This has recently been a major point point for Matplotlib for the
implementation of string-categoricals as well.
Having numpy go to object or fail on `np.asarray([1, 2, 'foo'])` would make
things much easier for us.
Tom
On Fri, Feb 9, 2018 at 2:22 AM Stephan Hoyer wrote:
> On Thu, Feb 8, 2018
On Thu, Feb 8, 2018 at 11:00 PM Eric Wieser
wrote:
> Presumably you would extend that to all (str, np.number), or even (str,
> np.generic_)?
>
Yes, I'm currently doing (np.character, np.number) and (np.character,
np.bool_). But only in direct consultation with the diagram of NumPy's type
hierarch
Presumably you would extend that to all (str, np.number), or even (str,
np.generic_)?
I suppose there’s the argument that with python-3-only support around the
corner, even (str, bytes) should go to object.
Right now, promote_types gives examples in the docs of int/string
conversions, so changing
This is one of my oldest NumPy pain-points:
>>> np.array([1, 2, 'three'])
array(['1', '2', 'three'],
dtype='https://github.com/pydata/xarray/pull/1847), but mostly just
hides bugs until later. It's certainly very un-Pythonic.
The sane promotion rule would be `np.promote_types(str, float) ->
