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=========================
NumPy 2.0.0 Release Notes
=========================
[Possibly 1.7.0 release notes, as ABI compatibility is still being maintained]
Highlights
==========
New features
============
Mask-based NA missing values
----------------------------
Support for NA missing values similar to those in R has been implemented.
This was done by adding optional NA masks to the core array object.
While a significant amount of the NumPy functionality has been extended to
support NA masks, not everything is yet supported. Here is a list of things
that do and do not work with NA values:
What works with NA:
* Basic indexing and slicing, as well as full boolean mask indexing.
* All element-wise ufuncs.
* UFunc.reduce methods, with a new skipna parameter.
* Array methods:
+ ndarray.clip, ndarray.min, ndarray.max, ndarray.sum, ndarray.prod,
ndarray.conjugate, ndarray.diagonal
+ numpy.concatenate
What doesn't work with NA:
* Fancy indexing, such as with lists and partial boolean masks.
* ndarray.flat and any other methods that use the old iterator
mechanism instead of the newer nditer.
* UFunc.reduce of multi-dimensional arrays, with skipna=True and a ufunc
that doesn't have an identity.
* UFunc.accumulate, UFunc.reduceat.
* np.logical_and, np.logical_or, np.all, and np.any don't satisfy the
rules NA | True == True and NA & False == False yet.
* Array methods:
+ ndarray.argmax, ndarray.argmin,
Custom formatter for printing arrays
------------------------------------
Changes
=======
The default casting rule for UFunc out= parameters has been changed from
'unsafe' to 'same_kind'. Most usages which violate the 'same_kind'
rule are likely bugs, so this change may expose previously undetected
errors in projects that depend on NumPy.
The functions np.diag, np.diagonal, and <ndarray>.diagonal now return a
view into the original array instead of making a copy. This makes these
functions more consistent with NumPy's general approach of taking views
where possible, and performs much faster as well.
Deprecations
============
Specifying a custom string formatter with a `_format` array attribute is
deprecated. The new `formatter` keyword in ``numpy.set_printoptions`` or
``numpy.array2string`` can be used instead.
|
