{"id":49570059,"url":"https://github.com/pfei/py-time-series","last_synced_at":"2026-05-03T13:14:30.252Z","repository":{"id":300180937,"uuid":"1004855337","full_name":"pfei/py-time-series","owner":"pfei","description":null,"archived":false,"fork":false,"pushed_at":"2025-06-20T09:10:04.000Z","size":91,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-20T09:28:56.530Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"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/pfei.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,"zenodo":null}},"created_at":"2025-06-19T09:31:33.000Z","updated_at":"2025-06-20T09:10:07.000Z","dependencies_parsed_at":"2025-06-20T09:30:50.802Z","dependency_job_id":"f2b1242f-a2d8-42e1-b6f6-95ca62c6407a","html_url":"https://github.com/pfei/py-time-series","commit_stats":null,"previous_names":["pfei/py-time-series"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/pfei/py-time-series","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pfei%2Fpy-time-series","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pfei%2Fpy-time-series/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pfei%2Fpy-time-series/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pfei%2Fpy-time-series/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pfei","download_url":"https://codeload.github.com/pfei/py-time-series/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pfei%2Fpy-time-series/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32570033,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-03T06:36:36.687Z","status":"ssl_error","status_checked_at":"2026-05-03T06:36:09.306Z","response_time":103,"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":[],"created_at":"2026-05-03T13:14:29.388Z","updated_at":"2026-05-03T13:14:30.243Z","avatar_url":"https://github.com/pfei.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# py-time-series: Probabilistic, Statistical, and Time Series Analysis Learning\n\nThis repository serves as a dedicated learning and development space for Python-based data analysis, with a strong focus on:\n\n- **Probabilistic and Statistical Methods:** Exploring core concepts, theoretical foundations, and practical implementations.\n- **Time Series Analysis (TSA):** Techniques for modeling, analyzing, and forecasting time-dependent data across various domains.\n- **Machine Learning Applications:** Implementing and understanding machine learning algorithms for diverse datasets.\n\nIt contains code examples, learning modules, and practical implementations inspired by academic texts, research, and real-world data across various fields. The aim is to build a robust collection of tools and insights for general data science and analytical studies.\n\n## Contents \u0026 Structure\n\n- `data/`: Contains raw and processed datasets used across various analyses and learning modules.\n  - `data/raw/jj_data.json`: An example dataset for Johnson \u0026 Johnson quarterly earnings, often used in time series analysis studies.\n- `src/`: Contains standalone Python scripts for common functions, utilities, and specific analysis tasks.\n- `notebooks/`: Houses Jupyter Notebooks that walk through different topics, concepts, and case studies.\n  - `notebooks/shumway_stoffer_fig1.1_p3.ipynb`: An initial example notebook demonstrating time series data loading, processing, and visualization for J\u0026J quarterly earnings.\n- `models/`: (Optional) Directory for saved machine learning models or model-related code.\n- `docs/`: (Optional) For project documentation, reports, or research notes.\n- `tests/`: Contains unit and integration tests to ensure code correctness and reliability.\n- `.vscode/`: VS Code specific settings for consistent development environment setup.\n- `mypy.ini`: MyPy configuration for strict static type checking.\n\n## Getting Started\n\n1.  Clone this repository:\n    `git clone https://github.com/your-username/py-time-series.git`\n2.  Navigate to the project directory:\n    `cd py-time-series`\n3.  Ensure your Python virtual environment is active (e.g., `source venvs/py-time-series/bin/activate`).\n4.  Install required dependencies (e.g., `pip install -r requirements.txt` - _you might need to create this file based on your project's dependencies_).\n5.  Explore the notebooks in the `notebooks/` directory or run scripts from `src/`.\n\n## Resources\n\n- **\"Time Series Analysis and Its Applications: With R Examples\"** by Robert H. Shumway and David S. Stoffer.\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpfei%2Fpy-time-series","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpfei%2Fpy-time-series","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpfei%2Fpy-time-series/lists"}