🐍 Python Learning Repository

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📌 Overview

This repository documents my Python learning journey, covering:

• 🧠 Core Python fundamentals (learned primarily from Apna College)
• 📊 Popular Python libraries for data analysis and visualization
• 📓 Extensive Jupyter notebooks used as structured notes + hands-on practice
• 🛠️ Mini projects for applying concepts in real-world scenarios

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The goal of this repo is to act as:

• A personal reference for revision
• A practice playground for concepts
• A showcase of consistency through my #100DaysOfCode journey

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🎯 Goals of This Repository

• Build a strong foundation in Python
• Develop problem-solving skills
• Learn data analysis & visualization libraries deeply
• Maintain structured notes for revision
• Track progress through #100DaysOfCode
• Create a reusable learning reference

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🔗 Related Repository: AI / ML & Data Science

I am also actively learning AI, Machine Learning, and Data Science from Apna College. All advanced AI/ML concepts, notebooks, and practice related to that journey are maintained separately here:

👉 AI / ML & Data Science Repository 🔗 https://github.com/TonyStark-19/AI-ML-DataScience

This Python repository focuses on foundations + data handling + visualization, while the linked repo dives deeper into AI/ML models, math, and applied data science workflows.

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📊 Repository Statistics

Category	Count
🧾 Total Python Programs	100
📓 Total Jupyter Notebooks	28
📁 Mini Projects	3
📦 Core Python Topics	11+
📈 Libraries Covered	4 major libraries

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🔹 Core Python Concepts

Topic	Contents
Basic Questions	13 beginner-level Python programs
Conditional Statements	9 programs (if-else, nested conditions, logical operators)
Loops	8 programs (for, while, loop-based problems)
Strings	6 programs + 1 notebook (string methods & manipulation notes)
Lists	7 programs + 1 notebook (lists, methods & comprehensions)
Tuples	3 programs + 1 notebook (tuple properties & use-cases)
Sets	4 programs + 1 notebook (set operations & applications)
Dictionaries	4 programs + 1 notebook (dictionary operations & methods)
Functions & Recursion	14 programs (functions, parameters, recursion problems)
File I/O	7 programs (reading/writing files & handling file types)
OOPS	17 programs + 1 notebook (classes, objects, inheritance, etc.)

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⚙️ Practical Python Concepts

📦 Exception Handling

• Covers common runtime errors
• Proper use of try, except, else, and finally
• 2 dedicated topics with examples

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🗂️ Working with JSON

• 3 Python programs
• 3 JSON files for practice
• Parsing, reading, writing, and manipulating JSON data

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🔹 Data Handling & Thinking in Data

This section focuses on understanding and working with data before using heavy libraries.

• 📡 Data Collection using APIs – 1 notebook (notes + examples)
• 🌐 Web Scraping – 1 notebook (concepts & notes) + 1 practice notebook
• 🧠 Thinking in Data (Plain Python) – 1 notebook focused on data understanding using core Python

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🔹 Python Libraries

🔢 NumPy

• 1 notebook → NumPy notes & fundamentals

• 4 notebooks → Level-wise NumPy concepts (Level 1 to 4)

• NumPy-100 Exercises:

  • Level 1 – 1 notebook
  • Level 2 – 1 notebook

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🐼 Pandas

• 1 notebook → Pandas notes
• 1 notebook → Series deep dive
• 1 notebook → DataFrame deep dive

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📈 Matplotlib

• 1 notebook → Matplotlib notes

• 3 notebooks →

  • Univariate Analysis
  • Bivariate Analysis
  • Multivariate Analysis

• 1 notebook → Object-Oriented (OO) API

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🎨 Seaborn

• 1 notebook → Seaborn notes
• 2 notebooks → Deep dive into Seaborn plots & visualizations

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🔹 Projects

• Mini Python Projects

  • 3 small projects focused on applying Python concepts practically

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📸 Visualizations Preview

Some examples of work in this repo:

Matplotlib plots:

Line Chart	Box Plot

Bar Plot	Bubble Plot

Multiple Datasets Line Chart	3D Plot

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Seaborn plots:

Scatter Plot	Sworm Plot

Line Plot	Violin Plot

Heat Map	Pair Grid

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🚀 Technologies Used

• Python 3.x

• Jupyter Notebook

• Libraries:

  • numpy
  • pandas
  • matplotlib
  • seaborn

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🔧 Requirements

Install required libraries with:

pip install -r requirements.txt

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📘 How to Use

1. Clone the repository:

   https://github.com/TonyStark-19/Python-coding.git

2. Navigate into the repository:

   cd Python-coding

3. Open Jupyter Notebook to explore:

   jupyter notebook

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📚 Resources

• Python Tutorial by Apna College
• Numpy Tutorial by Chai or Code
• Pandas Tutorial by Intellipaat
• MatplotLib Tutorial by Intellipaat
• Seaborn Tutorial by Intellipaat

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🤝 Contributions

This repository is mainly for personal learning and documentation, but:

• Suggestions
• Improvements
• Pull Requests

are always welcome 🙂

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⭐ Acknowledgements

• Apna College for structured Python fundamentals
• Open-source community & documentation
• Everyone sharing knowledge through blogs, videos & tutorials

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📜 License

This project is licensed under the MIT License. Feel free to use, modify, and share it – just give proper credit. Check the LICENSE file for more details.

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✨ If you find this repo useful, consider giving it a star! ⭐