docstr: Load this data into a set of nodes and edges
  
  Returns:
      A tuple ``(graph, edges)``
  
      ``graph`` is a :class:`.StellarGraph` containing all the data. Timestamp information on
      edges are encoded as edge weights.
  
      ``edges`` are the original edges from the dataset which are sorted in ascending
      order of time - these can be used to create train/test splits based on time values.
  
      Node IDs in the returned data structures are all converted to strings to allow for
      compatibility with with ``gensim``'s ``Word2Vec`` model.
docstr_tok: ["Load","this","data","into","a","set","of","nodes","and","edges","Returns",":","A","tuple","``","(","graph",",","edges",")","``","``","graph","``","is","a",":","class",":","`",".StellarGraph","`","containing","all","the","data",".","Timestamp","information","on","edges","are","encoded","as","edge","weights",".","``","edges","``","are","the","original","edges","from","the","dataset","which","are","sorted","in","ascending","order","of","time","-","these","can","be","used","to","create","train\/test","splits","based","on","time","values",".","Node","IDs","in","the","returned","data","structures","are","all","converted","to","strings","to","allow","for","compatibility","with","with","``","gensim","``","'s","``","Word2Vec","``","model","."]
code: def load(self):
      """
      Load this data into a set of nodes and edges
  
      Returns:
          A tuple ``(graph, edges)``
  
          ``graph`` is a :class:`.StellarGraph` containing all the data. Timestamp information on
          edges are encoded as edge weights.
  
          ``edges`` are the original edges from the dataset which are sorted in ascending
          order of time - these can be used to create train/test splits based on time values.
  
          Node IDs in the returned data structures are all converted to strings to allow for
          compatibility with with ``gensim``'s ``Word2Vec`` model.
      """
      self.download()
  
      edges_path = self._resolve_path("ia-enron-employees.edges")
      edges = pd.read_csv(
          edges_path,
          sep=" ",
          header=None,
          names=["source", "target", "x", "time"],
          usecols=["source", "target", "time"],
      )
      edges[["source", "target"]] = edges[["source", "target"]].astype(
          str
      )
  
      nodes = pd.DataFrame(
          index=np.unique(
              pd.concat(
                  [edges["source"], edges["target"]], ignore_index=True
              )
          )
      )
  
      return (
          StellarGraph(
              nodes=nodes, edges=edges, edge_weight_column="time"
          ),
          edges,
      )
  
imports: from .dataset_loader import DatasetLoader
  from ..core.graph import StellarGraph, StellarDiGraph
  import itertools
  import logging
  import os
  import pandas
  import numpy
  from sklearn import preprocessing
  from ..core.experimental import experimental
label_desc: Use image node_id 1 for calling the IAEnronEmployees obj's underlying member method code with example usage: obj.load() and returns: StellarGraph,  edges