[Numpy-discussion] nan result from np.linalg.lstsq()

[Larry Paltrow]

Ok thanks, I figured np.isnan(data) is True is what we want but wasn't
certain. I think it should describe the same thing.

np.all(~np.isnan(data))
>>> False

Seems to be all non-nan

On Mon, Oct 29, 2012 at 2:12 AM, eat <e.antero.tammi at gmail.com> wrote:

> Hi,
>
> On Mon, Oct 29, 2012 at 11:01 AM, Larry Paltrow <larry.paltrow at gmail.com>wrote:
>
>> np.isnan(data) is True
>> >>> False
>>
> Check with:
> np.all(~np.isnan(x))
>
> My 2 cents,
> -eat
>
>>
>>
>> On Mon, Oct 29, 2012 at 1:50 AM, Pauli Virtanen <pav at iki.fi> wrote:
>>
>>> Larry Paltrow <larry.paltrow <at> gmail.com> writes:
>>> > I'm having some trouble using the linalg.lstsq() function
>>> > with certain data and trying to understand why. It's
>>> > always returning nans when I feed it this numpy array of float64 data:
>>> >
>>> > data = df.close.values #coming from a pandas dataframe
>>> >
>>> > type(data)
>>> > >>> numpy.ndarray
>>>
>>> Maybe you have NaNs in the array? (i.e. np.isnan(data) is True)
>>>
>>> --
>>> Pauli Virtanen
>>>
>>>
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