[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 dalloliogm):

 Replying to [comment:1 mwiebe]:
 > I think Python list comprehensions offer a better syntax then an
 'ignore_None' flag would provide. See:
 >
 > {{{
 > In [44]: a = [1, None, 2, None]
 >
 > In [45]: [x for x in a if x != None]
 > Out[45]: [1, 2]
 >
 > In [46]: numpy.average([x for x in a if x != None])
 > Out[46]: 1.5
 > }}}
 >
 > Closing as wontfix.

 Try explaining this to a newbie who does not know what list comprehensions
 are.

 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.

-- 
Ticket URL: <http://projects.scipy.org/numpy/ticket/1180#comment:2>
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