[Numpy-discussion] Re: Efficient way to handle None->nan?

[Russell E. O. <ro...@ce...>]

In article <43D...@ee...>,
 Travis Oliphant <oli...@ee...> wrote:

> Russell E. Owen wrote:
> 
> >We're getting numeric data from a (MySQL) database. We'd like to use 
> >numarray or NumPy on the resulting data, but some values may be None. Is 
> >there a fast, efficient way to replace None with NaN? I'd hate to use a 
> >list comprehension on each data tuple before turning it into an array, 
> >but I haven't thought of anything else.
> >  
> >
> 
> Current numpy SVN allows
> 
> array([1.0,None,2.0],dtype=float)
> array([ 1.        ,         nan,  2.        ])

That's great! Thanks!!

-- Russell