Hi!
I did put the "string" and now I get the following
error:
File
"C:\Python24\Lib\site-packages\tables\description.py",
line 169, in from_
type
newatom = atom.Atom.from_type(type, shape, dflt)
File "C:\Python24\lib\site-packages\tables\atom.py",
line 451, in from_type
return class_
A Tuesday 11 March 2008, dragan savic escrigué:
> Hi!
>
> I am trying to build a table with a first column
> having a string type. I get the following error:
>
> File
> "C:\Python24\Lib\site-packages\tables\description.py",
> line 169, in from_
> type newatom = atom.Atom.from_type(type, shape, df
A Tuesday 11 March 2008, Charles R Harris escrigué:
> On Tue, Mar 11, 2008 at 4:00 AM, Francesc Altet <[EMAIL PROTECTED]>
wrote:
> > A Tuesday 11 March 2008, Francesc Altet escrigué:
> > > The thing that makes uint64 so special is that it is the largest
> > > integer (in current processors) that h
Hi!
I am trying to build a table with a first column
having a string type. I get the following error:
File
"C:\Python24\Lib\site-packages\tables\description.py",
line 169, in from_
type newatom = atom.Atom.from_type(type, shape, dflt)
File "C:\Python24\Lib\site-packages\tables\atom.py",
line 44
A Tuesday 11 March 2008, Francesc Altet escrigué:
> The thing that makes uint64 so special is that it is the largest
> integer (in current processors) that has a native representation
> (i.e. the processor can operate directly on them, so they can be
> processed very fast), and besides, there is no
Hi Marteen,
A Monday 10 March 2008, escriguéreu:
> > Solution 1) is appealing because is how NumPy works, but I don't
> > personally like the upcasting to float64. First of all, because
> > you transparently convert numbers potentially loosing the least
> > significant
> > digits. Second, becaus
