code: def convert_Series_to_Hierarchical(
      obj, store=None, return_to_mtype=False
  ):
      """Convert series to a single-series hierarchical object.
  
      Adds two dimensions to the series to obtain a 3-level MultiIndex, 2 levels added.
  
      Assumes input is conformant with one of the three Series mtypes.
      This method does not perform full mtype checks, use mtype or check_is_mtype for
      checks.
  
      Parameters
      ----------
      obj: an object of scitype Series, of mtype pd.DataFrame, pd.Series, or np.ndarray.
      store: dict, optional
          converter store for back-conversion
      return_to_mtype: bool, optional (default=False)
          if True, also returns the str of the mtype converted to
  
      Returns
      -------
      returns a data container of mtype pd_multiindex_hier
      """
      obj_df = convert_to(
          obj, to_type="pd.DataFrame", as_scitype="Series"
      )
      obj_df = obj_df.copy()
      obj_df["__level1"] = 0
      obj_df["__level2"] = 0
      obj_df = obj_df.set_index(["__level1", "__level2"], append=True)
      obj_df = obj_df.reorder_levels([1, 2, 0])
  
      if return_to_mtype:
          return obj_df, "pd_multiindex_hier"
      else:
          return obj_df
  
file_path: sktime/sktime/datatypes/_series_as_panel/_convert.py
imports: import numpy
  import pandas
  from sktime.datatypes import convert_to, scitype
label_desc: Use image node_id 3 for calling a global function with example usage: convert_Series_to_Hierarchical(obj, store, return_to_mtype) and returns: obj_df,  str, obj_df