In [1]:

    

import numpy as np


    

In [2]:

    

a = np.array([0, 0, 0, 1])
a


    

    
Out[2]:





array([0, 0, 0, 1])

In [3]:

    

a.sum()


    

    
Out[3]:





1

In [4]:

    

a.mean()


    

    
Out[4]:





0.25

In [5]:

    

b = np.array([0, 0, np.nan, 1])
b


    

    
Out[5]:





array([  0.,   0.,  nan,   1.])

In [6]:

    

b.sum()


    

    
Out[6]:





nan

In [7]:

    

b.mean()


    

    
Out[7]:





nan

In [8]:

    

def sum_(x):
    return sum(y for y in x if not np.isnan(y))


    

In [9]:

    

sum_(a)


    

    
Out[9]:





1

In [10]:

    

sum_(b)


    

    
Out[10]:





1.0

In [11]:

    

def mean_(x):
    return np.array(list(y for y in x if not np.isnan(y))).mean()


    

In [12]:

    

mean_(a)


    

    
Out[12]:





0.25

In [13]:

    

mean_(b)


    

    
Out[13]:





0.33333333333333331

In [14]:

    

1. + np.nan


    

    
Out[14]:





nan

In [15]:

    

1. + 2. + 3.


    

    
Out[15]:





6.0

In [16]:

    

1. is np.nan


    

    
Out[16]:





False

In [17]:

    

np.nan is np.nan


    

    
Out[17]:





True

In [18]:

    

b[2]


    

    
Out[18]:





nan

In [19]:

    

b[2] is np.nan


    

    
Out[19]:





False

In [20]:

    

nan


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-20-8496edc65712> in <module>()
----> 1 nan

NameError: name 'nan' is not defined

In [21]:

    

np.isnan(1.)


    

    
Out[21]:





False

In [22]:

    

np.isnan(np.nan)


    

    
Out[22]:





True

In [23]:

    

np.isnan(b[2])


    

    
Out[23]:





True

In [24]:

    

np.isnotnan(1.)


    

    




---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-24-96c92b9076a4> in <module>()
----> 1 np.isnotnan(1.)

AttributeError: module 'numpy' has no attribute 'isnotnan'

In [25]:

    

c = np.array([0, 0, None, 1])
c


    

    
Out[25]:





array([0, 0, None, 1], dtype=object)

In [26]:

    

c.sum()


    

    




---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-26-009f6e31c6cb> in <module>()
----> 1 c.sum()

/home/jep/anaconda3/envs/jupy/lib/python3.6/site-packages/numpy/core/_methods.py in _sum(a, axis, dtype, out, keepdims)
     30 
     31 def _sum(a, axis=None, dtype=None, out=None, keepdims=False):
---> 32     return umr_sum(a, axis, dtype, out, keepdims)
     33 
     34 def _prod(a, axis=None, dtype=None, out=None, keepdims=False):

TypeError: unsupported operand type(s) for +: 'int' and 'NoneType'

In [27]:

    

c.mean()


    

    




---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-27-5a30177bb035> in <module>()
----> 1 c.mean()

/home/jep/anaconda3/envs/jupy/lib/python3.6/site-packages/numpy/core/_methods.py in _mean(a, axis, dtype, out, keepdims)
     68             is_float16_result = True
     69 
---> 70     ret = umr_sum(arr, axis, dtype, out, keepdims)
     71     if isinstance(ret, mu.ndarray):
     72         ret = um.true_divide(

TypeError: unsupported operand type(s) for +: 'int' and 'NoneType'

In [28]:

    

d = np.array([0, 0, np.nan, 'np.nan', 1])
d


    

    
Out[28]:





array(['0', '0', 'nan', 'np.nan', '1'], 
      dtype='<U32')

In [29]:

    

for x in d:
    try:
        is_nan = np.isnan(x)
    except TypeError:
        is_nan = 'mu'
    print(type(x), is_nan, x)


    

    




<class 'numpy.str_'> mu 0
<class 'numpy.str_'> mu 0
<class 'numpy.str_'> mu nan
<class 'numpy.str_'> mu np.nan
<class 'numpy.str_'> mu 1

In [30]:

    

d = np.array([0, 0, np.nan, 1])
d


    

    
Out[30]:





array([  0.,   0.,  nan,   1.])

In [31]:

    

for x in d:
    try:
        is_nan = np.isnan(x)
    except TypeError:
        is_nan = 'mu'
    print(type(x), is_nan, x)


    

    




<class 'numpy.float64'> False 0.0
<class 'numpy.float64'> False 0.0
<class 'numpy.float64'> True nan
<class 'numpy.float64'> False 1.0