This is a Cookiecutter template for creating a data analysis project
- Python 3.9
- Git integration
- Python preset functions
- Anaconda >= 4.x
- git >= 2.x
- Cookiecutter Python package >= 1.4.0:
You could install cookiecutter depending on how you manage your Python packages (pip or conda), follow the code below:
- pip:
pip install cookiecutter
- conda:
conda install -c conda-forge cookiecutter
├── README.md
├── cookiecutter.json
├── environment.yml
├── .gitignore
├── hooks
│ ├── pre_gen_project.py
│ └── post_gen_project.py
└── {{ cookiecutter.project_slug }}
├── LICENCE
├── README.md
├── environment.yml
├── .gitignore
├── data
│ ├── .gitkeep
├── notebooks
│ └── .gitkeep
In the directory that you create for the project, execute in terminal:
cookiecutter https://github.com/Pipe-Vash/cookiecutter-personal
This project was made it in base of:
- Platzi Configuración Profesional de Entorno de Trabajo para Ciencia de Datos course by Jesús Vélez Santiago
- Cookiecutter Data Science repository by Driven Data