[Numpy-discussion] Numpy Array of dtype=object with strings and floats question

Darryl Wallace darryl.wallace@prosensus...
Tue Nov 10 12:09:30 CST 2009


Hello again,

The best way so far that's come to my attention is to use:

numpy.ma.masked_object

The problem with this is that it's looking for a specific instance of an
object.  So if the user had some elements of their array that were, for
example, "randomString" , then it would not be picked up

e.g.
---
from numpy import *

mixedArray=array([1,2, '', 3, 4, 'randomString'], dtype=object)

mixedArrayMask = ma.masked_object(mixedArray, 'randomString').mask
---

then mixedArrayMask will yield:

array([ False, False, False, False, False, True])

Can anyone help me so that all strings are found in the array without having
to explicitly loop through them in Python?

Thanks,
Darryl


On Fri, Nov 6, 2009 at 3:56 PM, Darryl Wallace
<darryl.wallace@prosensus.ca>wrote:

> What I'm doing is importing some data from excel and sometimes there are
> strings in the worksheet.  Often times a user will use an empty cell or a
> string to represent data that is missing.
>
> e.g.
> from numpy import *
> mixedArray=array([1, 2, '', 3, 4, 'String'], dtype=object)
>
> Two questions:
> 1) Is there a quick way to find the elements in the array that are the
> strings without iterating over each element in the array?
>
> or
>
> 2) Could I quickly turn it into a masked array of type float where all
> string elements are set as missing points?
>
> I've been struggling with this for a while and can't come across a method
> that will all me to do it without iterating over each element.
>
> Any help or pointers in the right direction would be greatly appreciated.
>
> Thanks,
> Darryl
>



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