Coverage for /var/srv/projects/api.amasfac.comuna18.com/tmp/venv/lib/python3.9/site-packages/pandas/core/arrays/floating.py: 93%
34 statements
« prev ^ index » next coverage.py v6.4.4, created at 2023-07-17 14:22 -0600
1from __future__ import annotations
3import numpy as np
5from pandas.core.dtypes.common import is_float_dtype
6from pandas.core.dtypes.dtypes import register_extension_dtype
8from pandas.core.arrays.numeric import (
9 NumericArray,
10 NumericDtype,
11)
14class FloatingDtype(NumericDtype):
15 """
16 An ExtensionDtype to hold a single size of floating dtype.
18 These specific implementations are subclasses of the non-public
19 FloatingDtype. For example we have Float32Dtype to represent float32.
21 The attributes name & type are set when these subclasses are created.
22 """
24 _default_np_dtype = np.dtype(np.float64)
25 _checker = is_float_dtype
27 @classmethod
28 def construct_array_type(cls) -> type[FloatingArray]:
29 """
30 Return the array type associated with this dtype.
32 Returns
33 -------
34 type
35 """
36 return FloatingArray
38 @classmethod
39 def _str_to_dtype_mapping(cls):
40 return FLOAT_STR_TO_DTYPE
42 @classmethod
43 def _safe_cast(cls, values: np.ndarray, dtype: np.dtype, copy: bool) -> np.ndarray:
44 """
45 Safely cast the values to the given dtype.
47 "safe" in this context means the casting is lossless.
48 """
49 # This is really only here for compatibility with IntegerDtype
50 # Here for compat with IntegerDtype
51 return values.astype(dtype, copy=copy)
54class FloatingArray(NumericArray):
55 """
56 Array of floating (optional missing) values.
58 .. versionadded:: 1.2.0
60 .. warning::
62 FloatingArray is currently experimental, and its API or internal
63 implementation may change without warning. Especially the behaviour
64 regarding NaN (distinct from NA missing values) is subject to change.
66 We represent a FloatingArray with 2 numpy arrays:
68 - data: contains a numpy float array of the appropriate dtype
69 - mask: a boolean array holding a mask on the data, True is missing
71 To construct an FloatingArray from generic array-like input, use
72 :func:`pandas.array` with one of the float dtypes (see examples).
74 See :ref:`integer_na` for more.
76 Parameters
77 ----------
78 values : numpy.ndarray
79 A 1-d float-dtype array.
80 mask : numpy.ndarray
81 A 1-d boolean-dtype array indicating missing values.
82 copy : bool, default False
83 Whether to copy the `values` and `mask`.
85 Attributes
86 ----------
87 None
89 Methods
90 -------
91 None
93 Returns
94 -------
95 FloatingArray
97 Examples
98 --------
99 Create an FloatingArray with :func:`pandas.array`:
101 >>> pd.array([0.1, None, 0.3], dtype=pd.Float32Dtype())
102 <FloatingArray>
103 [0.1, <NA>, 0.3]
104 Length: 3, dtype: Float32
106 String aliases for the dtypes are also available. They are capitalized.
108 >>> pd.array([0.1, None, 0.3], dtype="Float32")
109 <FloatingArray>
110 [0.1, <NA>, 0.3]
111 Length: 3, dtype: Float32
112 """
114 _dtype_cls = FloatingDtype
116 # The value used to fill '_data' to avoid upcasting
117 _internal_fill_value = np.nan
118 # Fill values used for any/all
119 _truthy_value = 1.0
120 _falsey_value = 0.0
123_dtype_docstring = """
124An ExtensionDtype for {dtype} data.
126This dtype uses ``pd.NA`` as missing value indicator.
128Attributes
129----------
130None
132Methods
133-------
134None
135"""
137# create the Dtype
140@register_extension_dtype
141class Float32Dtype(FloatingDtype):
142 type = np.float32
143 name = "Float32"
144 __doc__ = _dtype_docstring.format(dtype="float32")
147@register_extension_dtype
148class Float64Dtype(FloatingDtype):
149 type = np.float64
150 name = "Float64"
151 __doc__ = _dtype_docstring.format(dtype="float64")
154FLOAT_STR_TO_DTYPE = {
155 "float32": Float32Dtype(),
156 "float64": Float64Dtype(),
157}