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20190222_一堆数据摆在你面前，老板让你画成图表，怎么做？
文章目录
小技巧
避免采用隐式拷贝,多用就地操作,比如你想打印5个b,有两种方法:
# 方法1:
b = 5
b *= 5
print(b)
# 方法2:
b = 5
a = b * 5
print(a)
25
25
ndarray 对象
创建数组
import numpy as np
a = np.array([[1,2,3],[4,5,6],[7,8,9]])
print (a)
[[1 2 3]
[4 5 6]
[7 8 9]]
用shape 属性获得数组的大小
import numpy as np
a = np.array([[1,2,3],[4,5,6],[7,8,9]])
print(a.shape)
(3, 3)
更改数组的元素,把元素中5 换成0,直接用小标
a = np.array([[1,2,3],[4,5,6],[7,8,9]])
a[1,1] = 0
print (a)
[[1 2 3]
[4 0 6]
[7 8 9]]
通过dtype获得元素的属性
import numpy as np
a = np.array([[1,2,3],[4,5,6],[7,8,9]])
print (a.dtype)
int32
结构数组
自定义结构数组
import numpy as np
student_type = np.dtype({
'names':['name','chinese','math','english'],
'formats': ['S32', 'i', 'i', 'i']
})
定义真实数组
students = np.array([('zhangsan',85,72,56),('lisi',88,90,68),
('wangwu',78,66,88)],dtype = student_type)
取出全部值
name = students[:]['name']
print(name)
chinese = students[:]['chinese']
print(chinese)
math = students[:]['math']
print(math)
english = students[:]['english']
[b'zhangsan' b'lisi' b'wangwu']
[85 88 78]
[72 90 66]
求平均值
print(np.mean(chinese))
print(np.mean(math))
print(np.mean(english))
83.66666666666667
76.0
70.66666666666667
ufun 运算
创建连续数组
# 方法一:arange(初始值,终值,步长) # 终值为开区间
import numpy as np
b = np.arange(1,8,2)
print(b)
[1 3 5 7]
# 方法二:linspace(初始值,终值,元素个数),其中终值是闭区间
import numpy as np
b = np.linspace(1,7,4)
print(b)
[1. 3. 5. 7.]
算法运算
加减乘除
import numpy as np
b = np.linspace(1,7,4)
c = np.arange(1,8,2)
print(np.add(b,c)) # 加法运算
print(np.subtract(b,c)) # 减法运算
print(np.multiply(b,c)) # 乘法运算
print(np.divide(b,c)) # 除法运算
print(np.mod(b,c)) # 取余运算
[ 2. 6. 10. 14.]
[0. 0. 0. 0.]
[ 1. 9. 25. 49.]
[1. 1. 1. 1.]
[0. 0. 0. 0.]
最大值,最小值,平均值,标准差,方差
a = np.array([[1,2,3],[4,5,6],[7,8,9]])
print(a.max()) # 数组中最大值
print(a.min()) # 数组中最小值
print(a.mean()) #数组中的平均值
print(a.std()) # 数组中的标准差
print(a.var()) # 数组中的方差
9
1
5.0
2.581988897471611
6.666666666666667