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pandas.arrays.IntegerArray
class pandas.arrays.IntegerArray(values, mask, copy=False)
[source]-
Array of integer (optional missing) values.
New in version 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
pandas.array()
with one of the integer dtypes (see examples).See Nullable integer data type 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
andmask
.
Returns: - IntegerArray
Examples
Create an IntegerArray with
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
Attributes
None Methods
None
© 2008–2012, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.25.0/reference/api/pandas.arrays.IntegerArray.html