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Flatten A list of NumPy arrays

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  • Last Updated : 16 Sep, 2021
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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.

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]

 


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