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dd« Z e
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dd« Z y) Ú FloatingDtypea
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An ExtensionDtype to hold a single size of floating dtype.
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These specific implementations are subclasses of the non-public
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FloatingDtype. For example we have Float32Dtype to represent float32.
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The attributes name & type are set when these subclasses are created.
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c ó t S )zq
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Return the array type associated with this dtype.
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Returns
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-------
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type
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Safely cast the values to the given dtype.
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"safe" in this context means the casting is lossless.
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Array of floating (optional missing) values.
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.. warning::
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FloatingArray is currently experimental, and its API or internal
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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
|
:func:`pandas.array` with one of the float dtypes (see examples).
|
|
See :ref:`integer_na` for more.
|
|
Parameters
|
----------
|
values : numpy.ndarray
|
A 1-d float-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`.
|
|
Attributes
|
----------
|
None
|
|
Methods
|
-------
|
None
|
|
Returns
|
-------
|
FloatingArray
|
|
Examples
|
--------
|
Create an FloatingArray with :func:`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
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g ð?g N) r r r! r" r
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Ú
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An ExtensionDtype for {dtype} data.
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|
This dtype uses ``pd.NA`` as missing value indicator.
|
|
Attributes
|
----------
|
None
|
|
Methods
|
-------
|
None
|
|
Examples
|
--------
|
For Float32Dtype:
|
|
>>> ser = pd.Series([2.25, pd.NA], dtype=pd.Float32Dtype())
|
>>> ser.dtype
|
Float32Dtype()
|
|
For Float64Dtype:
|
|
>>> ser = pd.Series([2.25, pd.NA], dtype=pd.Float64Dtype())
|
>>> ser.dtype
|
Float64Dtype()
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