pandas.arrays.FloatingArray#

classpandas.arrays.FloatingArray(values,mask,copy=False)[source]#

Array of floating (optional missing) values.

Warning

FloatingArray is currently experimental, and its API or internalimplementation may change without warning. Especially the behaviourregarding 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, usepandas.array() with one of the float dtypes (see examples).

SeeNullable 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 thevalues andmask.

Attributes

None

Methods

None

Returns:

FloatingArray

Examples

Create an FloatingArray withpandas.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