1. Adding Elements 2. Removing Elements 3. Accessing Elements 4. Sorting & Reversing 5. Copying & Joining 6. List Comparison & Operations Note: Python List copy() Method with Examples The copy() method in Python returns a shallow copy of a list. This means it creates a new list with the same elements as the original, but the new list…
In Python, lists are ordered, mutable collections that support various operations. Here are the key list operators along with four basic examples: List Operators in Python 4 Basic Examples 1. Concatenation (+) Combines two lists into one. python list1 = [1, 2, 3] list2 = [4, 5, 6] combined = list1 + list2 print(combined) # Output: [1, 2, 3,…
Negative slicing in Python lists lets you access elements from the end of the list. It’s a handy way to get a portion of a list without knowing its exact length. In negative slicing, you use negative numbers as indices. The index -1 refers to the last element, -2 to the second to last, and…
Indexing and Slicing for Writing (Modifying) Lists in Python Indexing and slicing aren’t just for reading lists – they’re powerful tools for modifying lists as well. Let’s explore how to use them to change list contents with detailed examples. 1. Modifying Single Elements (Indexing for Writing) You can directly assign new values to specific indices. Example 1:…
Indexing and Slicing in Python Lists Read Indexing and slicing are fundamental operations to access and extract elements from a list in Python. 1. Indexing (Accessing Single Elements) Example 1: Basic Indexing python fruits = [“apple”, “banana”, “cherry”, “date”, “fig”] # Positive indexing print(fruits[0]) # “apple” (1st element) print(fruits[2]) # “cherry” (3rd element) # Negative indexing print(fruits[-1]) # “fig”…
Linear vs. Scalar Data Types in Python In programming, data types can be categorized based on how they store and organize data. Two important classifications are scalar (atomic) types and linear (compound) types. 1. Scalar (Atomic) Data Types 2. Linear (Compound/Sequential) Data Types Key Differences Between Scalar and Linear Data Types Feature Scalar (Atomic) Linear (Compound) Stores Single…
In Python, there are multiple ways to create lists, depending on the use case. Below are the most common methods: 1. Direct Initialization (Using Square Brackets []) The simplest way to create a list is by enclosing elements in square brackets []. Example: python empty_list = [] numbers = [1, 2, 3, 4] mixed_list = [1, “hello”, 3.14,…
In Python, a list is a built-in data structure that represents an ordered, mutable (changeable), and heterogeneous (can contain different data types) collection of elements. Lists are one of the most commonly used data structures in Python due to their flexibility and dynamic nature. Definition of a List in Python: Example: python my_list = [1, “hello”, 3.14,…
C-Style String Formatting in Python Python supports C-style string formatting using the % operator, which provides similar functionality to C’s printf() function. This method is sometimes called “old-style” string formatting but remains useful in many scenarios. Basic Syntax python “format string” % (values) Control Characters (Format Specifiers) Format Specifier Description Example Output %s String “%s” % “hello” hello %d…
The print() Function in Python: Complete Guide The print() function is Python’s built-in function for outputting data to the standard output (usually the console). Let’s explore all its arguments and capabilities in detail. Basic Syntax python print(*objects, sep=’ ‘, end=’\n’, file=sys.stdout, flush=False) Arguments Explained 1. *objects (Positional Arguments) The values to print. You can pass multiple items separated by commas. Examples:…