Add README, environment files, CI workflow, CONTRIBUTING and Code of Conduct

Author: ccleberg

README.md

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+# audit-labs/tutorials
+
+Learn how to perform data analysis, scripting, automation, and more using reproducible Jupyter Notebooks.
+
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/audit-labs/tutorials/HEAD)
+[![Notebooks](https://img.shields.io/badge/notebooks-Jupyter-orange.svg)]()
+[![License](https://img.shields.io/badge/license-GPLv3-blue.svg)]()
+
+Table of contents
+- [Project overview](#project-overview)
+- [Who this is for](#who-this-is-for)
+- [What's included](#whats-included)
+- [Getting started](#getting-started)
+  - [Prerequisites](#prerequisites)
+  - [Quick start — using Binder (no local setup)](#quick-start---using-binder-no-local-setup)
+  - [Run locally (recommended)](#run-locally-recommended)
+  - [Run in Google Colab](#run-in-google-colab)
+  - [Run with Docker](#run-with-docker)
+  - [Run headless / export notebooks](#run-headless--export-notebooks)
+- [Best practices for notebooks](#best-practices-for-notebooks)
+- [Contributing](#contributing)
+- [License & Code of Conduct](#license--code-of-conduct)
+- [Contact / Support](#contact--support)
+
+## Project overview
+This repository contains interactive tutorials and example notebooks designed to teach practical skills in data analysis, scripting, automation, and related topics using Jupyter Notebooks. Each notebook demonstrates concepts through hands-on examples so you can follow along and adapt the patterns to your own projects.
+
+## Who this is for
+- Data analysts and engineers learning reproducible workflows.
+- Developers who want to prototype automation or analysis in notebooks.
+- Students and instructors seeking ready-made examples for teaching.
+
+## What's included
+- A collection of Jupyter Notebook tutorials (look in the repository root or `notebooks/` folder for .ipynb files).
+- Guidance and examples that demonstrate common patterns for data ingestion, transformation, visualization, and basic automation.
+
+(If your repo has a specific folder layout or important notebooks, consider adding a short list here with links to the most important notebooks.)
+
+## Getting started
+
+### Prerequisites
+- Python 3.10+ (3.10 recommended)
+- Git (to clone the repo)
+- JupyterLab or Jupyter Notebook (for local development)
+
+Optional:
+- Conda (recommended for reproducible environments)
+- Docker (for containerized runs)
+
+This repository is licensed under the GNU General Public License v3.0 (GPL-3.0). See the included LICENSE file for details.
+
+### Quick start — using Binder (no local setup)
+To run the notebooks in your browser with no local install, use Binder:
+
+- Launch Binder: https://mybinder.org/v2/gh/audit-labs/tutorials/HEAD
+
+Binder will respect `environment.yml` or `requirements.txt` if present; this repository includes an `environment.yml` to produce a reproducible environment.
+
+### Run locally (recommended)
+
+1. Clone the repository
+   ```bash
+   git clone https://github.com/audit-labs/tutorials.git
+   cd tutorials
+   ```
+
+2. Create and activate an environment
+
+   Using conda (recommended):
+   ```bash
+   conda env create -f environment.yml
+   conda activate audit-tutorials
+   ```
+
+   Or with pip and virtualenv:
+   ```bash
+   python -m venv venv
+   source venv/bin/activate   # macOS / Linux
+   venv\Scripts\activate      # Windows
+   pip install --upgrade pip
+   pip install -r requirements.txt
+   ```
+
+3. Install JupyterLab (if not already)
+   ```bash
+   pip install jupyterlab
+   jupyter lab
+   ```
+   Or run the classic notebook server:
+   ```bash
+   jupyter notebook
+   ```
+
+4. Open the notebooks in the browser and follow the cells.
+
+### Run in Google Colab
+To open a notebook in Colab:
+- Navigate to the notebook file on GitHub, then use "Open in Colab" or open via:
+  https://colab.research.google.com/github/audit-labs/tutorials/blob/HEAD/path/to/notebook.ipynb
+- Colab will run in the cloud; you may need to pip-install extra dependencies at the top of the notebook using `!pip install ...`.
+
+### Run with Docker
+You can run the notebooks inside a Docker container using Jupyter's base images:
+```
+docker run -p 8888:8888 -v "$(pwd)":/home/jovyan/work jupyter/base-notebook:latest
+```
+Then open `http://localhost:8888` and navigate to `work/`.
+
+### Run headless / export notebooks
+To execute notebooks and export them programmatically:
+```
+pip install nbconvert nbclient
+jupyter nbconvert --to html --execute path/to/notebook.ipynb
+```
+This is useful for CI pipelines and automated report generation.
+
+## Best practices for notebooks
+- Keep notebooks focused: one concept or analysis per notebook.
+- Include a short README or top-level markdown cell describing purpose and inputs.
+- Avoid long-running data downloads inside notebooks—prefer referencing local sample data or scripts.
+- Use version control: commit notebooks regularly. Consider tools like `nbstripout` or `nbdime` to manage diffs.
+- Parametrize notebooks for reproducibility (e.g., use papermill for parameterized runs).
+
+## Contributing
+See CONTRIBUTING.md for contribution guidelines.
+
+## License & Code of Conduct
+This project is licensed under the GNU General Public License v3.0 (GPL-3.0). See [LICENSE](./LICENSE) for details.
+
+Please review CODEOFCONDUCT.md for expected behavior when contributing.
+
+## Contact / Support
+For questions or help, open an issue in this repository or contact the maintainers listed in the repository settings.
+
+---