In [5]:
import numpy as np
In [6]:
np
Out[6]:
<module 'numpy' from '/home/don/miniconda3/lib/python3.8/site-packages/numpy/__init__.py'>
Creating arrays¶
In [8]:
np.zeros(10)
Out[8]:
array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])
In [11]:
np.ones(10)
Out[11]:
array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1.])
In [12]:
np.full(10, 2.5)
Out[12]:
array([2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5])
In [14]:
a = np.array([1, 2, 3, 5, 7, 12])
a
Out[14]:
array([ 1, 2, 3, 5, 7, 12])
In [16]:
a[2]
Out[16]:
3
In [17]:
a[2] = 10
a
Out[17]:
array([ 1, 2, 10, 5, 7, 12])
In [19]:
np.arange(10)
Out[19]:
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
In [20]:
np.arange(3, 10)
Out[20]:
array([3, 4, 5, 6, 7, 8, 9])
In [21]:
np.linspace(0, 1, 11)
Out[21]:
array([0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. ])
In [22]:
np.linspace(0, 100, 11)
Out[22]:
array([ 0., 10., 20., 30., 40., 50., 60., 70., 80., 90., 100.])
Multi-dimentional arrays¶
In [27]:
np.zeros((5, 2))
Out[27]:
array([[0., 0.],
[0., 0.],
[0., 0.],
[0., 0.],
[0., 0.]])
In [33]:
n = np.array([
[1, 2, 3],
[4, 5, 6],
[7, 8, 9]
])
In [35]:
n[0, 1] = 20
In [36]:
n
Out[36]:
array([[ 1, 20, 3],
[ 4, 5, 6],
[ 7, 8, 9]])
In [37]:
n[0]
Out[37]:
array([ 1, 20, 3])
In [38]:
n[1]
Out[38]:
array([4, 5, 6])
In [40]:
n[2] = [1, 1, 1]
In [42]:
n
Out[42]:
array([[ 1, 20, 3],
[ 4, 5, 6],
[ 1, 1, 1]])
In [43]:
n[:, 1]
Out[43]:
array([20, 5, 1])
In [44]:
n[:, 2]
Out[44]:
array([3, 6, 1])
In [45]:
n[:, 2] = [0, 1, 2]
In [46]:
n
Out[46]:
array([[ 1, 20, 0],
[ 4, 5, 1],
[ 1, 1, 2]])
In [ ]:
Randomly generated arrays¶
In [47]:
np.random.rand(5, 2)
Out[47]:
array([[0.231976 , 0.74911649],
[0.8326009 , 0.13289997],
[0.27142672, 0.41198653],
[0.97242509, 0.03984149],
[0.92495703, 0.96274713]])
In [48]:
np.random.seed(2)
np.random.rand(5, 2)
Out[48]:
array([[0.4359949 , 0.02592623],
[0.54966248, 0.43532239],
[0.4203678 , 0.33033482],
[0.20464863, 0.61927097],
[0.29965467, 0.26682728]])
In [49]:
np.random.seed(2)
np.random.randn(5, 2)
Out[49]:
array([[-0.41675785, -0.05626683],
[-2.1361961 , 1.64027081],
[-1.79343559, -0.84174737],
[ 0.50288142, -1.24528809],
[-1.05795222, -0.90900761]])
In [51]:
np.random.seed(2)
100 * np.random.rand(5, 2)
Out[51]:
array([[43.59949021, 2.59262318],
[54.96624779, 43.53223926],
[42.03678021, 33.0334821 ],
[20.4648634 , 61.92709664],
[29.96546737, 26.68272751]])
In [52]:
np.random.seed(2)
np.random.randint(low=0, high=100, size=(5, 2))
Out[52]:
array([[40, 15],
[72, 22],
[43, 82],
[75, 7],
[34, 49]])
In [ ]:
Element-wise operations¶
In [54]:
a = np.arange(5)
a
Out[54]:
array([0, 1, 2, 3, 4])
In [55]:
a + 1
Out[55]:
array([1, 2, 3, 4, 5])
In [56]:
a * 2
Out[56]:
array([0, 2, 4, 6, 8])
In [57]:
a / 100
Out[57]:
array([0. , 0.01, 0.02, 0.03, 0.04])
In [58]:
10 + (a * 2)
Out[58]:
array([10, 12, 14, 16, 18])
In [60]:
b = (10 + (a * 2)) ** 2 / 100
In [61]:
b
Out[61]:
array([1. , 1.44, 1.96, 2.56, 3.24])
In [62]:
a + b
Out[62]:
array([1. , 2.44, 3.96, 5.56, 7.24])
In [63]:
a * b
Out[63]:
array([ 0. , 1.44, 3.92, 7.68, 12.96])
In [64]:
a / b
Out[64]:
array([0. , 0.69444444, 1.02040816, 1.171875 , 1.2345679 ])
In [65]:
a / b + 10
Out[65]:
array([10. , 10.69444444, 11.02040816, 11.171875 , 11.2345679 ])
Comparison opertaions¶
In [66]:
a
Out[66]:
array([0, 1, 2, 3, 4])
In [67]:
a >= 2
Out[67]:
array([False, False, True, True, True])
In [68]:
b
Out[68]:
array([1. , 1.44, 1.96, 2.56, 3.24])
In [69]:
a > b
Out[69]:
array([False, False, True, True, True])
In [70]:
a[a > b]
Out[70]:
array([2, 3, 4])
Summarizing operations¶
In [73]:
a
Out[73]:
array([0, 1, 2, 3, 4])
In [72]:
a.min()
Out[72]:
0
In [74]:
a.sum()
Out[74]:
10
In [75]:
a.max()
Out[75]:
4
In [76]:
a.mean()
Out[76]:
2.0
In [77]:
a.std()
Out[77]:
1.4142135623730951
In [78]:
n
Out[78]:
array([[ 1, 20, 0],
[ 4, 5, 1],
[ 1, 1, 2]])
In [79]:
n.min()
Out[79]:
0
In [80]:
n.sum()
Out[80]:
35
In [82]:
n.sum([:, 2])
Input In [82] n.sum([:, 2]) ^ SyntaxError: invalid syntax
In [85]:
sum(n[:, 1])
Out[85]:
26
Leave a Reply