code: def get_graphistry_from_milieu_search(
      search_term, src, dst, node_col, edf, ndf, both=False
  ):
      """
          Produces large graphs of neighbors from a given search term
      :param search_term:
      :param src:
      :param dst:
      :param node_col:
      :param edf:
      :param ndf:
      :param both:
      :return:
      """
      tdf = get_milieu_graph_from_search(
          search_term, src, dst, edf, both=both
      )
      gcols = pd.concat(
          [tdf[dst], tdf[src]], axis=0
      )  # get all node entries that show up in edge graph
      ntdf = ndf[ndf[node_col].isin(gcols)]
      g = graphistry.edges(tdf, src, dst).nodes(ntdf, node_col)
      return g
  
file_path: pygraphistry/graphistry/ai_utils.py
imports: import pandas
  import numpy
  import graphistry
  from .constants import DISTANCE, WEIGHT, BATCH
  from logging import getLogger
label_desc: Use image node_id 5 for calling a global function with example usage: get_graphistry_from_milieu_search(search_term, src, dst, node_col, edf, ndf, both) and returns: g