Both lists and NumPy arrays are inter-convertible. Since NumPy is a fast (High-performance) Python library for performing mathematical operations so it is preferred to work on NumPy arrays rather than nested lists.
Method 1: Using numpy.array().
Approach :
- Import numpy package.
- Initialize the nested list and then use numpy.array() function to convert the list to an array and store it in a different object.
- Display both list and NumPy array and observe the difference.
Example:
# importing numpy library
import numpy
# initializing list ls = [[1, 7, 0], [ 6, 2, 5]]
# converting list to array ar = numpy.array(ls)
# displaying list
print ( ls)
# displaying array
print ( ar)
Output :
[[1, 7, 0], [6, 2, 5]]
[[1 7 0] [6 2 5]]
Method 2: Using numpy.asarray().
Approach :
- Import numpy package.
- Initialize the nested 4-dimensional list and then use numpy.asarray() function to convert the list to the array and store it in a different object.
- Display both list and NumPy array and observe the difference.
Example:
# importing numpy library
import numpy
# initializing list ls = [[1, 7, 0],[ 6, 2, 5],[ 7, 8, 9],[ 41, 10, 20]]
# converting list to array ar = numpy.asarray(ls)
# displaying list print ( ls)
# displaying array print ( ar)
Output :
[[1, 7, 0], [6, 2, 5], [7, 8, 9], [41, 10, 20]]
[[ 1 7 0] [ 6 2 5] [ 7 8 9] [41 10 20]]