In [1]:

    

import numpy as np


    

In [2]:

    

a = np.arange(12).reshape(3, 4)
print(a)


    

    




[[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]]

In [3]:

    

b = np.arange(12).reshape(4, 3).T
print(b)


    

    




[[ 0  3  6  9]
 [ 1  4  7 10]
 [ 2  5  8 11]]

In [4]:

    

a_compare = a < b
print(a_compare)


    

    




[[False  True  True  True]
 [False False  True  True]
 [False False False False]]

In [5]:

    

print(type(a_compare))


    

    




<class 'numpy.ndarray'>

In [6]:

    

print(a_compare.dtype)


    

    




bool

In [7]:

    

print(a > b)


    

    




[[False False False False]
 [ True  True False False]
 [ True  True  True False]]

In [8]:

    

print(a <= b)


    

    




[[ True  True  True  True]
 [False False  True  True]
 [False False False  True]]

In [9]:

    

print(a >= b)


    

    




[[ True False False False]
 [ True  True False False]
 [ True  True  True  True]]

In [10]:

    

print(a == b)


    

    




[[ True False False False]
 [False False False False]
 [False False False  True]]

In [11]:

    

print(a != b)


    

    




[[False  True  True  True]
 [ True  True  True  True]
 [ True  True  True False]]

In [12]:

    

b_float = b.astype(float)
print(b_float)


    

    




[[ 0.  3.  6.  9.]
 [ 1.  4.  7. 10.]
 [ 2.  5.  8. 11.]]

In [13]:

    

print(b_float.dtype)


    

    




float64

In [14]:

    

print(a == b_float)


    

    




[[ True False False False]
 [False False False False]
 [False False False  True]]

In [15]:

    

b_1d = np.arange(4, 8)
print(b_1d)


    

    




[4 5 6 7]

In [16]:

    

print(a < b_1d)


    

    




[[ True  True  True  True]
 [False False False False]
 [False False False False]]

In [17]:

    

print(a < 6)


    

    




[[ True  True  True  True]
 [ True  True False False]
 [False False False False]]

In [18]:

    

print(a % 2)


    

    




[[0 1 0 1]
 [0 1 0 1]
 [0 1 0 1]]

In [19]:

    

print(a % 2 == 0)


    

    




[[ True False  True False]
 [ True False  True False]
 [ True False  True False]]

In [20]:

    

print(np.count_nonzero(a < 6))


    

    




6

In [21]:

    

print(np.all(a < 6))


    

    




False

In [22]:

    

print(np.all(a < 6, axis=1))


    

    




[ True False False]

In [23]:

    

print(np.any(a < 6))


    

    




True

In [24]:

    

print(np.any(a < 6, axis=1))


    

    




[ True  True False]

In [25]:

    

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


    

    




[ 0.  1. nan]

In [26]:

    

print(a_nan == np.nan)


    

    




[False False False]

In [27]:

    

print(np.isnan(a_nan))


    

    




[False False  True]

In [28]:

    

print(a_nan > 0)


    

    




[False  True False]






    




/usr/local/lib/python3.7/site-packages/ipykernel_launcher.py:1: RuntimeWarning: invalid value encountered in greater
  """Entry point for launching an IPython kernel.

In [29]:

    

a_nan_only = np.array([np.nan])
print(a_nan_only)


    

    




[nan]

In [30]:

    

print(a_nan_only > 0)


    

    




[False]

In [31]:

    

print(np.nan > 0)


    

    




False

In [32]:

    

x = 6


    

In [33]:

    

print(4 < x < 8)


    

    




True

In [34]:

    

# print(4 < a < 8)
# ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()


    

In [35]:

    

print((a > 4) & (a < 8))


    

    




[[False False False False]
 [False  True  True  True]
 [False False False False]]

In [36]:

    

# print((a > 4) and (a < 8))
# ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()


    

In [37]:

    

# print(a > 4 & a < 8)
# ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()


    

In [38]:

    

x = 6
y = 6
z = 6


    

In [39]:

    

print(x == y == z)


    

    




True

In [40]:

    

c = np.zeros((3, 4), int)
print(c)


    

    




[[0 0 0 0]
 [0 0 0 0]
 [0 0 0 0]]

In [41]:

    

# print(a == b == c)
# ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()


    

In [42]:

    

print((a == b) & (b == c))


    

    




[[ True False False False]
 [False False False False]
 [False False False False]]