pandas.arrays.FloatingArray#
- class pandas.arrays.FloatingArray(values, mask, copy=False)[source]#
Array of floating (optional missing) values.
New in version 1.2.0.
Warning
FloatingArray is currently experimental, and its API or internal implementation may change without warning. Especially the behaviour regarding NaN (distinct from NA missing values) is subject to change.
We represent a FloatingArray with 2 numpy arrays:
data: contains a numpy float array of the appropriate dtype
mask: a boolean array holding a mask on the data, True is missing
To construct an FloatingArray from generic array-like input, use
pandas.array()
with one of the float dtypes (see examples).See Nullable integer data type for more.
- Parameters
- valuesnumpy.ndarray
A 1-d float-dtype array.
- masknumpy.ndarray
A 1-d boolean-dtype array indicating missing values.
- copybool, default False
Whether to copy the values and mask.
- Returns
- FloatingArray
Examples
Create an FloatingArray with
pandas.array()
:>>> pd.array([0.1, None, 0.3], dtype=pd.Float32Dtype()) <FloatingArray> [0.1, <NA>, 0.3] Length: 3, dtype: Float32
String aliases for the dtypes are also available. They are capitalized.
>>> pd.array([0.1, None, 0.3], dtype="Float32") <FloatingArray> [0.1, <NA>, 0.3] Length: 3, dtype: Float32
Attributes
None
Methods
None