code: def new_categorical(
      self, inputs, shape=None, dtype=None, categories_value=None, **kw
  ):
      if getattr(self, "output_limit") != 1:
          raise TypeError(
              "cannot new Categorical with more than 1 outputs"
          )
  
      return self.new_categoricals(
          inputs,
          shape=shape,
          dtype=dtype,
          categories_value=categories_value,
          **kw,
      )[0]
  
imports: from collections import OrderedDict
  from functools import reduce
  import numpy
  import pandas
  from ..core import FuseChunkData, FuseChunk, ENTITY_TYPE, OutputType
  from ..core.operand import Operand, TileableOperandMixin, Fuse, ShuffleProxy, FuseChunkMixin
  from ..tensor.core import TENSOR_TYPE
  from ..tensor.datasource import tensor
  from ..tensor.operands import TensorOperandMixin
  from ..utils import calc_nsplits
  from .core import DATAFRAME_CHUNK_TYPE, SERIES_CHUNK_TYPE, INDEX_CHUNK_TYPE, DATAFRAME_TYPE, SERIES_TYPE, INDEX_TYPE, DATAFRAME_GROUPBY_TYPE, SERIES_GROUPBY_TYPE, CATEGORICAL_TYPE
  from .utils import parse_index
label_desc: Use image node_id 11 for calling the DataFrameOperandMixin obj's underlying member method code with example usage: obj.new_categorical(inputs, shape, dtype, categories_value) and returns: self