3 ms·

I wonder what they plan to use it for. Numpy kind of seems finished already.

• cing 9y ago
  There are about 200 open "Numpy Enhancement Proposal" issues on Github, https://github.com/numpy/numpy/labels/01%20-%20Enhancement https://github.com/numpy/numpy/labels/01%20-%20Enhancement
• ris 9y ago
  That's not to say there aren't things NumPy doesn't do that it could. How about lazy evaluation or even just matrix chain multiplication? Either could save a lot of computation.
  • VHRanger 9y ago
    Dynamic arrays anyone?
  • shoyer 9y ago
    Matrix chain multiplication was added to NumPy recently, see numpy.linalg.multi_dot: https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.linalg.multi_dot.html https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/...
    • ris 9y ago
      Hooray! Still, it's not exactly transparent in a way that you could get with lazy array evaluation.
• cdavid 9y ago
  Many things could be improved in NumPy: * make it easier to implement and deploy custom dtypes, fix the time-related dtype * support for ragged arrays * consolidate internals, especially around ufuncs I also think some non trivial part of pandas lowest levels belong to NumPy, though I have not thought very deeply about that one: support for missing value, some kind of indexing, etc...
  • travisoliphant 9y ago
    Yes, I agree. I would love to see parts of what is in Pandas actually supported better in NumPy.