code: def homogenize(series_dict):
      
      index = None
  
      need_reindex = False
  
      for _, series in series_dict.items():
          if not np.isnan(series.fill_value):
              raise TypeError('this method is only valid with NaN fill values')
  
          if index is None:
              index = series.sp_index
          elif not series.sp_index.equals(index):
              need_reindex = True
              index = index.intersect(series.sp_index)
  
      if need_reindex:
          output = {}
          for name, series in series_dict.items():
              if not series.sp_index.equals(index):
                  series = series.sparse_reindex(index)
  
              output[name] = series
      else:
          output = series_dict
  
      return output
docs: Conform a set of SparseSeries (with NaN fill_value) to a common SparseIndex
      corresponding to the locations where they all have data
  
      Parameters
      ----------
      series_dict : dict or DataFrame
  
      Notes
      -----
      Using the dumbest algorithm I could think of. Should put some more thought
      into this
  
      Returns
      -------
      homogenized : dict of SparseSeries