code: def __init__(
      self,
      size=None,
      frac=None,
      replace=None,
      weights=None,
      seed=None,
      axis=None,
      random_state=None,
      always_multinomial=None,
      chunk_samples=None,
      **kw,
  ):
      super().__init__(
          _size=size,
          _frac=frac,
          _replace=replace,
          _weights=weights,
          _seed=seed,
          _axis=axis,
          _random_state=random_state,
          _always_multinomial=always_multinomial,
          _chunk_samples=chunk_samples,
          **kw,
      )
  
imports: import copy
  import itertools
  import numpy
  from ...None import opcodes
  from ...core import ENTITY_TYPE, get_output_types, recursive_tile
  from ...serialization.serializables import BoolField, AnyField, Int8Field, Int64Field, Float64Field, KeyField
  from ...tensor import searchsorted
  from ...tensor.base import TensorMapChunk
  from ...tensor.merge import TensorConcatenate
  from ...tensor.random import RandomState, RandomStateField
  from ...tensor.utils import normalize_chunk_sizes, gen_random_seeds
  from ...utils import has_unknown_shape, ceildiv
  from ..operands import DataFrameOperandMixin, DataFrameOperand
  from ..utils import validate_axis, parse_index
label_desc: Use image node_id 1 to create a new DataFrameSample object from inherited base classes: DataFrameOperand, DataFrameOperandMixin with example: obj = DataFrameSample(size, frac, replace, weights, seed, axis, random_state, always_multinomial, chunk_samples)