In [2]:

    

import numpy as np


    

In [54]:

    

a = np.arange(10)
a


    

    
Out[54]:





array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

In [33]:

    

type(a)


    

    
Out[33]:





numpy.ndarray

In [80]:

    

a.dtype


    

    
Out[80]:





dtype('int32')

In [81]:

    

a.shape


    

    
Out[81]:





(10,)

In [38]:

    

a = np.arange(10.0)
a


    

    
Out[38]:





array([ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9.])

In [111]:

    

a.dtype


    

    
Out[111]:





dtype('int32')

In [115]:

    

a = array(["1","2","3"])
a


    

    
Out[115]:





array(['1', '2', '3'], 
      dtype='|S1')

In [116]:

    

a = array(["1","2","3",1,2,3])
a


    

    
Out[116]:





array(['1', '2', '3', '1', '2', '3'], 
      dtype='|S1')

In [44]:

    

a = np.arange(1,10)
a


    

    
Out[44]:





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

In [48]:

    

a = np.arange(1,10,2)
a


    

    
Out[48]:





array([1, 3, 5, 7, 9])

In [50]:

    

a = np.arange(10,1,-1)
a


    

    
Out[50]:





array([10,  9,  8,  7,  6,  5,  4,  3,  2])

In [53]:

    

print('a[0] = %s, a[1] = %s') % (a[0],a[1])


    

    




a[0] = 10, a[1] = 9

In [11]:

    

b = array([1,2,3,4,5])


    

In [13]:

    

type(b)


    

    
Out[13]:





numpy.ndarray

In [15]:

    

b ** 2


    

    
Out[15]:





array([ 1,  4,  9, 16, 25])

In [16]:

    

b + 1


    

    
Out[16]:





array([2, 3, 4, 5, 6])

In [18]:

    

a + b


    

    




---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-18-f96fb8f649b6> in <module>()
----> 1 a + b

ValueError: operands could not be broadcast together with shapes (10,) (5,) 

In [117]:

    

a1 = array([1,2,3,4,5])
a2 = array([5,4,3,2,1])
a1 + a2


    

    
Out[117]:





array([6, 6, 6, 6, 6])

In [128]:

    

a1_a2 = concatenate((a1,a2))


    

    
Out[128]:





(10,)

In [103]:

    

m = array([arange(1,4),arange(4,7)])
m


    

    
Out[103]:





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

In [105]:

    

m.shape


    

    
Out[105]:





(2, 3)

In [107]:

    

print(m[0,0])
print(m[0,1])
print(m[1,0])
print(m[1,1])


    

    




1
2
4
5

In [171]:

    

m = array([arange(1,5),arange(4,7)])
m


    

    
Out[171]:





array([array([1, 2, 3, 4]), array([4, 5, 6])], dtype=object)

In [172]:

    

m.shape


    

    
Out[172]:





(2,)

In [173]:

    

m[0]


    

    
Out[173]:





array([1, 2, 3, 4])

In [131]:

    




    

In [145]:

    

a1 = array([[1,2],[3,4]])
a2 = array([5,6])
print(a1)
print(a2)


    

    




[[1 2]
 [3 4]]
[5 6]

In [147]:

    

concatenate((a1,a2),axis=0)


    

    




---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-147-7abe06269518> in <module>()
----> 1 concatenate((a1,a2),axis=0)

ValueError: all the input arrays must have same number of dimensions

In [152]:

    

print(a1.shape)
print(a2.shape)


    

    




(2, 2)
(2,)

In [161]:

    

a1 = array([[1,2],[3,4]])
a2 = array([[5,6]])
print(a1)
print(a2)


    

    




[[1 2]
 [3 4]]
[[5 6]]

In [164]:

    

print(a1.shape)
print(a2.shape)


    

    




(2, 2)
(1, 2)

In [166]:

    

concatenate((a1,a2),axis=0)


    

    
Out[166]:





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

In [1]:

    

concatenate((a1,a2.T),axis = 1)


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-1-ab3a56bc0583> in <module>()
----> 1 concatenate((a1,a2.T),axis = 1)

NameError: name 'concatenate' is not defined

In [4]:

    

a = np.arange(24)


    

In [5]:

    

a


    

    
Out[5]:





array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,
       17, 18, 19, 20, 21, 22, 23])

In [7]:

    

b = a.reshape(2,3,4)


    

In [9]:

    

b


    

    
Out[9]:





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

       [[12, 13, 14, 15],
        [16, 17, 18, 19],
        [20, 21, 22, 23]]])

In [11]:

    

b[0,0,0]


    

    
Out[11]:





0

In [13]:

    

b[:,0,0]


    

    
Out[13]:





array([ 0, 12])

In [15]:

    

b[0,:,:]


    

    
Out[15]:





array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11]])

In [16]:

    

b[0,...]


    

    
Out[16]:





array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11]])

In [22]:

    

b[0,1,::2]


    

    
Out[22]:





array([4, 6])

In [24]:

    

b[0]+b[1]


    

    
Out[24]:





array([[12, 14, 16, 18],
       [20, 22, 24, 26],
       [28, 30, 32, 34]])

In [42]:

    

b[0] * b[1]


    

    
Out[42]:





array([[  0,  13,  28,  45],
       [ 64,  85, 108, 133],
       [160, 189, 220, 253]])

In [53]:

    

np.arange(3*2).reshape(3,2).dot(np.arange(3*2).reshape(3,2).T)


    

    
Out[53]:





array([[ 1,  3,  5],
       [ 3, 13, 23],
       [ 5, 23, 41]])

In [29]:

    

#計算一二維矩陣每個欄的總和, 平均數, 標準差


    

In [33]:

    

a = np.arange(10).reshape(2,5)


    

In [35]:

    

a


    

    
Out[35]:





array([[0, 1, 2, 3, 4],
       [5, 6, 7, 8, 9]])

In [41]:

    

a[:,1].sum()


    

    
Out[41]:





7