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

[Travis Oliphant]

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.        ])

-Travis