[SciPy-user] scipy.io.read_array: NaN in data file

[Dharhas Pothina]

so does np.genfromtxtx also deal with missing values in a file?

i.e something like:
1999,1,22,42
1999,2,18,23
1999,3,,22
1999,4,12,
1999,5,,,
1999,6,12,34

I've worked out how to do this using np.loadtxt by defining conversions for each column buts its pretty cumbersome and looks like spagetti in the code.
 
- dharhas

>>> Pierre GM <pgmdevlist at gmail.com> 3/10/2009 11:14 AM >>>
With the SVN version of Numpy:

 >>> import numpy as np
 >>> import StringIO

 >>> a = np.genfromtxtx(StringIO.StringIO("1, NaN"), delimiter=",")

If you want to output a MaskedArray:
 >>> a = np.genfromtxt(StringIO.StringIO("1, NaN"), delimiter=",",
                       missing="NaN", usemask=True)
 >>> isinstance(a, np.ma.MaskedArray)
True

On Mar 10, 2009, at 11:57 AM, Erik Granstedt wrote:

> Hello,
>
> I am using scipy.io.read_array to read in values from data files to
> arrays.  The data files occasionally contain "NaN"s, and I would like
> the returned array to also contain "NaN"s.  I've tried calling
> read_array with:
>
> scipy
> .io.read_array(file('read_array_test.dat','r'),missing=float('NaN'))
>
> but this still seems to convert the "NaN"s to 0.0
>
> Is there a way to get it to return "NaN"s in the array instead of
> converting them to 0.0 ?
>
> Thanks,
>
> -Erik
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org 
> http://mail.scipy.org/mailman/listinfo/scipy-user 

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