Python---numpy的一些操作_python def main numpy代码demo-优快云博客

本文链接：https://blog.youkuaiyun.com/zhangmary/article/details/79580786

本文介绍了使用Anaconda安装及Numpy的基本操作，包括数组属性、随机数生成、数学运算等，并通过实例演示了如何利用Numpy进行数据处理。

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安装了Anaconda感觉棒棒哒，Numpy关于其中

numpy的数据类型

array的属性attribute

随机数的生成

一些简单的加减乘除操作等等

# encoding = utf-8 #
import numpy as np

def main():
    lst = [[1, 3, 5], [2, 4, 6]]
    print(type(lst))
    np_lst = np.array(lst)
    print(type(np_lst))
    np_lst=np.array(lst,dtype=np.float)
    # np_array attributes #
    print(np_lst.shape)
    print(np_lst.ndim)
    print(np_lst.dtype)
    print(np_lst.itemsize)
    print(np_lst.size)
    #2 some arrays#
    print(np.zeros([2,4]))
    print(np.ones([3,5]))
    print("Rand")#in 0-1 #
    print (np.random.rand(2,4))
    print (np.random.rand())
    print ("RandInt:") # you can assign range #
    print (np.random.randint(1,10,4))
    print ("Randn:") # random normal distribution #
    print (np.random.randn(2,4))
    print("Choice:") # random in assign number #
    print(np.random.choice([1,2,3,4,5,6,9,22,34,44]))
    print ("Distribution:")# random in math methods #
    print (np.random.beta(1,10,20))
    # 3 array operations #
    lst = np.arange(1,11).reshape([2,5])
    print (np.exp(lst))
    print (np.exp2(lst))
    print (np.sqrt(lst))
    print (np.sin(lst))
    print (np.log(lst))
    lst =np.array([[[1,2,3,4],[4,5,6,7]],
                   [[7,8,9,10],[10,11,12,13]],
                   [[13,14,15,16],[16,17,18,19]]])
    print(lst.sum(axis=0)) # more deep more high #
    print(lst.sum(axis=1))
    print(lst.sum(axis=2))
    print(lst.max(axis=1))
    print(lst.min(axis=1))

    lst1 = np.array([10, 20, 30, 40])
    lst2 = np.array([1, 2, 3, 4])
    print ("Add")
    print (lst1+lst2)
    print ("Subtract")
    print (lst1-lst2)
    print ("Multiplication")
    print (lst1*lst2)
    print ("Division")
    print (lst1/lst2)
    print ("Square")
    print (lst1**2)
    print ("Dot")
    print (np.dot(lst1.reshape(2,2),lst2.reshape(2,2)))
    print ("Concatenate")
    print (np.concatenate((lst1,lst2),axis=0))
    print (np.vstack((lst1, lst2)))
    print (np.hstack((lst1, lst2)))
    print (np.split(lst1,4))
    print (np.copy(lst1))

if __name__=="__main__":
    main()