Its pretty easy to implement this table functionality and more on top of
the code I linked above. I still think such a comprehensive overhaul of
arraysetops is worth discussing.
import numpy as np
import grouping
x = [1, 1, 1, 1, 2, 2, 2, 2, 2]
y = [3, 4, 3, 3, 3, 4, 5, 5, 5]
z = np.random.randint
On Wed, Aug 13, 2014 at 5:15 PM, Benjamin Root wrote:
> The ever-wonderful pylab mode in matplotlib has a table function for
> plotting a table of text in a plot. If I remember correctly, what would
> happen is that matplotlib's table() function will simply obliterate the
> numpy's table function
The ever-wonderful pylab mode in matplotlib has a table function for
plotting a table of text in a plot. If I remember correctly, what would
happen is that matplotlib's table() function will simply obliterate the
numpy's table function. This isn't a show-stopper, I just wanted to point
that out.
P
On Tue, Aug 12, 2014 at 12:51 PM, Eelco Hoogendoorn <
hoogendoorn.ee...@gmail.com> wrote:
> ah yes, that's also an issue I was trying to deal with. the semantics I
> prefer in these type of operators, is (as a default), to have every array
> be treated as a sequence of keys, so if calling unique(a
On Wed, Aug 13, 2014 at 12:47 AM, Sturla Molden wrote:
> Robert Kern wrote:
>
BLAS/LAPACK are heavy dependencies that often give problems, which is why
you don't want to require them for the casual user that only needs numpy
arrays to make some plots for examples.
>>>
>>> Maybe we