Numpy

Numpy是数据处理的利器

import numpy as np
array = np.zeros((3,4)) #生成零矩阵
array1 = np.ones((3,4))#生成单位矩阵
array2 = np.empty((3,4))#生成近似零的矩阵
print(array)
print(array1)
print(array2)

 

 

 

array = np.arange(10,20,2)  #从10到20间隔2
array = np.arange(12).reshape((3,4))  #分成12个，生产3x4的矩阵
array = np.linspace(1,10,6)  #生成线段数列  6个点5段
array = np.linspace(1,10,6).reshape((2,3))
array = np.array([1,2,3],dtype=np.int64)
print(array.dtype)  #显示位数
print(array.ndim)  #维度
print(array.shape)  #形状
print(array.size) #大小

 

 

 

a = np.array([[1,1],
              [0,1]])
b = np.arange(4).reshape((2,2))
print(a)
print(b)
c = a*b
print(c)
c_dot = np.dot(a,b)
print(c_dot)
c_dot_2 = a.dot(b)
print(c_dot_2)

 

 

 

A = np.random.random((2,4))

print(A)
print(np.sum(A))
print(np.min(A))
print(np.max(A))
print(np.mean(A))
print(np.average(A))
print(np.median(A) )#中位数
print(np.cumsum(A))  #累加
print(np.diff(A))   #累差
print(np.nonzero(A))  #非零的数
print(np.sort(A))  #逐行排序
print(np.transpose(A)) # 转置
print(np.clip(A,5,9))  #所有小于5的数都等于5，大于9的数等于9
print(np.sum(A,axis=0))  #在列中
print(np.sum(A,axis=1) ) #在行中
print(np.argmin(A) )# 最小值的索引

B = np.arange(3,15).reshape(3,4)
print(B)
for row in B:
    print(row)

 

 

 

C= np.arange(3,15).reshape(3,4)
print(C)
for column in C.T:
    print(column)

 

 

 

D = np.arange(3,15).reshape((3,4))
print(D)
for item in D.flat:
    print(item)

 

 

 

E = np.array([1,1,1])
F = np.array([2,2,2])

G = np.vstack((E,F))
H = np.hstack((E,F))

print(G)
print(H)
print(G.shape,H.shape)

 

 

 

E = np.array([1,1,1])
F = np.array([2,2,2])

G = np.vstack((E,F))[:,np.newaxis]
H = np.hstack((E,F))[:,np.newaxis]

print(G)
print(H)
print(G.shape,H.shape)

 

 

 

J = np.arange(12).reshape((3,4))
print(J)

print(np.split(J,3,axis=0))

 

 

 

J = np.arange(12).reshape((3,4))
print(J)

print(np.array_split(J,3,axis=0))