Python Lecture Notes

Introduction to Arrays

• Arrays allow us to store multiple values in a single variable.
• We have learned how to:
  • Insert values
  • Fetch values

Types of Arrays

1. Single Dimensional Array

   • One row and multiple columns.
   • Example: [1, 2, 3, 4]

2. Multi-Dimensional Array

   • Multiple rows and multiple columns.
   • Examples:
     • 2D Array: Used for matrices.
     • 3D Array: Can be visualized like a cube.
     • Higher dimensions.

Multi-Dimensional Arrays in Python

• Standard Python array does not support multi-dimensional arrays out-of-the-box.
• Example: Attempting multi-dimensional arrays with the array module results in errors.

Introduction to NumPy

• NumPy is a third-party library that supports multi-dimensional arrays.
• Use the command pip install numpy to install NumPy.

Installing NumPy

1. Command Prompt:

   • Use pip install numpy.
   • Make sure it displays numpy successfully installed.
   • Confirm by importing NumPy in Python shell: import numpy

2. IDE Specific Installation:

   • PyCharm:
     • Go to Settings (Ctrl + Alt + S).
     • Select Project Interpreter.
     • Search for and install NumPy.

Working with NumPy

• Importing NumPy: import numpy as np
• Creating Arrays:
  • Single Dimensional: arr = np.array([1, 2, 3])
  • Multi-Dimensional: arr = np.array([[1, 2, 3], [4, 5, 6]])
• Type specification (optional): arr = np.array([1, 2, 3], dtype=int)

Summary

• NumPy is essential for working with multi-dimensional arrays in Python.
• Installation and setup are straightforward via pip and IDE settings.
• Upcoming topics will cover more advanced NumPy operations and use-cases.

Please leave your comments and hit the like button if you enjoyed the lecture!

---

Instructor: Ivan Ready