class_docstr: A Column object for Numeric types.
  
  Parameters
  ----------
  data : Buffer
  dtype : np.dtype
      The dtype associated with the data Buffer
  mask : Buffer, optional
class_docstr_tok: ["A","Column","object","for","Numeric","types",".","Parameters","--","--","--","--","--","data",":","Buffer","dtype",":","np.dtype","The","dtype","associated","with","the","data","Buffer","mask",":","Buffer",",","optional"]
code: def __init__(
      self,
      data: Buffer,
      dtype: DtypeObj,
      mask: Optional[Buffer] = None,
      size: Optional[int] = None,  # TODO: make this non-optional
      offset: int = 0,
      null_count: Optional[int] = None,
  ):
      dtype = cudf.dtype(dtype)
  
      if data.size % dtype.itemsize:
          raise ValueError(
              "Buffer size must be divisible by element size"
          )
      if size is None:
          size = (data.size // dtype.itemsize) - offset
      self._nan_count = None
      super().__init__(
          data,
          size=size,
          dtype=dtype,
          mask=mask,
          offset=offset,
          null_count=null_count,
      )
  
imports: from __future__ import annotations
  from typing import Any, Callable, Mapping, Optional, Sequence, Tuple, Union, cast
  import cupy
  import numpy
  import pandas
  from typing_extensions import Self
  import cudf
  from cudf import _lib
  from cudf._lib.types import size_type_dtype
  from cudf._typing import ColumnBinaryOperand, ColumnLike, Dtype, DtypeObj, ScalarLike
  from cudf.api.types import is_bool_dtype, is_float_dtype, is_integer, is_integer_dtype, is_scalar
  from cudf.core.buffer import Buffer, cuda_array_interface_wrapper
  from cudf.core.column import ColumnBase, as_column, build_column, column, full, string
  from cudf.core.dtypes import CategoricalDtype
  from cudf.core.mixins import BinaryOperand
  from cudf.utils.dtypes import NUMERIC_TYPES, min_column_type, min_signed_type, np_dtypes_to_pandas_dtypes, numeric_normalize_types
  from .numerical_base import NumericalBaseColumn
label_desc: Use image node_id 1 to create a new NumericalColumn object from inherited base classes: NumericalBaseColumn with example: obj = NumericalColumn(data, dtype, mask, size, offset, null_count)