A Tuesday 30 December 2008, Francesc Alted escrigué:
> A Monday 29 December 2008, Jean-Baptiste Rudant escrigué:
[snip]
>
> The difference for both approaches is that the row-wise arrangement
> is more efficient when data is iterated by field, while the
> column-wise one is more efficient when data
A Monday 29 December 2008, Jean-Baptiste Rudant escrigué:
> Hello,
>
> I like to use record arrays to access fields by their name, and
> because they are esay to use with pytables. But I think it's not very
> effiicient for what I have to do. Maybe I'm misunderstanding
> something.
>
> Example :
>
Jean-Baptiste,
As you stated, everything depends on what you want to do.
If you need to keep the correspondence age<>weight for each entry,
then yes, record arrays, or at least flexible-type arrays, are the
best. (The difference between a recarray and a flexible-type array is
that fields can
Jean-Baptiste Rudant wrote:
> Hello,
>
> I like to use record arrays to access fields by their name, and because
> they are esay to use with pytables. But I think it's not very effiicient
> for what I have to do. Maybe I'm misunderstanding something.
>
> Example :
>
> import numpy as np
> age =
Jean-Baptiste Rudant wrote:
Hello,
I like to use record arrays to access fields by their name, and
because they are esay to use with pytables. But I think it's not very
effiicient for what I have to do. Maybe I'm misunderstanding something.
Example :
import numpy as np
age = np.random.ran
Hello,
I like to use record arrays to access fields by their name, and because they
are esay to use with pytables. But I think it's not very effiicient for what I
have to do. Maybe I'm misunderstanding something.
Example :
import numpy as np
age = np.random.randint(0, 99, 10e6)
weight = np.ra
