pandas.arrays.IntegerArray#

class pandas.arrays.IntegerArray(values, mask, copy=False)[source]#

Array of integer (optional missing) values.

Changed in version 1.0.0: Now uses pandas.NA as the missing value rather than numpy.nan.

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 pandas.array() with one of the integer dtypes (see examples).

See Nullable integer data type for more.

Parameters
valuesnumpy.ndarray

A 1-d integer-dtype array.

masknumpy.ndarray

A 1-d boolean-dtype array indicating missing values.

copybool, default False

Whether to copy the values and mask.

Returns
IntegerArray

Examples

Create an IntegerArray with 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

Attributes

None

Methods

None