Reshape Data

In some occasions, you need to reshape the data from wide to long. You can use the reshape function for this. The syntax is

numpy.reshape(a, newShape, order='C')

Here,

a: Array that you want to reshape

newShape: The new desires shape

Order: Default is C which is an essential row style.

Exampe of Reshape

import numpy as np
e  = np.array([(1,2,3), (4,5,6)])
print(e)
e.reshape(3,2)

Output:

 // Before reshape
[[1 2 3] 
 [4 5 6]]			
//After Reshape
array([[1, 2],       
	[3, 4],       
	[5, 6]])			

Flatten Data

When you deal with some neural network like convnet, you need to flatten the array. You can use flatten(). The syntax is

numpy.flatten(order='C')

Here,

Order: Default is C which is an essential row style.

Exampe of Flatten

e.flatten()			

Output:

array([1, 2, 3, 4, 5, 6])			

 

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