python数据分析之numpy

 1 # -*- coding: utf-8 -*-
 2 """
 3 Spyder Editor
 4 
 5 This is a temporary script file.
 6 """
 7 
 8 import numpy as np
 9 a = np.array([1, 2, 3])
10 b = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
11 b[1,1]=10
12 print(a.shape)#3
13 print(b.shape)#(3,3)
14 print(a.dtype)#int32
15 
16 import numpy as np
17 persontype = np.dtype({
18     ‘names‘:[‘name‘, ‘age‘, ‘chinese‘, ‘math‘, ‘english‘],
19     ‘formats‘:[‘S32‘,‘i‘, ‘i‘, ‘i‘, ‘f‘]})
20 peoples = np.array([("lisi",32,75,100, 90),("wangW",24,85,96,88.5),
21        ("ZhaoYun",28,85,92,96.5),("HuangZhong",29,65,85,100)],
22     dtype=persontype)
23 ages = peoples[:][‘age‘]
24 chineses = peoples[:][‘chinese‘]
25 maths = peoples[:][‘math‘]
26 englishs = peoples[:][‘english‘]
27 print(np.mean(ages))#计算平均值
28 print(np.mean(chineses))
29 print(np.mean(maths))
30 print(np.mean(englishs))
31 
32 x1 = np.arange(1,11,2)
33 x2 = np.linspace(1,9,5)
34 
35 x1 = np.arange(1,11,2)
36 x2 = np.linspace(1,9,5)
37 print(np.add(x1, x2))#[ 2.  6. 10. 14. 18.]
38 print(np.subtract(x1, x2))
39 #print(np.multiply((x1,x2)))
40 print(np.divide(x1, x2))
41 print(np.power(x1, x2))
42 print(np.remainder(x1, x2))
43 
44 
45 import numpy as np
46 a=np.array([[1,2,3],[4,5,6],[7,8,9]])
47 print(np.amin(a))#1
48 print(np.amin(a,0))#[1 2 3]
49                   
50 print(np.amin(a,1)) #[1 4 7]
51 print(np.amax(a))#9
52 print(np.amax(a,0))#[7 8 9]
53 print(np.amax(a,1))#[3 6 9]
54 
55 a = np.array([[1,2,3], [4,5,6], [7,8,9]])
56 print(np.ptp(a))#8 所有元素中最大和最小的差值
57 print(np.ptp(a,0))#[6 6 6]
58 print(np.ptp(a,1))#[2 2 2]
59 
60 a = np.array([1,2,3,4])
61 wts = np.array([1,2,3,4])
62 print(np.average(a))#2.5
63 #print(np.average((a,weights=wts))
64 
65 a = np.array([1,2,3,4])
66 print(np.std(a))
67 print(np.var(a))
68 
69 a = np.array([[4,3,2],[2,4,1]])
70 print(np.sort(a))#每个子元素排序
71 print(np.sort(a, axis=None))#
72 print(np.sort(a, axis=0))  
73 print(np.sort(a, axis=1))