Tableau
Tableau Charts & Graphs Tutorial: Types & Examples
Tableau can create interactive visualizations customized for the target audience. In this...
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]])
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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