python-numpyライブラリの基礎知識

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([[1.3,5.7,9.1],[2.4,6.8,10.12]])
print(b)
print(b.dtype)
print(b.ndim)
print(b.size)
print(b.shape)
print(b.itemsize)   #       
print(b.data)       #   
c=np.array(((1,5,9),(7,5,3)))  #      
print(c)
d=np.array([(1,5,7),[3,8,4],(7,6,9)])   #              
print(d)
e=np.array([(6,5,7),(9,7,2)],dtype=np.complex64)   #      
print(e)
f=np.zeros((3,3))  #  float64                  shape  
print(f)
g=np.ones((3,3))   #  float64
print(g)
h=np.arange(0,10)  # 0 9
print(h)
i=np.arange(1,16,3)  #         
print(i)
j=np.linspace(0,9,3)   #                
print(j)
k=np.arange(0,15).reshape(3,5)   #       
print(k)
l=np.random.random((3,3))   #    
print(l)
l=l+2       #       
print(l)
l=l*2
print(l)
print(d)
m=d*d     #                  * numpy              
print(m)
n=np.array([(1,2,4),(2,4,7),(4,7,5),(1,3,4)])
#print(d*n)     shape      
o=np.array([(1,2,3),(2,3,4),(4,5,6)])
p=np.dot(o,d)     #    
print(p)
print(o.dot(d))  #         
print(d.dot(o))  #          
print(np.sqrt(d))
print(np.log(d))
print(np.sin(d))
print(d.sum())
print(d.min())
print(d.max())
print(d.mean())
print(d.std())   #   
q=np.array([1,2,3,4])
print(q[1])    #  0 1 2 3
print(q[-3])   #  -4 -3 -2 -1
print(d[2,2])
print(q[0:3])   #  
print(q[0:3:2])
print(d)
print(d[0,:])
print(d[:,1])
print(d[0:2,0:2])
print(d[[0,2],0:2])    #      0，2（       ）       0：2（       ）
for dd in d:
    for ddd in dd:
        print(ddd)
print(np.apply_along_axis(np.mean,axis=0,arr=d))    #axis=0                   1      
r=np.random.random((4,4))
print(r<0.5)    #      
s=r[r<0.5]
print(s)
print(d.ravel())   #ravel      
print(d.transpose())   #    
t=np.ones((3,3))
u=np.zeros((3,3))
print(np.vstack((t,u)))    #         
print(np.hstack((t,u)))    #         
v=np.array([1,2,3])
w=np.array([4,5,6])
x=np.array([7,8,9])
print(np.row_stack((v,w,x)))
print(np.column_stack((v,w,x)))
[A,B,C]=np.hsplit(d,3)
print(A)
[A,B,C]=np.vsplit(d,3)
print(B)
[A,B,C]=np.split(d,[1,3],axis=0)
print(d)
print(A,B,C)
structured=np.array([(1,'first'),(2,'second'),(3,'third')],dtype=('i2,a6'))  #     
print(structured)
print(structured[1])
print(structured['f1'])     #     
structured=np.array([(1,'first'),(2,'second'),(3,'third')],dtype=[('num','i2'),('eng','a6')])
print(structured['eng'])
np.save('save_date',d)
load_date=np.load('save_date.npy')
print(load_date)
data=np.genfromtxt('data.csv',delimiter=',',names=True)
print(data)