{"id":24657713,"url":"https://github.com/nabilshadman/etl-python-sql-airflow","last_synced_at":"2026-05-06T23:42:51.979Z","repository":{"id":273503082,"uuid":"919922256","full_name":"nabilshadman/etl-python-sql-airflow","owner":"nabilshadman","description":"Build ETL pipelines using Python, Pandas, and SQL to extract, transform, and load data from sources, with exercises and job scheduling practices","archived":false,"fork":false,"pushed_at":"2025-01-21T09:19:39.000Z","size":427,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-21T04:15:01.127Z","etag":null,"topics":["airflow","data-engineering","data-pipeline","etl","python","sql"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/nabilshadman.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-01-21T08:56:08.000Z","updated_at":"2025-01-21T09:24:10.000Z","dependencies_parsed_at":"2025-01-21T10:24:31.324Z","dependency_job_id":"55d2462d-d4d4-4696-978f-a01032947abf","html_url":"https://github.com/nabilshadman/etl-python-sql-airflow","commit_stats":null,"previous_names":["nabilshadman/etl-python-sql-airflow"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/nabilshadman/etl-python-sql-airflow","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nabilshadman%2Fetl-python-sql-airflow","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nabilshadman%2Fetl-python-sql-airflow/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nabilshadman%2Fetl-python-sql-airflow/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nabilshadman%2Fetl-python-sql-airflow/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/nabilshadman","download_url":"https://codeload.github.com/nabilshadman/etl-python-sql-airflow/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nabilshadman%2Fetl-python-sql-airflow/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32716947,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-06T19:35:05.142Z","status":"ssl_error","status_checked_at":"2026-05-06T19:35:03.996Z","response_time":117,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["airflow","data-engineering","data-pipeline","etl","python","sql"],"created_at":"2025-01-26T00:34:00.974Z","updated_at":"2026-05-06T23:42:51.966Z","avatar_url":"https://github.com/nabilshadman.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ETL in Python and SQL\n\n## Course Overview\nThis repository contains the course materials for [**ETL in Python and SQL**](https://www.linkedin.com/learning/etl-in-python-and-sql/), taught by Jennifer Ebe, a data engineer with over 5 years of experience. The course is designed to help you build robust systems that gather, transform, and store data efficiently for actionable insights. It focuses on:\n\n- **Extracting Data**: Using Python to gather data from various sources.\n- **Transforming Data**: Leveraging tools like pandas and SQL to explore, clean, and standardize data.\n- **Loading Data**: Storing processed data in target systems.\n- **Scheduling Jobs**: Automating ETL workflows with Python.\n\nEach chapter includes hands-on challenges to reinforce learning through practical experience.\n\n---\n\n## Repository Structure\n\n```plaintext\netl-python-sql-airflow/\n├── Chapter_1/          # Introduction to ETL concepts and Python basics\n│   ├── *.ipynb         # Jupyter notebooks for code demonstrations\n│   └── sample_data.csv # Sample data for exercises\n├── Chapter_2/          # Extracting and transforming data\n│   ├── *.ipynb         # Notebooks for practical ETL tasks\n│   └── *.xlsx, *.csv   # Example datasets\n├── Chapter_3/          # Data validation and relational modeling\n│   └── *.ipynb         # Advanced ETL tasks and data checks\n├── Chapter_4/          # Scheduling and automation\n│   ├── *.ipynb         # Scheduling tutorials\n│   └── *.sh            # Shell scripts for job automation\n├── .git/               # Git repository metadata\n└── README.md           # Course overview and instructions\n```\n\n---\n\n## Getting Started\n\n### Prerequisites\n- Python 3.8+\n- Jupyter Notebook\n- pandas, openpyxl, and SQL-related libraries\n- Basic understanding of Python and SQL\n\n### Installation\n1. Clone this repository:\n   ```bash\n   git clone https://github.com/your-repo-url.git\n   ```\n2. Install dependencies:\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n### Running Notebooks\n1. Navigate to a chapter folder:\n   ```bash\n   cd Chapter_1\n   ```\n2. Open the desired notebook:\n   ```bash\n   jupyter notebook 01_03_end.ipynb\n   ```\n\n---\n\n## Course Content\n1. **Chapter 1**: Understanding ETL and exploring data with Python\n2. **Chapter 2**: Data extraction and transformation using pandas and SQL\n3. **Chapter 3**: Validating and modeling data in relational systems\n4. **Chapter 4**: Automating and scheduling ETL workflows\n\n---\n\n## License\nThis repository is for educational purposes only. All materials are copyrighted by Jennifer Ebe.\n\n--- \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnabilshadman%2Fetl-python-sql-airflow","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnabilshadman%2Fetl-python-sql-airflow","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnabilshadman%2Fetl-python-sql-airflow/lists"}