On Thu, May 27, 2010 at 10:25 AM, Bruce Southey <bsout...@gmail.com> wrote:
> On 05/27/2010 10:40 AM, Vincent Davis wrote:
> Can you give an example of what you are trying to do?
>
arr = np.array([(1,'a'),(2,'b')], dtype =[(num,int),(str, |s2)]
No supposed I want to know if I can sum the values in 'num'. I could just
try and then handle the exemption, but I would like to do something more
like
for col in arr.dtypes.names:
if arr[col] "is a number":
sum(arr[col])
I think i can use Roberts suggestion, I was not aware of np.number, I guess
I need to look into the hierarchy more.
The dtypes have a hierarchy.
>
> In [2]: np.issubdtype(float, np.number)
> Out[2]: True
>
> In [3]: np.issubdtype(str, np.number)
> Out[3]: False
>
> --
> Robert Kern
Thanks
Vincent
>
>
> If some of your string arrays only have string representations of numbers
> that you want to do the math on then you have to attempt to convert those
> arrays into a numeric dtype (probably float) using for example asarray().
>
> Bruce
>
> >>> import numpy as np
> >>> a=np.array([1,2,3])
> >>> c=np.array(['1','2','3'])
> >>> d=np.array(['a','b','1'])
> >>> np.asarray(a, dtype=float)
> array([ 1., 2., 3.])
> >>> np.asarray(c,dtype=float)
> array([ 1., 2., 3.])
> >>> np.asarray(d,dtype=float)
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File "/usr/lib64/python2.6/site-packages/numpy/core/numeric.py", line
> 284, in asarray
> return array(a, dtype, copy=False, order=order)
> ValueError: invalid literal for float(): a
> >>> try:
> ... np.asarray(d,dtype=float)
> ... except:
> ... print 'fail'
> ...
> fail
>
>
>
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>
*Vincent Davis
720-301-3003 *
vinc...@vincentdavis.net
my blog <http://vincentdavis.net> |
LinkedIn<http://www.linkedin.com/in/vincentdavis>
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