[Numpy-discussion] number datetime64 dtypes

Hi, Thank you for your time. A colleague asked me about creating a range of numpy datetime64 at 15-day increments. This works: np.arange(np.datetime64('2008-04-01'), np.datetime64('2020-09-01'), np.timedelta64(15, 'D')) but then they also showed me this, which leads to some very strange respon

Re: [Numpy-discussion] number datetime64 dtypes

It's interesting to confirm that people are aware of this syntax! This is intended but perhaps not useful behavior. `datetime64[15D]` is a type that stores dates by the nearest date that is a multiple of 15 days from the unix epoch. Arguably there isn't a situation where using `15D` makes a whole

Re: [Numpy-discussion] number datetime64 dtypes

Hi Eric, Thank you so much for your answer! That explains this interesting behavior: >>> [np.datetime64('2008-04-01', f'{x}D') for x in range(1, 16)] [numpy.datetime64('2008-04-01'), numpy.datetime64('2008-04-01','2D'), numpy.datetime64('2008-03-30','3D'), numpy.datetime64('2008-03-30','4D')

[Numpy-discussion] NumPy 1.19.2 released

Hi All, On behalf of the NumPy team I am pleased to announce that NumPy 1.19.2 has been released. This release fixes several bugs, prepares for the upcoming Cython 3.x release. and pins setuptools to keep distutils working while upstream modifications are ongoing. The aarch64 wheels are built with

[Numpy-discussion] Numpy wheels with Python 3.9 support.

Hi All, There are numpy pre-wheels for Python 3.9 available on the x86_64, i686, and aarch64 platforms. They use manylinux2010 and manylinux2014, so you need a recent pip to get them. Chuck ___ NumPy-Discussion mailing list NumPy-Discussion@python.org