Flatten A list of NumPy arrays
Last Updated :
23 Jul, 2025
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]
