class_docstr: Class which stores vertex and edge properties that can be used to construct
  Graphs from individual property selections and used later to annotate graph
  algorithm results with corresponding properties.
class_docstr_tok: ["Class","which","stores","vertex","and","edge","properties","that","can","be","used","to","construct","Graphs","from","individual","property","selections","and","used","later","to","annotate","graph","algorithm","results","with","corresponding","properties","."]
docstr: Add a new category to a categorical dtype column of a dataframe.
  
  Returns the new categorical dtype.
docstr_tok: ["Add","a","new","category","to","a","categorical","dtype","column","of","a","dataframe",".","Returns","the","new","categorical","dtype","."]
code: def __update_categorical_dtype(self, df, column, val):
      """Add a new category to a categorical dtype column of a dataframe.
  
      Returns the new categorical dtype.
      """
      # Add `val` to the categorical dtype if necessary
      if val not in df.dtypes[column].categories:
          df[column] = df[column].cat.add_categories([val])
      return df.dtypes[column]
  
imports: import cudf
  import cupy
  import cugraph
  import dask_cudf
  import cugraph.dask
  from cugraph.utilities.utils import import_optional, create_list_series_from_2d_ar
  from typing import Union
label_desc: Use image node_id 45 for calling the EXPERIMENTAL__MGPropertyGraph obj's underlying member method code with example usage: obj.__update_categorical_dtype(df, column, val) and returns: df