Skip to content
Related Articles

Related Articles

Improve Article

Create a contiguous flattened NumPy array

  • Last Updated : 19 Aug, 2020

Let us see how to create a contiguous array in NumPy.The contiguous flattened array is a two-dimensional and multi-dimensional array that is stored as a one-dimensional array. We will be using the ravel() method to perform this task.

Syntax : numpy.ravel(array, order = ‘C’)
Parameters :

  • array : Input array.
  • order : C-contiguous, F-contiguous, A-contiguous; optional

Returns : Flattened array having same type as the Input array and and order as per choice.

Example 1 : Flattening a 2D array.

Python3






# Importing libraries
import numpy as np
  
# Creating 2D array
arr = np.array([[5, 6, 7], [8, 9, 10]])
print("Original array:\n", arr)
  
# Flattening the array
flattened_array = np.ravel(arr)
print("New flattened array:\n", flattened_array)

Output :

Original array:
 [[ 5  6  7]
 [ 8  9 10]]
New flattened array:
 [ 5  6  7  8  9 10]

Example 2 : Flattening a 3D array.

Python3




# Importing libraries
import numpy as np
  
# Creating 3D array
arr = np.array([[[3, 4], [5, 6]], [[7, 8], [9, 0]]])
print("Original array:\n", arr)
  
# Flattening the array
flattened_array = np.ravel(arr)
print("New flattened array:\n", flattened_array)

Output :

Original array:
 [[[3 4]
  [5 6]]

 [[7 8]
  [9 0]]]
New flattened array:
 [3 4 5 6 7 8 9 0]

 Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.  

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course




My Personal Notes arrow_drop_up
Recommended Articles
Page :