Variations in different Sorting techniques in Python

# Python code to sort an array in-place
# using a.sort
import numpy as np
# Numpy array created
a = np.array([9, 3, 1, 7, 4, 3, 6])
# unsorted array print
print('Original array:\n', a)
# Return type is None
print('Return type:', a.sort())
# Sorted array output
print('Original array sorted->', a)

# Python code to create a sorted copy using
# sorted()
import numpy as np
# Numpy array created
a = np.array([9, 3, 1, 7, 4, 3, 6])
# unsorted array print
print('Original array:\n', a)
b = sorted(a)
# sorted list returned to b, b type is
# <class 'list'> 
print('New array sorted->', b)
# original array no change
print('Original array->', a)

# Python code to demonstrate working of np.argsort
import numpy as np
# Numpy array created
a = np.array([9, 3, 1, 7, 4, 3, 6])
# unsorted array print
print('Original array:\n', a)
# Sort array indices
b = np.argsort(a)
print('Sorted indices of original array->', b)
# To get sorted array using sorted indices
# c is temp array created of same len as of b
c = np.zeros(len(b), dtype = int)
for i in range(0, len(b)):
    c[i]= a[b[i]]
print('Sorted array->', c)

# Python code to demonstrate working of 
# np.lexsort()
import numpy as np
# Numpy array created
a = np.array([9, 3, 1, 3, 4, 3, 6]) # First column
b = np.array([4, 6, 9, 2, 1, 8, 7]) # Second column
print('column a, column b')
for (i, j) in zip(a, b):
    print(i, ' ', j)
ind = np.lexsort((b, a)) # Sort by a then by b
print('Sorted indices->', ind)