docstr: Inserts dictionary of meta data terms into object.
  
  Parameters
  ----------
  term_dict: dict {metadataname: [term1, term2, ....], ...}
  
  Returns
  -------
  self: ScatterChart
docstr_tok: ["Inserts","dictionary","of","meta","data","terms","into","object",".","Parameters","--","--","--","--","--","term_dict",":","dict","{","metadataname",":","[","term1",",","term2",",","....","]",",","...","}","Returns","--","--","--","-","self",":","ScatterChart"]
code: def inject_metadata_term_lists(self, term_dict):
      """
      Inserts dictionary of meta data terms into object.
  
      Parameters
      ----------
      term_dict: dict {metadataname: [term1, term2, ....], ...}
  
      Returns
      -------
      self: ScatterChart
      """
      check_topic_model_string_format(term_dict)
  
      if not self.term_doc_matrix.metadata_in_use():
          raise TermDocMatrixHasNoMetadataException(
              "No metadata is present in the term document matrix"
          )
  
      self.metadata_term_lists = term_dict
      return self
  
imports: import logging
  import sys
  import numpy
  import pandas
  from scipy.stats import rankdata
  from scattertext.PValGetter import get_p_vals
  from scattertext.Scalers import percentile_min, percentile_alphabetical
  from scattertext.ScatterChartData import ScatterChartData
  from scattertext.TermDocMatrixFilter import filter_bigrams_by_pmis, filter_out_unigrams_that_only_occur_in_one_bigram
  from scattertext.termscoring import ScaledFScore
  from scattertext.termscoring.RankDifference import RankDifference
  from scattertext.termscoring.CornerScore import CornerScore
label_desc: Use image node_id 2 for calling the ScatterChart obj's underlying member method code with example usage: obj.inject_metadata_term_lists(term_dict) and returns: self