Python Learning

A personal workspace containing Python exercises, notebooks, and data analysis projects focused on visualization, machine learning, and data science with Python.

Contents

• Data Analysis Projects: COVID-19 data, Democracy Index, Formula1, Spotify analytics, London/House price data
• Learning Projects: Football Match database, OOP practice, network programming
• Notebooks: JupyterNotebooks and comprehensive course materials (Py_DS_ML_Bootcamp-master)
• Practice Scripts: Python basics and small examples
• Data Visualization: Seaborn, Matplotlib, and Pandas plotting examples

Repository structure

Data Analysis Projects

• Covid19/ — COVID-19 data analysis and visualizations
• Democracy/ — Global democracy index analysis with correlation heatmaps and KDE plots
• Formula1/ — Formula 1 racing data exploration
• Spotify/ — Spotify track data processing and analysis
• London_House/ — London housing market data
• house/ — Housing price analysis

Learning & Practice Projects

• Footbal_Match/ — Database project with SQLite; see README.md inside
• PracticeOOP/ — Object-oriented programming exercises
• LearningNetworkwithpy/ — Network programming practice
• Project1/ — General project exercises

Course Materials & Notebooks

• Py_DS_ML_Bootcamp-master/ — Complete data science bootcamp material (NumPy, Pandas, ML, NLP, Deep Learning)
• JupyterNotebooks/ — Daily exercises and lesson notebooks
• data_visualization/ — Seaborn and Pandas visualization exercises

Scripts & Utilities

• Python/ — Python basics practice scripts (day2.py, day3.py, decorators, file I/O, etc.)
• dotenv/ — Environment variable practice
• test.py — Quick testing script

Getting started

1. Clone the repository:

git clone https://github.com/MUHAMMEDQULIYEV/Python_Learning.git
cd Python_Learning

2. Set up Python environment:

python3 -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Run notebooks or scripts:

# Launch Jupyter
jupyter notebook

# Or run individual scripts
python Python/day2.py
python Footbal_Match/main.py

Key Projects

Data Analysis

• Democracy Index (Democracy/) — Analyze global democracy trends with pandas and seaborn
• Spotify Analytics (Spotify/) — Track data processing, correlation analysis, duration metrics
• COVID-19 Analysis (Covid19/) — Pandemic data visualization and insights
• Formula 1 (Formula1/) — Racing statistics and performance analysis
• Housing Data (London_House/, house/) — Real estate price analysis

Database Projects

• Football Match (Footbal_Match/) — SQLite database with match tracking (see project README)

Technologies & Libraries

• Data Analysis: pandas, numpy
• Visualization: seaborn, matplotlib, plotly
• Machine Learning: scikit-learn (in bootcamp materials)
• Database: SQLite
• Deep Learning: TensorFlow/Keras (in course materials)
• NLP & Big Data: NLTK, Spark (in advanced sections)

Jupyter Notebooks

The repository contains extensive notebook collections:

• JupyterNotebooks/ — daily exercises and progressive learning
• Py_DS_ML_Bootcamp-master/ — comprehensive bootcamp covering:
  • Python fundamentals
  • NumPy and Pandas
  • Data visualization (Matplotlib, Seaborn, Plotly)
  • Machine learning algorithms
  • Deep learning and neural networks
  • Natural language processing
  • Big data with Spark

Learning Path

1. Basics → Python/ scripts + JupyterNotebooks/
2. Data Analysis → Pandas exercises in Py_DS_ML_Bootcamp-master/03-Python-for-Data-Analysis-Pandas/
3. Visualization → data_visualization/ + bootcamp visualization sections
4. Projects → Democracy, Spotify, COVID-19, Formula1 analyses
5. Advanced → Machine learning and deep learning in bootcamp materials

Notes

• Personal learning repository tracking progress in data science and Python
• Most projects include exploratory data analysis (EDA) and visualizations
• Datasets included or referenced in project folders
• Many notebooks contain exercises with solutions

Contact

If you want help improving this repository (formatting, dependency management, CI), open an issue or ask for a review.

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Generated/updated by repository maintainer.