(columns[i])
          else:
              break
      return main_columns
docs: All numeric columns up-until the first non-numeric column are considered main columns.
      :param df: The pd.DataFrame
      :param index_level: Name of the index level of the column names. Default 'Column Name'
      :param numeric_dtypes: Set of numpy.dtype containing all numeric types. Default int/float.
      :returns: The names of the infered main columns