Ryan Neve wrote:
> Hello,
>
> [...]
> This works, but is very slow for something that will be on the back end
> of a web page.
Iterating in python is usually slow, so you should use numpy array
methods if possible. I've made a faster version. It gives the same
result for your test case, but yo
Hello,
I've got many 1d arrays of data which contain occasional NaNs where there
weren't any samples at that depth bin. Something like this...
array([np.nan,1,2,3,np.nan,5,6,7,8,np.nan,np.nan,11,12,np.nan,np.nan,np.nan])
But much bigger, and I have hundreds of them. Most NaN's are isolated
betwee
