Convert python list with None values to numpy array with nan values

Question

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?

Answer 1

You simply have to explicitly declare the data type:

>>> my_list = [3, 5, 6, None, 6, None] >>> np.array(my_list, dtype=np.float) array([  3.,   5.,   6.,  nan,   6.,  nan]) 

Answer 2

What about

my_array = np.array(map(lambda x: numpy.nan if x==None else x, my_list))