https://github.com/icoxfog417/datascience-template

Data science project template
https://github.com/icoxfog417/datascience-template

amazon-sagemaker-lab datascience jupyter-notebook machine-learning

Last synced: 4 months ago
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Data science project template

• Host: GitHub
• URL: https://github.com/icoxfog417/datascience-template
• Owner: icoxfog417
• License: mit
• Created: 2022-08-11T01:42:26.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-12-08T00:56:38.000Z (about 2 years ago)
• Last Synced: 2024-04-15T12:50:35.549Z (10 months ago)
• Topics: amazon-sagemaker-lab, datascience, jupyter-notebook, machine-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 20.5 KB
• Stars: 19
• Watchers: 3
• Forks: 4
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# datascience-template

[![Source Code Check](https://github.com/icoxfog417/datascience-template/actions/workflows/ci.yml/badge.svg)](https://github.com/icoxfog417/datascience-template/actions/workflows/ci.yml)

[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

[![Code style: flake8](https://img.shields.io/badge/code%20style-flake8-black)](https://github.com/PyCQA/flake8)

[![Imports: isort](https://img.shields.io/badge/%20imports-isort-%231674b1?style=flat&labelColor=ef8336)](https://pycqa.github.io/isort/)

[![Typing: mypy](https://img.shields.io/badge/typing-mypy-blue)](https://github.com/python/mypy)

Well structured and tested data science project template. You can use this [template](https://docs.github.com/ja/repositories/creating-and-managing-repositories/creating-a-repository-from-a-template) when creating the data sicence repository.

📁 **Organized**: The project structure is refereed to [Cookiecutter Data Science](https://github.com/drivendata/cookiecutter-data-science)

🚀 **Prepared**: Major libraries are prepared in `environment.yml`. If you are familiar with [Colaboratory](https://colab.research.google.com/?utm_source=scs-index) environment, please use `environment-colab.yml` .

✅ **Tested**: `scripts` are checked by common linter when [pre-commit](https://pre-commit.com/).

Here is the notebook link to provide the quick access to your analysis. You can create the conda environment by Right click `Build Conda Environment` or `conda create -f environment.yml` in Studio Lab.

[![Open in SageMaker Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/icoxfog417/datascience-template/blob/main/notebooks/example.ipynb)

## Project Structure

```bash

.

├── data

│   ├── external                    # data from third party sources.

│   ├── processed                   # data after processing

│   ├── interim                     # data that transformed

│   └── raw                         # raw data

├── models                          # store models

├── notebooks                       # store notebooks

├── docs                            # documentation for your project

├── .gitignore                      # ignore files that cannot commit to Git

├── .pre-commit-config.yaml         # configurations for pre-commit

├── pyproject.toml                  # dependencies for poetry

├── README.md                       # describe your project

├── scripts                         # store source code used in notebook

│   └── __init__.py                 # make src a Python module

└── tests                           # store tests

    └── __init__.py                 # make tests a Python module

```

## Customization

* `environment.yml`: Please specify the packages and versions. As a default, no version is specified.

* `.pre-commit-config.yaml`: Please check the `rev` to check the code.

* Change the Notebook url for `Open in Studio Lab`.