class_docstr: Array of integer (optional missing) values.
  
  .. versionadded:: 0.24.0
  
  .. warning::
  
     IntegerArray is currently experimental, and its API or internal
     implementation may change without warning.
  
  We represent an IntegerArray with 2 numpy arrays:
  
  - data: contains a numpy integer array of the appropriate dtype
  - mask: a boolean array holding a mask on the data, True is missing
  
  To construct an IntegerArray from generic array-like input, use
  :func:`pandas.array` with one of the integer dtypes (see examples).
  
  See :ref:`integer_na` for more.
  
  Parameters
  ----------
  values : numpy.ndarray
      A 1-d integer-dtype array.
  mask : numpy.ndarray
      A 1-d boolean-dtype array indicating missing values.
  copy : bool, default False
      Whether to copy the `values` and `mask`.
  
  Returns
  -------
  IntegerArray
  
  Examples
  --------
  Create an IntegerArray with :func:`pandas.array`.
  
  >>> int_array = pd.array([1, None, 3], dtype=pd.Int32Dtype())
  >>> int_array
  <IntegerArray>
  [1, NaN, 3]
  Length: 3, dtype: Int32
  
  String aliases for the dtypes are also available. They are capitalized.
  
  >>> pd.array([1, None, 3], dtype='Int32')
  <IntegerArray>
  [1, NaN, 3]
  Length: 3, dtype: Int32
  
  >>> pd.array([1, None, 3], dtype='UInt16')
  <IntegerArray>
  [1, NaN, 3]
  Length: 3, dtype: UInt16
docstr: Internal pandas method for lossy conversion to a NumPy ndarray.
  
  This method is not part of the pandas interface.
  
  The expectation is that this is cheap to compute, and is primarily
  used for interacting with our indexers.
docstr_tok: ["Internal","pandas","method","for","lossy","conversion","to","a","NumPy","ndarray",".","This","method","is","not","part","of","the","pandas","interface",".","The","expectation","is","that","this","is","cheap","to","compute",",","and","is","primarily","used","for","interacting","with","our","indexers","."]
code: def _ndarray_values(self):
      # type: () -> np.ndarray
      """Internal pandas method for lossy conversion to a NumPy ndarray.
  
      This method is not part of the pandas interface.
  
      The expectation is that this is cheap to compute, and is primarily
      used for interacting with our indexers.
      """
      return self._data
  
imports: import copy
  import sys
  import warnings
  import numpy
  from pandas._libs import lib
  from pandas.compat import range, set_function_name, string_types
  from pandas.util._decorators import cache_readonly
  from pandas.core.dtypes.base import ExtensionDtype
  from pandas.core.dtypes.cast import astype_nansafe
  from pandas.core.dtypes.common import is_bool_dtype, is_float, is_float_dtype, is_integer, is_integer_dtype, is_list_like, is_object_dtype, is_scalar
  from pandas.core.dtypes.dtypes import register_extension_dtype
  from pandas.core.dtypes.generic import ABCIndexClass, ABCSeries
  from pandas.core.dtypes.missing import isna, notna
  from pandas.core import nanops
  from pandas.core.arrays import ExtensionArray, ExtensionOpsMixin
  from pandas.core.tools.numeric import to_numeric
label_desc: Use image node_id 20 for calling the IntegerArray obj's underlying member method code with example usage: obj._ndarray_values() and returns: self