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An ExtensionDtype to hold a single size & kind of integer dtype.
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IntegerDtype. For example, we have Int8Dtype to represent signed int 8s.
The attributes name & type are set when these subclasses are created.
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Return the array type associated with this dtype.
Returns
-------
type
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Array of integer (optional missing) values.
Uses :attr:`pandas.NA` as the missing value.
.. 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`.
Attributes
----------
None
Methods
-------
None
Returns
-------
IntegerArray
Examples
--------
Create an IntegerArray with :func:`pandas.array`.
>>> int_array = pd.array([1, None, 3], dtype=pd.Int32Dtype())
>>> int_array
<IntegerArray>
[1, <NA>, 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, <NA>, 3]
Length: 3, dtype: Int32
>>> pd.array([1, None, 3], dtype='UInt16')
<IntegerArray>
[1, <NA>, 3]
Length: 3, dtype: UInt16
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An ExtensionDtype for {dtype} integer data.
Uses :attr:`pandas.NA` as its missing value, rather than :attr:`numpy.nan`.
Attributes
----------
None
Methods
-------
None
Examples
--------
For Int8Dtype:
>>> ser = pd.Series([2, pd.NA], dtype=pd.Int8Dtype())
>>> ser.dtype
Int8Dtype()
For Int16Dtype:
>>> ser = pd.Series([2, pd.NA], dtype=pd.Int16Dtype())
>>> ser.dtype
Int16Dtype()
For Int32Dtype:
>>> ser = pd.Series([2, pd.NA], dtype=pd.Int32Dtype())
>>> ser.dtype
Int32Dtype()
For Int64Dtype:
>>> ser = pd.Series([2, pd.NA], dtype=pd.Int64Dtype())
>>> ser.dtype
Int64Dtype()
For UInt8Dtype:
>>> ser = pd.Series([2, pd.NA], dtype=pd.UInt8Dtype())
>>> ser.dtype
UInt8Dtype()
For UInt16Dtype:
>>> ser = pd.Series([2, pd.NA], dtype=pd.UInt16Dtype())
>>> ser.dtype
UInt16Dtype()
For UInt32Dtype:
>>> ser = pd.Series([2, pd.NA], dtype=pd.UInt32Dtype())
>>> ser.dtype
UInt32Dtype()
For UInt64Dtype:
>>> ser = pd.Series([2, pd.NA], dtype=pd.UInt64Dtype())
>>> ser.dtype
UInt64Dtype()
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