Python数组中将零值转换为nan值

Question

I have an array with some zero values that i wish to convert in nan values. When i apply the code
all values become nan

myarray
array([[ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       ..., 
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.]])

myarray.shape
(64L, 52L)
myarray.max()
4563.666015625
myarray.min()
0.0

i wish to convert zero values in nan. I use an example from stackoverflow

a = np.arange(3.0)
a
array([ 0.,  1.,  2.])
a[a==0] = np.nan
a
array([ nan,   1.,   2.])

when i apply the example to my array all values became nan

myarray[myarray == 0.] = nan
myarray
array([[ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       ..., 
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan]])

myarray.max()
nan
myarray.min()
nan

Answer 1

It's not that all the values become nan , it's that (1) you're only looking at the parts that do, and (2) min and max don't work well with nan s.

For example, if we make an array resembling yours:

>>> myarray = np.zeros((64, 52))
>>> myarray[3:-3,3:-3] = np.random.uniform(0, 5000, (64-6,52-6))
>>> myarray
array([[ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       ..., 
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.],
       [ 0.,  0.,  0., ...,  0.,  0.,  0.]])
>>> myarray[myarray==0] = np.nan
>>> myarray
array([[ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       ..., 
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan],
       [ nan,  nan,  nan, ...,  nan,  nan,  nan]])

It may look like it's all nan , but it's not:

>>> myarray[2:5, 2:5]
array([[           nan,            nan,            nan],
       [           nan,  1500.05326562,  4583.70521213],
       [           nan,  4896.62420284,   892.83210033]])

You can also use nanmin and nanmax , which ignore nan s:

>>> myarray.min()
nan
>>> myarray.max()
nan
>>> np.nanmin(myarray)
0.60474162939361253
>>> np.nanmax(myarray)
4996.8967777356092