https://github.com/maxrdu/data-science-template
https://github.com/maxrdu/data-science-template
Last synced: 8 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/maxrdu/data-science-template
- Owner: maxrdu
- License: mit
- Created: 2022-09-27T16:34:34.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2022-09-27T16:44:04.000Z (over 3 years ago)
- Last Synced: 2025-10-13T03:35:33.280Z (8 months ago)
- Language: Python
- Size: 31.3 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
Data Science Template
=====================
A simple [cookiecutter](https://github.com/audreyr/cookiecutter) template for creating a modern (python) data science project.
## Features
- [Poetry](https://python-poetry.org) for dependency management
- [nbdime](https://nbdime.readthedocs.io) to easily version jupyter notebooks using git
- Commonly used packages like pandas, matplotlib, numpy and many more already included
- [pre-commit](https://pre-commit.com) hooks such as [isort](https://github.com/PyCQA/isort) and [black](https://github.com/psf/black) for consistent, PEP8 conform code style
## Getting started
Assuming you have [cookiecutter](https://github.com/audreyr/cookiecutter) and [poetry](https://python-poetry.org) already installed the setup is as simple as running the following line in your terminal:
```
cookiecutter gh:MushroomMaula/data-science-template
```
## Project structure
```
├─ LICENSE
├─ pyproject.toml 🠔 Configuration for poetry and other tools like black
├─ README.md 🠔 Information about your project
│
├── data
│ ├── interim 🠔 Intermediate data after some transformations have been
│ │ applied
│ ├── processed 🠔 Data after processing, ready to be used in your models
│ └── raw 🠔 The orginial data
│
├── docs 🠔 A folder to keep all your documentation about the project
│ └── references 🠔 Other reading material
│
├── models 🠔 Trained models, e.g. as serialized objects
│
├── notebooks 🠔 Jupyter notebooks
│ ├── exploratory 🠔 Notebooks that explore the data
│ └── reports 🠔 More polished notebooks ready to be exported
│
└── src
├── data 🠔 Scripts to generate/process your data
├── models 🠔 Scripts to train/create your models
└── utils 🠔 Other utilities e.g. visualizations
```