A structured Python learning portfolio — from language fundamentals to applied data analytics.
| Module | Description |
|---|---|
01-python-fundamentals/ |
Core language concepts through exercises and a CLI project |
02-data-analytics/ |
Applied data analytics from library basics to structured, evidence-aware analysis |
Eleven focused exercises covering the core Python language, followed by a standalone command-line project.
| Component | Contents |
|---|---|
exercises/ |
Output formatting · variables · types · strings · control flow · validation · data structures |
project/dataset-summary/ |
CLI tool for CSV structural inspection — standard library only |
→ 01-python-fundamentals/README.md
Applied analytics centered on the 2023 Data Jobs dataset, progressing from library fundamentals to an evidence-aware multi-notebook study.
| Component | Contents |
|---|---|
exercises/ |
Role matching and type conversion in pure Python |
notebooks/ |
Pandas and Matplotlib basics, then demand, trend, and compensation analysis for Germany |
project/job-market-analysis/ |
Five-notebook structured analysis of India's data-job market |
python-learning/
├── 01-python-fundamentals/
│ ├── exercises/ # 11 exercises covering core language concepts
│ ├── project/
│ │ └── dataset-summary/ # CSV inspection CLI tool
│ └── README.md
├── 02-data-analytics/
│ └── data-jobs-analysis/
│ ├── exercises/ # 2 exercises covering data-oriented Python
│ ├── notebooks/ # 5 analysis notebooks + figures
│ ├── project/
│ │ └── job-market-analysis/ # 5-notebook India market analysis
│ └── README.md
├── .gitattributes
├── .gitignore
├── LICENSE
├── README.md
└── requirements.txt
pip install -r requirements.txtModule 01 uses the standard library only. Module 02 requires datasets · pandas · matplotlib · numpy · seaborn.
This repository is licensed under the MIT License.