pandas.arrays.IntegerArray — pandas 0.25.3 documentation (original) (raw)
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, usepandas.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 and mask. |
|---|---|
| Returns: | IntegerArray |
Examples
Create an IntegerArray with pandas.array().
int_array = pd.array([1, None, 3], dtype=pd.Int32Dtype()) int_array [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') [1, NaN, 3] Length: 3, dtype: Int32
pd.array([1, None, 3], dtype='UInt16') [1, NaN, 3] Length: 3, dtype: UInt16
Attributes
| None | | | -------- | |
Methods
| None | | | -------- | |