Numpy Basic

Numpy Basic

Create a Numpy Array

 import numpy as np  
 # create numpy array  
 a = np.array([2,3,4])  
 print ("***** a *****")  
 print ("value", a) # print array  
 print ("data type", a.dtype) # data type of array   
 print ("shape", a.shape) # size of array in each dimension(m, n)  
 print ("size", a.size) # total number of elements of the array  
 print ("itemsize", a.itemsize) # the size in bytes of each element of the array  
 print ("ndim", a.ndim)  
 print ("data", a.data) # buffer containing the actual elements of the array  
 print ("***** b *****") # number of axes (dimensions) of the array.  
 b = np.array([[1.2, 3.5, 5.1], [1.2, 3.5, 5.1]])  
 print ("value", b)  
 print ("data type", b.dtype)  
 print ("shape", b.shape)  
 print ("size", b.size)  
 print ("itemsize", b.itemsize)  
 print ("ndim", b.ndim)  
 print ("data", b.data)  

Create Numpy Array of size (M, N) 

 # create numpy array of shape (3, 4) and all element are 0  
 arr = np.zeros((3,4))  
 print (arr)  

Numpy Arrange (np.arrange)

 # create number starting between 10 to 30 with difference 5  
 arr = np.arange(10, 30, 5)  
 print (arr) # 10, 15, 20, 25   

 # create 1d array  
 a = np.arange(6)   
 print (a) # create array 0, 1, 2, 3, 4, 5  

 # 2d array  
 b = np.arange(12).reshape(4,3)  
 print (b)  

Basic Operator

  a = np.array( [20,30,40,50])    
  b = np.arange(4) # [0, 1, 2, 3]   
  c = a - b # [20-0, 30-1, 40-2, 50-3] = [20, 29, 38, 47]   
  print (c) # add element of same index   
  c = a*b # multiply element of same index   
  print (c)    
  # matricx dot product   
  c = a.dot(b)   
  print (c) # matrix multiplication   
 </code></pre>  

Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.