Python Datascience

Python is a simple, easy-to-learn programming language that’s perfect for beginners. It uses clean, readable syntax that feels like writing plain English, making it a great first language for anyone new to coding.

In the beginning, you’ll learn how to install Python on your computer, explore popular code editors like VS Code and PyCharm, and write your very first Python program.

You’ll also understand how Python code runs, how to use the Python interpreter, and get comfortable with basic tools that make coding fun and efficient.

This foundation sets you up for all the exciting things you’ll build with Python!

📚 Table of Contents

  1. Introduction to Python
  2. Basic Syntax and Operations
  3. Control Flow
  4. Data Structures
  5. Functions
  6. Object-Oriented Programming (OOP)
  7. File Handling
  8. Error Handling
  9. Modules and Packages
  10. Advanced Topics
  11. Data Science Libraries
  12. Web Scraping
  13. APIs and JSON
  14. Visual Studio Code
  15. Google Colab
  16. PIP and Virtual Environment
  17. Python Project 1: Personal Book Manager
  18. Python Project 2: Quote Data Explorer

1. Introduction to Python

  • Overview of Python
  • Installation and Setup
  • Python IDEs (PyCharm, VSCode, etc.)
  • Writing and Running Your First Python Program

2. Basic Syntax and Operations

  • Variables and Data Types
  • Basic Input and Output
  • Arithmetic, Comparison, and Logical Operators
  • Python Comments and Documentation

3. Control Flow

  • Conditional Statements (if, elif, else)
  • Looping Constructs (for, while)
  • break, continue, pass Statements

4. Data Structures

Lists

  • Creating, Accessing, and Modifying Lists
  • List Methods

Tuples

  • Differences between Lists and Tuples

Dictionaries

  • Key-Value Pairs, Common Methods

Sets

  • Creating Sets, Set Operations

5. Functions

  • Defining and Calling Functions
  • Function Arguments (positional, keyword, default)
  • Return Statements
  • Lambda Functions
  • Scope of Variables (local, global)

6. Object-Oriented Programming (OOP)

  • Introduction to Classes and Objects
  • Constructors and Destructors
  • Class and Instance Variables
  • Methods (instance, class, static)
  • Inheritance, Polymorphism, and Encapsulation
  • Magic Methods and Operator Overloading

7. File Handling

  • Reading and Writing Text Files
  • File Methods (open, read, write, close)
  • Working with CSV Files

8. Error Handling

  • Types of Errors (syntax, runtime)
  • Exception Handling (try, except, finally)
  • Custom Exceptions

9. Modules and Packages

  • Importing Built-in and External Modules
  • Creating Custom Modules
  • Package Structure and Importing

10. Advanced Topics

  • List Comprehensions
  • Generators and Iterators
  • Decorators
  • Context Managers (with statement)

11. Data Science Libraries

  • NumPy Basics
  • Pandas for Data Manipulation
  • Matplotlib for Basic Plotting

12. Web Scraping

  • Using BeautifulSoup and Requests
  • Extracting Data from HTML

13. APIs and JSON

  • Introduction to REST APIs
  • Making API Requests
  • Working with JSON Data

14. Visual Studio Code

  • Installing and Setting Up VS Code
  • Creating and Running Python Files
  • Visual Studio Code Plugins

15. Google Colab

  • What is Google Colab?
  • Using Google Colab for Python Programming
  • Uploading and Downloading Files
  • Running Code in the Cloud
  • Sharing and Collaboration Features

16. PIP and Virtual Environment

  • Introduction to pip
  • Installing Packages using pip
  • Upgrading and Uninstalling Packages
  • What is a Virtual Environment?
  • Creating a Virtual Environment with venv
  • Activating and Deactivating the Environment
  • Managing Dependencies with requirements.txt

Python Project 1: Personal Book Manager (CLI-Based)

🎯 Objective

Build a command-line Python application to manage a personal library of books.

📦 Concepts Covered

  • Variables, I/O, Lists, Dictionaries
  • Functions, File Handling
  • Exception Handling
  • CSV and JSON
  • Decorators, Generators
  • OOP (Optional)

🔧 Requirements

1. User Authentication

  • Accept username/password (hardcoded or stored)

2. Menu Options

  • Add, View, Search, Update, Delete, Export, Exit

3. Data Storage

books = [
    {"title": "Python 101", "author": "John Doe", "genre": "Education", "rating": 4.5},
]

4. File Handling

  • Load from JSON on start
  • Save to JSON on exit

5. Functions

  • Use a separate function for each operation

6. CSV Export

  • Use csv module

7. Optional OOP

  • Create a Book class

8. Bonus

  • Logging with decorators
  • Book generator

🧪 Sample Output

Welcome to Personal Book Manager!
1. Add Book
2. View All
3. Search
4. Update Rating
5. Delete Book
6. Export
7. Exit
Choose an option:

🧠 Python Project 2: Quote Data Explorer

🎯 Objective

Scrape quotes from the web and perform data analysis using Pandas and NumPy. This project blends web scraping with real-world data handling tasks.

📦 Concepts Covered

  • Web Scraping using requests, BeautifulSoup
  • DataFrames using Pandas
  • Array operations with NumPy
  • Data Filtering, Grouping, Transformation
  • File I/O (CSV and JSON)
  • Error Handling and Menu-driven CLI

🔧 Project Requirements

1. Data Source

2. Extracted Fields

For each quote, extract:

  • quote (text)
  • author
  • tags (comma-separated string or list)

3. Data Storage

  • Store data in a Pandas DataFrame
  • Each row should represent one quote
  • Columns: quote, author, tags

🗂️ Menu Options (CLI)

Welcome to Quote Data Explorer!
1. View Sample Data
2. Show Unique Authors
3. Filter by Author
4. Filter by Tag
5. Tag Frequency (Top N)
6. Export to CSV/JSON
7. Exit
Choose an option: