Given a list of float values, write a Python program to sort the list.
Examples:
Input: list = ['1.2', '.8', '19.8', '2.7', '99.8', '80.7'] Output: ['.8', '1.2', '2.7', '19.8', '80.7', '99.8'] Input: list = [12.8, .178, 1.8, 782.7, 99.8, 8.7] Output: [0.178, 1.8, 8.7, 12.8, 99.8, 782.7]
Let’s discuss different ways to solve this problem.
Method #1 :Using lambda
Python3
# Python code to sort list of decimal values# List initializationInput = [12.8, .178, 1.8, 782.7, 99.8, 8.7]# Using sorted and lambdaOutput = sorted(Input, key = lambda x:float(x))# Printing outputprint(Output) |
[0.178, 1.8, 8.7, 12.8, 99.8, 782.7]
Time complexity: The time complexity of this code is O(n log n), where n is the number of elements in the input list.
Auxiliary space: The auxiliary space used by this code is O(n), where n is the number of elements in the input list.
Method #2 : Using sorted
Python3
# Python code to sort list of decimal values# List initializationInput = [12.8, .178, 1.8, 782.7, 99.8, 8.7]# Using sorted + keyOutput = sorted(Input, key = float)# Printing outputprint(Output) |
[0.178, 1.8, 8.7, 12.8, 99.8, 782.7]
Time complexity: The time complexity of this code is O(n log n), where n is the number of elements in the input list.
Auxiliary space: The auxiliary space used by this code is O(n), where n is the number of elements in the input list.
Method #3 : Using sort
Python3
# Python code to sort list of decimal values# List initializationInput = [12.8, .178, 1.8, 782.7, 99.8, 8.7]# Using sort + keyInput.sort(key = float)# Printing outputprint(Input) |
[0.178, 1.8, 8.7, 12.8, 99.8, 782.7]
METHOD 3: we can use bubble sort algorithm.
This implementation iterates through the list multiple times, comparing adjacent elements and swapping them if they are in the wrong order. It repeats this process until the list is fully sorted.
Python3
# List initializationInput = [12.8, .178, 1.8, 782.7, 99.8, 8.7]# Bubble sort algorithmn = len(Input)for i in range(n): for j in range(0, n-i-1): if Input[j] > Input[j+1]: Input[j], Input[j+1] = Input[j+1], Input[j]# Printing outputprint(Input) |
[0.178, 1.8, 8.7, 12.8, 99.8, 782.7]
Time complexity: O(n^2) in the worst case, where n is the length of the list.
Auxiliary space: O(1), which means it does not require any extra memory beyond the input list.
Method #4: Using numpy.sort
This method involves using the numpy library’s sort() function to sort the list of float values. It takes in the list as an argument and returns a sorted numpy array.
Algorithm:
Import the numpy library
Initialize the input list
Convert the input list to a numpy array using np.array()
Sort the numpy array using np.sort()
Convert the sorted numpy array back to a list using .tolist()
Print the sorted list
Python3
# importing numpy libraryimport numpy as np # List initializationInput = [12.8, .178, 1.8, 782.7, 99.8, 8.7] # Converting list to numpy array and sortingsorted_array = np.sort(np.array(Input)) # Converting sorted numpy array to listsorted_list = sorted_array.tolist() # Printing outputprint(sorted_list) |
Output:
[0.178, 1.8, 8.7, 12.8, 99.8, 782.7]
Time complexity: The time complexity of this code is O(n log n), where n is the number of elements in the input list. This is because the np.sort() function uses a quicksort algorithm by default.
Auxiliary space: The auxiliary space used by this code is O(n), where n is the number of elements in the input list. This is because the np.array() function creates a new numpy array and the .tolist() function creates a new list.
