code: def from_pandas_edgelist(
      df,
      source="source",
      destination="destination",
      edge_attr=None,
      create_using=Graph,
      renumber=True,
  ):
      """
      Initialize a graph from the edge list. It is an error to call this
      method on an initialized Graph object. Source argument is source
      column name and destination argument is destination column name.
  
      By default, renumbering is enabled to map the source and destination
      vertices into an index in the range [0, V) where V is the number
      of vertices.  If the input vertices are a single column of integers
      in the range [0, V), renumbering can be disabled and the original
      external vertex ids will be used.
  
      If weights are present, edge_attr argument is the weights column name.
  
      Parameters
      ----------
      df : pandas.DataFrame
          A DataFrame that contains edge information
  
      source : str or array-like, optional (default='source')
          source column name or array of column names
  
      destination : str or array-like, optional (default='destination')
          destination column name or array of column names
  
      edge_attr : str or None, optional (default=None)
          the weights column name.
  
      renumber : bool, optional (default=True)
          Indicate whether or not to renumber the source and destination
          vertex IDs.
  
      create_using: cugraph.Graph (instance or class), optional (default=Graph)
          Specify the type of Graph to create. Can pass in an instance to create
          a Graph instance with specified 'directed' attribute.
  
      Returns
      -------
      G : cugraph.Graph
          Graph containing edges from the pandas edgelist
  
      Examples
      --------
      >>> #  Download dataset from
      >>> #  https://github.com/rapidsai/cugraph/datasets/...
      >>> df = pd.read_csv(datasets_path / 'karate.csv', delimiter=' ',
      ...                  header=None, names=["0", "1", "2"],
      ...                  dtype={"0": "int32", "1": "int32", "2": "float32"})
      >>> G = cugraph.Graph()
      >>> G.from_pandas_edgelist(df, source='0', destination='1',
      ...                        edge_attr='2', renumber=False)
  
      """
      if create_using is None:
          G = Graph()
      elif isinstance(create_using, Graph):
          attrs = {"directed": create_using.is_directed()}
          G = type(create_using)(**attrs)
      elif type(create_using) is type(Graph):
          G = create_using()
      else:
          raise TypeError(
              "create_using must be a cugraph.Graph "
              "(or subclass) type or instance, got: "
              f"{type(create_using)}"
          )
  
      G.from_pandas_edgelist(
          df,
          source=source,
          destination=destination,
          edge_attr=edge_attr,
          renumber=renumber,
      )
      return G
  
file_path: cugraph/python/cugraph/cugraph/structure/convert_matrix.py
imports: import cudf
  import dask_cudf
  from cugraph.structure.graph_classes import Graph
label_desc: Use image node_id 4 for calling a global function with example usage: from_pandas_edgelist(df, source, destination, edge_attr, create_using, renumber) and returns: G