[Numpy-discussion] Setting custom dtypes and 1.14
allanhaldane at gmail.com
Sat Jan 27 23:50:58 EST 2018
On 01/26/2018 06:01 PM, josef.pktd at gmail.com wrote:
> I thought recarrays were pretty cool back in the day, but pandas is
> a much better option.
> So I pretty much only use structured arrays for data exchange with C
> My impression is that this turns into a deprecate recarrays and
> supporting recfunction issue.
> recfunctions and the associated function from matplotlib.mlab where
> explicitly designed for using structured dtypes as dataframe_like >
> (old question: does numpy have a sort_rows function now without
> detouring to structured dtype views?)
No, that's still the way to do it.
*should* we have any dataframe-like functionality in numpy?
We get requests every once in a while about how to sort rows, or about
adding a "groupby" function. I myself have used recarrays in a
dataframe-like way, when I wanted a quick multiple-array object that
supported numpy indexing. So there is some demand to have minimal
"dataframe-like" behavior in numpy itself.
recarrays play part of this role currently, though imperfectly due to
padding and cache issues. I think I'm comfortable with supporting some
minor use of structured/recarrays as dataframe-like, with a warning in
docs that the user should really look at pandas/xarray, and that
structured arrays are primarily for data exchange.
(If we want to dream, maybe one day we should make a minimal
multiple-array container class. I imagine it would look pretty similar
to recarray, but stored as a set of arrays instead of a structured
array. But maybe recarrays are good enough, and let's not reimplement
> <all code needs to be rewritten every 5 to 10 years.>
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