Python program to sort a tuple by its float element

This article demonstrates how to sort a list of tuples by their float elements in Python. We'll explore three different approaches: using sorted(), using sort(), and implementing bubble sort manually.

Input-Output Scenarios

The following scenarios show how tuples are sorted by their float elements in descending order ?

Scenario 1

Input:
data = [('Dengue', '54.865'), ('Malaria', '345.743'), ('Corona', '456.864'), ('Typhoid', '35.285'), ('Jaundice', '83.367')]
Output:
[('Corona', '456.864'), ('Malaria', '345.743'), ('Jaundice', '83.367'), ('Dengue', '54.865'), ('Typhoid', '35.285')]

Scenario 2

Input:
data = [('638', '54.865'), ('932', '345.743'), ('256', '456.864'), ('843', '35.285'), ('246', '83.367')]
Output:
[('256', '456.864'), ('932', '345.743'), ('246', '83.367'), ('638', '54.865'), ('843', '35.285')]

Using sorted() Function

The sorted() function creates a new sorted list without modifying the original data. It accepts an iterable, an optional key function for custom sorting, and a reverse parameter ?

def sort_tuple(data):
    return sorted(data, key=lambda item: float(item[1]), reverse=True)

# Sample data
data = [('Dengue', '54.865'), ('Malaria', '345.743'), ('Corona', '456.864'), 
        ('Typhoid', '35.285'), ('Jaundice', '83.367')]

result = sort_tuple(data)
print("Original data:", data)
print("Sorted result:", result)

Original data: [('Dengue', '54.865'), ('Malaria', '345.743'), ('Corona', '456.864'), ('Typhoid', '35.285'), ('Jaundice', '83.367')]
Sorted result: [('Corona', '456.864'), ('Malaria', '345.743'), ('Jaundice', '83.367'), ('Dengue', '54.865'), ('Typhoid', '35.285')]

Using sort() Method

The sort() method modifies the original list in-place, which is more memory-efficient for large datasets ?

def sort_in_place(data):
    data.sort(key=lambda item: float(item[1]), reverse=True)
    return data

# Sample data
data = [('638', '54.865'), ('932', '345.743'), ('256', '456.864'), 
        ('843', '35.285'), ('246', '83.367')]

print("Original data:", data)
sort_in_place(data)
print("After sorting:", data)

Original data: [('638', '54.865'), ('932', '345.743'), ('256', '456.864'), ('843', '35.285'), ('246', '83.367')]
After sorting: [('256', '456.864'), ('932', '345.743'), ('246', '83.367'), ('638', '54.865'), ('843', '35.285')]

Using Bubble Sort Algorithm

This approach implements bubble sort manually to demonstrate how sorting works at a lower level ?

# Sample data with actual float values
data = [('638', 54.865), ('932', 345.743), ('256', 456.864), 
        ('843', 35.285), ('246', 83.367)]

print("Original data:", data)

# Bubble sort implementation
length = len(data)
for i in range(length):
    for j in range(length - i - 1):
        if data[j][1] < data[j + 1][1]:  # Compare float values
            # Swap elements
            data[j], data[j + 1] = data[j + 1], data[j]

print("Sorted data:", data)

Original data: [('638', 54.865), ('932', 345.743), ('256', 456.864), ('843', 35.285), ('246', 83.367)]
Sorted data: [('256', 456.864), ('932', 345.743), ('246', 83.367), ('638', 54.865), ('843', 35.285)]

Comparison

Conclusion

Use sorted() when you need to preserve the original data, and sort() for in-place sorting. Both built-in methods are more efficient than manual implementations for production code.