[NumPy-Tickets] [NumPy] #1180: numpy.average: add an option to skip 'None' values from count

[NumPy Trac]

#1180: numpy.average: add an option to skip 'None' values from count
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  Reporter:  dalloliogm   |       Owner:  somebody   
      Type:  enhancement  |      Status:  closed     
  Priority:  normal       |   Milestone:  Unscheduled
 Component:  Other        |     Version:             
Resolution:  wontfix      |    Keywords:             
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Comment(by mwiebe):

 Replying to [comment:2 dalloliogm]:
 > [snip]
 >
 > Try explaining this to a newbie who does not know what list
 comprehensions are.

 This is what I prefer. ;) I've made an initial attempt here:

 https://github.com/numpy/numpy/commit/ac2c160c5b0ad5a420543b94a1896f5e45f67b97

 If you would like to change what I have done or add similar comments to
 other functions, you can use the documentation wiki. Everything you need
 to get started with it is documented here:

 http://docs.scipy.org/numpy/Front%20Page/


 > In any case, consider that almost all the other
 mathematical/statistical/data analysis languages use the method proposed
 above; so, forcing people to use list comprehensions while with all the
 other languages people just use a parameter would be an anomaly.
 >
 > Example of implementation:
 >
 {{{
 >>> numpy.average([1, 2, None], ignore_None=True)
 1.5
 }}}
 >
 > It won't even be so difficult to implement, you can use the list
 comprehension code that you wrote above.

 While this is not difficult to implement, to me this doesn't fit into
 NumPy and Python very well, and nudging users to learn about the powerful
 features of Python that solve this more cleanly is much better.

-- 
Ticket URL: <http://projects.scipy.org/numpy/ticket/1180#comment:3>
NumPy <http://projects.scipy.org/numpy>
My example project