Convert Python List to numpy Arrays

A list in Python is a linear data structure that can hold heterogeneous elements they do not require to be declared and are flexible to shrink and grow. On the other hand, an array is a data structure which can hold homogeneous elements, arrays are implemented in Python using the NumPy library. Arrays require less memory than list.

The similarity between an array and a list is that the elements of both array and a list can be identified by its index value.
In Python lists can be converted to arrays by using two methods from the NumPy library:

• Using numpy.array()

Python3

# importing library
import numpy

# initializing list
lst = [1, 7, 0, 6, 2, 5, 6]

# converting list to array
arr = numpy.array(lst)

# displaying list
print ("List: ", lst)

# displaying array
print ("Array: ", arr)

Output:

List:  [1, 7, 0, 6, 2, 5, 6]
Array:  [1 7 0 6 2 5 6]

• Using numpy.asarray()

Python3

# importing library
import numpy

# initializing list
lst = [1, 7, 0, 6, 2, 5, 6]

# converting list to array
arr = numpy.asarray(lst)

# displaying list
print ("List:", lst)

# displaying array
print ("Array: ", arr)

Output:

List:  [1, 7, 0, 6, 2, 5, 6]
Array:  [1 7 0 6 2 5 6]

The vital difference between the above two methods is that numpy.array() will make a duplicate of the original object and numpy.asarray() would mirror the changes in the original object. i.e :

When a copy of the array is made by using numpy.asarray(), the changes made in one array would be reflected in the other array also but doesn’t show the changes in the list by which if the array is made. However, this doesn’t happen with numpy.array().

Python3

# importing library
import numpy

# initializing list
lst = [1, 7, 0, 6, 2, 5, 6]

# converting list to array
arr = numpy.asarray(lst)

# displaying list
print ("List:", lst)

# displaying array
print ("arr: ", arr)

# made another array out of arr using asarray function
arr1 = numpy.asarray(arr)

#displaying arr1 before the changes made
print("arr1: " , arr1)

#change made in arr1
arr1[3] = 23

#displaying arr1 , arr , list after the change has been made
print("lst: " , lst)
print("arr: " , arr)
print("arr1: " , arr1)

Output :

List: [1, 7, 0, 6, 2, 5, 6]
arr:  [1 7 0 6 2 5 6]
arr1:  [1 7 0 6 2 5 6]
lst:  [1, 7, 0, 6, 2, 5, 6]
arr:  [ 1  7  0 23  2  5  6]
arr1:  [ 1  7  0 23  2  5  6]

In “arr” and “arr1” the change is visible at index 3 but not in 1st.