I am trying to convert a list that contains numeric values and None values to numpy.array, such that None is replaces with numpy.nan.
For example:
my_list = [3,5,6,None,6,None]
# My desired result: 
my_array = numpy.array([3,5,6,np.nan,6,np.nan]) 
Naive approach fails:
>>> my_list
[3, 5, 6, None, 6, None]
>>> np.array(my_list)
array([3, 5, 6, None, 6, None], dtype=object) # very limited 
>>> _ * 2
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: unsupported operand type(s) for *: 'NoneType' and 'int'
>>> my_array # normal array can handle these operations
array([  3.,   5.,   6.,  nan,   6.,  nan])
>>> my_array * 2
array([  6.,  10.,  12.,  nan,  12.,  nan])
What is the best way to solve this problem?
 
     
    