On 01/26/2018 06:01 PM, josef.p...@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
code....
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
pandas either.)
Allan
Josef
<all code needs to be rewritten every 5 to 10 years.>
-CHB
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