Python Collections and Data Types

Introduction

• Overview of Python collections and how they handle data.

Key Concepts

Data Types in Python

• Python has various data types that can be used for collections.
• Common data types discussed:
  • Lists
  • Sets
  • Dictionaries

Lists

• Lists allow duplicate values.
• Elements can be accessed via index positions:
  • Example: Position 0 = first element, Position 1 = second element, etc.
• Methods discussed:
  • insert(index, value): Inserts a value at a specified index.
  • pop(): Removes and returns the last element (or a specific index if provided).
  • extend(): Adds elements from another collection to the list.

Sets

• Sets do not allow duplicate values.
• Duplicates are removed when a set is created.
• Elements can be added or removed, but sets themselves are immutable in terms of the original values present.
  • Example: {1, 2, 3, 4} will keep unique values only.

Dictionaries

• Dictionaries also do not allow duplicate keys.
• If a key is duplicated, the existing value will be overwritten.
• Syntax example: dict_name = {"key": "value"}.
• Useful for storing related data in key-value pairs.

Summary of Collections

• Practice using these collection types in Python.
• Understand the properties of each data type to choose the right one for specific use cases.