In Python, negative indexing lets you count backwards from the end of a list. So, -1 is the last item, -2 is the second to last, and so on. It’s like starting at the end of a line of people and moving backwards to find someone. Negative Indexing for Strings You can index single characters … Read more
Python Lists and 2D Arrays Understanding Python Lists Python lists are container data structures that allow you to store and manipulate collections of elements. Lists are created using square brackets [], and you can store any data type within a list, including numbers, strings, and even other lists. Here’s a simple Python list example: To … Read more
Python String Comprehension is a concise way to create strings using a single line of code, often involving iteration and optional conditionals, providing a succinct, readable alternative to using loops. It’s particularly useful for generating strings based on existing iterables. Here’s an example: In this example, the generator expression (fruit[0] for fruit in input_list if … Read more
When working with lists that contain Unicode strings, you may encounter characters that make it difficult to process or manipulate the data or handle internationalized content or content with emojis 😻. In this article, we will explore the best ways to remove Unicode characters from a list using Python. You’ll learn several strategies for handling … Read more
This article delves into the diverse methods of extracting values from Python’s Enum class. The Enum class in Python offers a platform to define named constants, known as enumerations. These enumerations can be accessed through various techniques: This article underscores the adaptability and multifaceted nature of the Enum class in Python, illustrating the myriad ways … Read more
Using heapq.nlargest() and heapq.nsmallest() is more efficient than sorting the entire list and then slicing it. Sorting takes O(n log n) time and slicing takes O(N) time, making the overall time complexity O(n log n) + O(N). However, heapq.nlargest() and heapq.nsmallest() have a time complexity of O(n log N), which is more efficient, especially when … Read more
Understanding zip() Function The zip() function in Python is a built-in function that provides an efficient way to iterate over multiple lists simultaneously. As this is a built-in function, you don’t need to import any external libraries to use it. The zip() function takes two or more iterable objects, such as lists or tuples, and … Read more
Understanding List Comprehension List comprehension is a concise way to create lists in Python. They offer a shorter syntax to achieve the same result as using a traditional for loop and a conditional statement. List comprehensions make your code more readable and efficient by condensing multiple lines of code into a single line. The basic … Read more
Understanding Functions in Python 💡 A Python function is a block of reusable code that performs a specific task. Functions help break your code into smaller, more modular and manageable pieces, which improves readability and maintainability. Python functions are defined using the def keyword, followed by the function’s name and a pair of parentheses containing … Read more
Understanding Collections.Counter Python’s Collections Module The collections module in Python contains various high-performance container datatypes that extend the functionality of built-in types such as list, dict, and tuple. These datatypes offer more specialized tools to efficiently handle data in memory. One of the useful data structures from this module is Counter. Counter Class in Collections … Read more
Problem Formulation Sorting a list of string numbers numerically in Python can lead to unexpected issues. For example, using the naive approach to sort the list lst = [“1”, “10”, “3”, “22”, “23”, “4”, “2”, “200”] using lst.sort() will result in the incorrect order as it sorts the list of strings lexicographically, not numerically. In … Read more
Basics of Sorting in Python In Python, sorting data structures like lists, strings, and tuples can be achieved using built-in functions like sort() and sorted(). These functions enable you to arrange the data in ascending or descending order. This section will provide an overview of how to use these functions. The sorted() function is primarily … Read more