numpy库基础知识第二遍

import numpy as np
a=np.array([1,2,3])
print(a)
print(type(a))
print(a.dtype)
print(a.ndim)
print(a.size)
print(a.shape)
b=np.array(([1,3,5,7],[2,4,6,8]))
print(b.ndim)
print(b.size)
print(b.shape)
c=np.array([[1,2,3],[5,7,4]],dtype=complex)
print(c)
print(np.zeros((3,3)))
print(np.ones((2,2)))
print(np.arange(0,5))
print(np.arange(0,12,0.8))
print(np.arange(0,9).reshape(3,3))
print(np.linspace(0,12,4))
print(np.random.random((3,4)))
print(a)
print(a+5)
print(a*a)
c=np.array([[1,2,3],[4,5,6],[7,8,9]])
print(c)
print(c*c)
print(np.dot(c,c))
print(c.dot(c))
print(a)
a+=1
print(a)
print(np.sqrt(a))
print(np.sin(a))
print(a.sum())
print(a.min())
print(a.std())
print(a[2])
print(a[-1])
print(b[1,2])
d=np.arange(0,10)
print(d[2:6])
print(d[2:6:2])
print(b[0,1:2])
print(b[0:2,0:2])
e=np.mat(b)
print(b)
for i in b:
    print(i)
print(e)
for i in e:
    print(i)
for i in e.flat:
    print(i)
print(b)
print(np.apply_along_axis(np.mean,axis=0,arr=b))
print(np.apply_along_axis(np.mean,axis=1,arr=b))
print(b<5)
b.shape=(4,2)
print(b)
b.ravel
print(b)
print(np.mat(b).transpose())
f=np.array([1,2,3])
g=np.array([4,5,6])
print(np.vstack((f,g)))
print(np.hstack((f,g)))
h=np.array([7,8,9])
print(np.column_stack((f,g,h)))
print(np.row_stack((f,g,h)))
print(np.arange(16).reshape((4,4)))
print(b)
print(np.hsplit(b,2))
print(np.vsplit(b,2))
print(np.split(b,[1,3],axis=0))
i=b
i[2,0]=100
print(b)
i[2,0]=2
j=b.copy()
j[2,0]=100
print(b)
print(j)
m=np.arange(6).reshape(3,1,2)
n=np.arange(6).reshape(3,2,1)
print(m+n)
structured=np.array([(1,"first"),(2,"second"),(3,"third")],dtype=[('id','i2'),('number','a6')])
print(structured[2])
print(structured['number'])
print(structured)
x=np.arange(16).reshape(4,4)
np.save("xdate",x)
y=np.load('xdate.npy')
print(y)
z=np.genfromtxt('data.csv',delimiter=',',names=True)
print(z)