Experiment–3

Lists in Python: Indexing, Slicing, and List Methods

Aim

To study Python lists and perform operations such as indexing, slicing, traversal, and manipulation using built-in list methods.

Objectives

• Create and access lists in Python
• Perform indexing and slicing operations
• Understand list mutability
• Apply commonly used list methods
• Traverse and modify list elements

Theory

1. Introduction to Lists

A list is a built-in data structure in Python used to store multiple values in a single variable. Lists are written using square brackets [], with elements separated by commas. Lists are dynamic, meaning their size can change during program execution.

2. Characteristics of Python Lists

Python lists have the following important properties:

• Ordered: Elements are stored in the order of insertion
• Indexed: Each element is associated with an index starting from 0
• Mutable: Elements can be changed, added, or removed
• Heterogeneous: Can store elements of different data types
• Allows Duplicates: Duplicate values are permitted

3. List Creation

Lists can be created using:

• Square brackets: list = [1, 2, 3]
• list() constructor
  Lists can also be nested, allowing lists inside other lists.

4. Indexing in Lists

Indexing allows access to individual elements of a list.

• Positive indexing: Starts from 0 (left to right)
• Negative indexing: Starts from -1 (right to left)

Indexing helps retrieve or update specific elements efficiently.

5. Slicing in Lists

Slicing is used to extract a portion (sublist) from a list.

Syntax:
list_name[start : end : step]

• start – starting index (included)
• end – ending index (excluded)
• step – interval between elements

Slicing does not alter the original list.

6. Mutability of Lists

Lists are mutable, meaning their contents can be modified after creation. This allows:

• Updating existing elements
• Adding new elements
• Removing unwanted elements

This property makes lists suitable for dynamic data storage.

7. List Traversal

List traversal refers to accessing each element of the list sequentially. It is commonly done using:

• for loop
• while loop

Traversal is useful for searching, updating, and processing list elements.

8. List Methods

Python provides built-in methods to manipulate lists, such as:

• append() – Adds element at the end
• insert() – Inserts element at a specific index
• remove() – Removes specified element
• pop() – Removes element by index
• sort() – Sorts elements
• reverse() – Reverses list order
• count() – Counts occurrences of an element
• index() – Returns index of an element

9. Built-in Functions for Lists

Common functions used with lists include:

• len() – Returns number of elements
• max() – Returns maximum value
• min() – Returns minimum value
• sum() – Returns sum of numeric elements

Applications / Programs Included

• Student marks management system
• Grocery shopping list
• Attendance register
• Mobile contact list
• Temperature analysis using slicing

Conclusion

Python lists are versatile data structures that support efficient storage and manipulation of data. Features like indexing, slicing, mutability, and built-in methods make lists essential for solving real-world programming problems.