Skip to content
Related Articles

Related Articles

Improve Article
Save Article
Like Article

Flatten A list of NumPy arrays

  • Last Updated : 16 Sep, 2021

Prerequisite Differences between Flatten() and Ravel() Numpy Functions, numpy.ravel() in Python

In this article, we will see how we can flatten a list of numpy arrays. NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.

 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

Flatten a list of NumPy array means to combine the multiple dimensional NumPy arrays into a single array or list, below is the example 



List of numpy array : 
[array([[ 0.00353654]]), 
array([[ 0.00353654]]), 
array([[ 0.00353654]]), 
array([[ 0.00353654]]), 
array([[ 0.00353654]]), 
array([[ 0.00353654]]), 
array([[ 0.00353654]]), 
array([[ 0.00353654]]), 
array([[ 0.00353654]]), 
array([[ 0.00353654]]), 
array([[ 0.00353654]]), 
array([[ 0.00353654]]), 
array([[ 0.00353654]])]

Flatten numpy array : 
array([ 0.00353654, 0.00353654, 0.00353654, 0.00353654, 0.00353654, 
0.00353654, 0.00353654, 0.00353654, 0.00353654, 0.00353654, 
0.00353654, 0.00353654, 0.00353654]) 
 

Method 1 
Using numpy’s concatenate method  

Python3




# importing numpy as np
import numpy as np
 
# list of numpy array
list_array = [np.array([[1]]),
               np.array([[2]]),
               np.array([[3]]),
               np.array([[4]]),
               np.array([[5]]),
               np.array([[6]]),
               np.array([[7]]),
               np.array([[8]]),
               np.array([[9]]),
               np.array([[10]]),
               np.array([[11]]),
               np.array([[12]]),
               np.array([[13]]),
               np.array([[14]]),
               np.array([[15]]),
               np.array([[16]])]
 
# concatenating all the numpy array
flatten = np.concatenate(list_array)
 
# printing the ravel flatten array
print(flatten.ravel())

Output : 

[ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16]

Method 2 
Using numpy’s flatten method 

Python3




# importing numpy as np
import numpy as np
 
# list of numpy array
list_array = [np.array([[1]]),
               np.array([[2]]),
               np.array([[3]]),
               np.array([[4]]),
               np.array([[5]]),
               np.array([[6]]),
               np.array([[7]]),
               np.array([[8]]),
               np.array([[9]]),
               np.array([[10]]),
               np.array([[11]]),
               np.array([[12]]),
               np.array([[13]]),
               np.array([[14]]),
               np.array([[15]]),
               np.array([[16]])]
 
# flatten the numpy array
flatten = np.array(list_array).flatten()
 
# printing the flatten array
print(flatten)

Output : 



[ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16]

Method 3 
Using numpy’s ravel method 

Python3




# importing numpy as np
import numpy as np
 
# list of numpy array
list_array = [np.array([[1]]),
               np.array([[2]]),
               np.array([[3]]),
               np.array([[4]]),
               np.array([[5]]),
               np.array([[6]]),
               np.array([[7]]),
               np.array([[8]]),
               np.array([[9]]),
               np.array([[10]]),
               np.array([[11]]),
               np.array([[12]]),
               np.array([[13]]),
               np.array([[14]]),
               np.array([[15]]),
               np.array([[16]])]
 
# flatten the numpy array using ravel method
flatten = np.array(list_array).ravel()
 
# printing the flatten array
print(flatten)

Output : 

[ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16]

Method 4 
Using numpy’s reshape method  

Python3




# importing numpy as np
import numpy as np
 
# list of numpy array
list_array = [np.array([[1]]),
               np.array([[2]]),
               np.array([[3]]),
               np.array([[4]]),
               np.array([[5]]),
               np.array([[6]]),
               np.array([[7]]),
               np.array([[8]]),
               np.array([[9]]),
               np.array([[10]]),
               np.array([[11]]),
               np.array([[12]]),
               np.array([[13]]),
               np.array([[14]]),
               np.array([[15]]),
               np.array([[16]])]
 
# flatten the numpy array using reshape method
flatten = np.array(list_array).reshape(-1)
 
# printing the flatten array
print(flatten)

Output : 

[ 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16]

 




My Personal Notes arrow_drop_up
Recommended Articles
Page :

Start Your Coding Journey Now!