2D Collections in Python

Overview

• 2D collections represent data in a grid or matrix format (e.g., like an Excel spreadsheet).
• Mainly involves working with 2D lists, but can include 2D tuples and sets.

2D Lists

• A 2D list is a list made up of lists.
• Useful for organizing data into rows and columns.

Creating a 2D List

1. One-dimensional lists: Start with individual lists, e.g., fruits, vegetables, meats.
2. Combine into a 2D list: Add these lists as elements within an outer list, forming a 2D structure.

Accessing Elements

• Single index: Returns an entire row (e.g., groceries[0] returns the 'fruits' list).
• Double index: Access specific elements (like coordinates), e.g., groceries[0][0] for 'apple'.

Printing a 2D List

• Printing directly displays the entire structure with inner lists separated by commas.
• Align elements to mimic a grid structure with rows and columns.

Modifying a 2D List

• Indices allow modification of specific elements.

Iterating Over a 2D List

• Nested loops: Use to iterate through rows and elements within each row. for collection in groceries: for food in collection: print(food, end=' ') print() # For new line after each row

Other 2D Collections

• 2D Tuples: Tuples made up of tuples; immutable and ordered.
• 2D Sets: Not typically used since sets are unordered.

Example: 2D Tuple for a Phone Keypad

1. Define a 2D tuple named numpad.
2. Structure:
   • ((1, 2, 3), (4, 5, 6), (7, 8, 9), ('*', 0, '#'))
3. Iterate over with loops to print in a grid format.*

Conclusion

• 2D collections are versatile for organizing and accessing data in a structured format.
• Understanding these fundamentals helps in effectively managing data in programming tasks.

Note: Choose between lists, tuples, or sets based on the data requirements, such as order and mutability.