class_docstr: A GPU Graph Object (Base class of other graph types)
  
  Parameters
  ----------
  m_graph : cuGraph.MultiGraph object or None (default=None)
      Initialize the graph from a cugraph.MultiGraph object
  directed : boolean, optional (default=False)
      Indicated is the graph is directed.
  
  Examples
  --------
  >>> # undirected graph
  >>> G = cugraph.Graph()
  >>> # directed graph
  >>> G = cugraph.Graph(directed=True)
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docstr: Given a DataFrame containing internal vertex ids in the identified
  column, replace this with external vertex ids. If the renumbering
  is from a single column, the output dataframe will use the same
  name for the external vertex identifiers.  If the renumbering is from
  a multi-column input, the output columns will be labeled 0 through
  n-1 with a suffix of _column_name.
  Note that this function does not guarantee order in single GPU mode,
  and does not guarantee order or partitioning in multi-GPU mode. If you
  wish to preserve ordering, add an index column to df and sort the
  return by that index column.
  
  Parameters
  ----------
  df: cudf.DataFrame or dask_cudf.DataFrame
      A DataFrame containing internal vertex identifiers that will be
      converted into external vertex identifiers.
  
  column_name: string
      Name of the column containing the internal vertex id.
  
  preserve_order: bool, optional (default=False)
      If True, preserve the order of the rows in the output DataFrame to
      match the input DataFrame
  
  get_column_names: bool, optional (default=False)
      If True, the unrenumbered column names are returned.
  
  Returns
  -------
  df : cudf.DataFrame or dask_cudf.DataFrame
      The original DataFrame columns exist unmodified.  The external
      vertex dentifiers are added to the DataFrame, the internal
      vertex identifier column is removed from the dataframe.
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code: def unrenumber(
      self,
      df,
      column_name,
      preserve_order=False,
      get_column_names=False,
  ):
      """
      Given a DataFrame containing internal vertex ids in the identified
      column, replace this with external vertex ids. If the renumbering
      is from a single column, the output dataframe will use the same
      name for the external vertex identifiers.  If the renumbering is from
      a multi-column input, the output columns will be labeled 0 through
      n-1 with a suffix of _column_name.
      Note that this function does not guarantee order in single GPU mode,
      and does not guarantee order or partitioning in multi-GPU mode. If you
      wish to preserve ordering, add an index column to df and sort the
      return by that index column.
  
      Parameters
      ----------
      df: cudf.DataFrame or dask_cudf.DataFrame
          A DataFrame containing internal vertex identifiers that will be
          converted into external vertex identifiers.
  
      column_name: string
          Name of the column containing the internal vertex id.
  
      preserve_order: bool, optional (default=False)
          If True, preserve the order of the rows in the output DataFrame to
          match the input DataFrame
  
      get_column_names: bool, optional (default=False)
          If True, the unrenumbered column names are returned.
  
      Returns
      -------
      df : cudf.DataFrame or dask_cudf.DataFrame
          The original DataFrame columns exist unmodified.  The external
          vertex dentifiers are added to the DataFrame, the internal
          vertex identifier column is removed from the dataframe.
      """
      return self.renumber_map.unrenumber(
          df, column_name, preserve_order, get_column_names
      )
  
imports: import numpy
  from .graph_implementation import simpleGraphImpl, simpleDistributedGraphImpl, npartiteGraphImpl
  import cudf
  import dask_cudf
  from cugraph.utilities.utils import import_optional
label_desc: Use image node_id 11 for calling the Graph obj's underlying member method code with example usage: obj.unrenumber(df, column_name, preserve_order, get_column_names) and returns: self