What is the status of: https://github.com/numpy/numpy/blob/master/doc/neps/missing-data.rst and of missing data in Numpy, more generally? Is np.ma.array still the "state-of-the-art" way to handle missing data? Or has something better and more comprehensive been put together?
On Wed, Mar 26, 2014 at 7:22 PM, T J <tjhnson@gmail.com> wrote:
What is the status of:
https://github.com/numpy/numpy/blob/master/doc/neps/missing-data.rst
For what it's worth this NEP was written in 2011 by mwiebe who made 258 numpy commits in 2011, 1 in 2012, and 3 in 2014. According to github, in the last few hours alone mwiebe has made several commits to 'blaze' and 'dynd-python'. Here's the blog post explaining the vision for Continuum's 'blaze' project http://continuum.io/blog/blaze. Continuum seems to have been started in early 2012.
On Wed, Mar 26, 2014 at 5:43 PM, alex <argriffi@ncsu.edu> wrote:
On Wed, Mar 26, 2014 at 7:22 PM, T J <tjhnson@gmail.com> wrote:
What is the status of:
https://github.com/numpy/numpy/blob/master/doc/neps/missing-data.rst
For what it's worth this NEP was written in 2011 by mwiebe who made 258 numpy commits in 2011, 1 in 2012, and 3 in 2014. According to github, in the last few hours alone mwiebe has made several commits to 'blaze' and 'dynd-python'. Here's the blog post explaining the vision for Continuum's 'blaze' project http://continuum.io/blog/blaze. Continuum seems to have been started in early 2012.
It looks like blaze will have bit pattern missing values ala R. I don't know if there is going to be a masked array implementation. The NA code was taken out of Numpy because it was not possible to reach agreement that it did the right thing. Numpy.ma remains the only solution for bad data at this time. The code could probably use more love than it has gotten ;) Chuck
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alex -
Charles R Harris -
T J