Overview

In this unit, you’ll discover how Python handles structured data using built-in and library-based object types. You will explore different ways to store multiple values efficiently and work with them effectively.

📘 Topics

• Lists
  Flexible, ordered collections that can hold multiple data types.

• Arrays
  Homogeneous sequences of numbers, optimized for performance via numpy.

• Data Frames
  Table-like objects from pandas, perfect for structured and labeled data.

• Matrices
  2D numeric data structures, often used in scientific computing.

🎯 Learning Goal

You will be able to create, access, and manipulate structured collections of data using Python lists, DataFrames, matrices, and arrays. You’ll also understand when to use each type based on the nature of your data and the task at hand.