In [4]:

    

import numpy as np

import matplotlib.pyplot as plt
%matplotlib inline


    

In [7]:

    

points = np.arange(-5,5,0.01)


    

In [8]:

    

dx,dy = np.meshgrid(points, points)


    

In [9]:

    

dx


    

    
Out[9]:





array([[-5.  , -4.99, -4.98, ...,  4.97,  4.98,  4.99],
       [-5.  , -4.99, -4.98, ...,  4.97,  4.98,  4.99],
       [-5.  , -4.99, -4.98, ...,  4.97,  4.98,  4.99],
       ..., 
       [-5.  , -4.99, -4.98, ...,  4.97,  4.98,  4.99],
       [-5.  , -4.99, -4.98, ...,  4.97,  4.98,  4.99],
       [-5.  , -4.99, -4.98, ...,  4.97,  4.98,  4.99]])

In [10]:

    

dy


    

    
Out[10]:





array([[-5.  , -5.  , -5.  , ..., -5.  , -5.  , -5.  ],
       [-4.99, -4.99, -4.99, ..., -4.99, -4.99, -4.99],
       [-4.98, -4.98, -4.98, ..., -4.98, -4.98, -4.98],
       ..., 
       [ 4.97,  4.97,  4.97, ...,  4.97,  4.97,  4.97],
       [ 4.98,  4.98,  4.98, ...,  4.98,  4.98,  4.98],
       [ 4.99,  4.99,  4.99, ...,  4.99,  4.99,  4.99]])

In [11]:

    

z = (np.sin(dx) + np.sin(dy))

z


    

    
Out[11]:





array([[  1.91784855e+00,   1.92063718e+00,   1.92332964e+00, ...,
         -8.07710558e-03,  -5.48108704e-03,  -2.78862876e-03],
       [  1.92063718e+00,   1.92342581e+00,   1.92611827e+00, ...,
         -5.28847682e-03,  -2.69245827e-03,  -5.85087534e-14],
       [  1.92332964e+00,   1.92611827e+00,   1.92881072e+00, ...,
         -2.59601854e-03,  -5.63993297e-14,   2.69245827e-03],
       ..., 
       [ -8.07710558e-03,  -5.28847682e-03,  -2.59601854e-03, ...,
         -1.93400276e+00,  -1.93140674e+00,  -1.92871428e+00],
       [ -5.48108704e-03,  -2.69245827e-03,  -5.63993297e-14, ...,
         -1.93140674e+00,  -1.92881072e+00,  -1.92611827e+00],
       [ -2.78862876e-03,  -5.85087534e-14,   2.69245827e-03, ...,
         -1.92871428e+00,  -1.92611827e+00,  -1.92342581e+00]])

In [12]:

    

plt.imshow(z)


    

    
Out[12]:





<matplotlib.image.AxesImage at 0x10d406f50>






    

In [13]:

    

plt.imshow(z)
plt.colorbar()

plt.title('Plot for sin(x) + sin(y)')


    

    
Out[13]:





<matplotlib.text.Text at 0x117767450>






    

In [14]:

    

A = np.array([1,2,3,4])

B = np.array([100,200,300,400])


    

In [15]:

    

condition = np.array([True, True, False, False])


    

In [18]:

    

answer = [(A_val if cond else B_val) for A_val, B_val, cond in zip(A, B, condition)]


    

In [19]:

    

answer


    

    
Out[19]:





[1, 2, 300, 400]

In [20]:

    

answer2 = np.where(condition, A, B)


    

In [21]:

    

answer2


    

    
Out[21]:





array([  1,   2, 300, 400])

In [22]:

    

from numpy.random import randn


    

In [24]:

    

np.where(arr < 0, 0, arr)


    

    
Out[24]:





array([[ 0.40771446,  1.30595905,  0.        ,  0.82898315,  0.        ],
       [ 0.        ,  0.        ,  0.        ,  0.18661231,  0.        ],
       [ 0.        ,  0.200937  ,  0.        ,  0.43000717,  0.65905596],
       [ 0.        ,  0.        ,  0.        ,  1.14771275,  0.        ],
       [ 0.        ,  0.0997334 ,  0.        ,  0.98441507,  0.        ]])

In [26]:

    

arr = np.array([[1,2,3], [4,5,6], [7,8,9]])
arr


    

    
Out[26]:





array([[1, 2, 3],
       [4, 5, 6],
       [7, 8, 9]])

In [27]:

    

arr.sum()


    

    
Out[27]:





45

In [28]:

    

arr.sum(0)


    

    
Out[28]:





array([12, 15, 18])

In [29]:

    

arr.mean()


    

    
Out[29]:





5.0

In [30]:

    

arr.std()


    

    
Out[30]:





2.5819888974716112

In [31]:

    

arr.var()


    

    
Out[31]:





6.666666666666667

In [32]:

    

bool_arr = np.array([True, False, True])


    

In [33]:

    

bool_arr.any()


    

    
Out[33]:





True

In [34]:

    

bool_arr.all()


    

    
Out[34]:





False

In [35]:

    

arr = randn(5)


    

In [36]:

    

arr
arr.sort()
arr


    

    
Out[36]:





array([-1.51679161, -0.09423467,  0.23712698,  0.27545112,  1.12752669])

In [38]:

    

countries = np.array(['France', 'Germany', 'USA', 'Russia', 'USA', 'Mexico'])


    

In [40]:

    

np.unique(countries)


    

    
Out[40]:





array(['France', 'Germany', 'Mexico', 'Russia', 'USA'], 
      dtype='|S7')

In [42]:

    

np.in1d(['France', 'USA', 'Sweeden'], countries)


    

    
Out[42]:





array([ True,  True, False], dtype=bool)

In [ ]: