code: def map_concepts_to_indicators(
          self, n: int = 1, min_temporal_res: Optional[str] = None
      ):
          
  
          for node in self.nodes(data=True):
              query_parts = [
                  "select Indicator from concept_to_indicator_mapping",
                  f"where `Concept` like '{node[0]}'",
              ]
  
              # TODO May need to delve into SQL/database stuff a bit more deeply
              # for this. Foreign keys perhaps?
  
              query = "  ".join(query_parts)
              results = engine.execute(query)
  
              if min_temporal_res is not None:
                  if min_temporal_res not in ["month"]:
                      raise ValueError("min_temporal_res must be 'month'")
  
                  vars_with_required_temporal_resolution = [
                      r[0]
                      for r in engine.execute(
                          "select distinct `Variable` from indicator where "
                          f"`{min_temporal_res.capitalize()}` is not null"
                      )
                  ]
                  results = [
                      r
                      for r in results
                      if r[0] in vars_with_required_temporal_resolution
                  ]
  
              node[1]["indicators"] = {
                  x: Indicator(x, "MITRE12")
                  for x in [r[0] for r in take(n, results)]
              }
docs: Map each concept node in the AnalysisGraph instance to one or more
          tangible quantities, known as 'indicators'.
  
          Args:
              n: Number of matches to keep
              min_temporal_res: Minimum temporal resolution that the indicators
              must have data for.