5 Free Templates for Data Science Projects on Jupyter Notebook
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For many professional data scientists, Jupyter Notebook has become their staple working environment. Even for me, it’s always the first place I go to for any data science experiment and workflow.
As a data scientist workplace, Jupyter Notebook is a unique IDE as the code can be executed independently in each cell. At the same time, the author could explain each cell. This distinction allows the notebook to be reused by others and become a project template.
In this article, we will discuss five free templates for building a data science project on Jupyter Notebook. So, what are these Jupyter Notebook templates? Let’s get into them.
1. Cookiecutter Template for Python Data Science Projects
The first template that we discuss is not necessarily a complete code project that we can fill in already. The template we would discuss is not only the Jupyter Notebook but also complete projects that support the Jupyter Notebook. What we would have is the Python data science projects by AWS.
This template creates a complete data science project structure that is ready to be used for your actual project. Using Cookiecutter CLI, you can generate the directory structure of the data science projects, which is similar to the structure below.
|-- bin/
|-- notebooks # A directory to place all notebooks files.
| |-- *.ipynb
| `-- my_nb_path.py # Imported by *.ipynb to treat src/ as PYTHONPATH
|-- requirements/
|-- src
| |-- my_custom_module # Your custom module
| |-- my_nb_color.py # Imported by *.ipynb to colorize their outputs
| `-- source_dir # Additional codes such as SageMaker source dir
|-- tests/ # Unit tests
|-- MANIFEST.in # Required by setup.py (if module name specified)
|-- setup.py # To pip install your Python module (if module name specified)
# These sample configuration files are auto-generated too:
|-- .editorconfig # Sample editor config (for IDE / editor that supports this)
|-- .gitattributes # Sample .gitattributes
|-- .gitleaks.toml # Sample Gitleaks config (if pre_commit is advanced)
|-- .gitignore # Sample .gitignore
|-- .pre-commit-config.yaml # Sample precommit hooks
|-- LICENSE # Boilperplate (auto-generated)
|-- README.md # Template for you to customize
|-- pyproject.toml # Sample configurations for Python toolchains
`-- tox.ini # Sample configurations for Python toolchains
If you are interested in how the template is applied to a real project, check its actual usage above this Reinforcement Learning Energy Storage use case.
2. Data Science Notebooks Templates by Coen Meintjes
The next Jupyter Notebook template we will discuss is the one by Coen Meintjes. It is a basic Jupyter Notebook collection from Data Exploration to Model Evaluation. It’s not a project-specific kind of template; in fact, it mostly consists of the essential code, nothing more. But I would say it is good. Why is that?
It’s a basic template that everyone can use for different kinds of projects with little tweaks. You can use this Jupyter Notebook template to develop any project idea. Moreover, the templates here explain in depth many of the processes in the notebook, so any beginner or professional could benefit from them.
3. Data Science Projects by Yusuf Cinarci
Let’s move on to a more project-specific template, the Data Science Projects Jupyter Notebook templates by Yusuf Cinarci. In these templates, you can use them to develop simple projects for your portfolio or any business needs.
There are many project templates you can choose from. You can choose from simple Salary Data Exploration with Python to the development of a Fake News Detection and Movie Recommendation System. The notebook is perfect for you who want to kickstart your projects easily.
What I like about the Yusuf Cinarci template collections is that they are not overly complicated, so beginners can start their projects when they learn about data science. However, many of the projects are for beginners, so they might lack data science projects if you are looking for one.
4. Data Science Projects by Sukman Singh
If you need a more complex project Jupyter Notebook template, then the Data Science Projects Jupyter Notebook template by Sukman Singh could be the one for you. It’s perfect for those who want to develop prediction models easily but need inspiration for their ideas.
The template collection contains many data science project templates, including customer churn prediction, loan approval prediction, and claim fraud projects. These are standard business projects that you can use to enrich your data project portfolio.
The project might seem one-dimensional, but you can extend the project as well. It’s a template that you can use to develop your project and use another dataset that you feel is appropriate for your business problem.
5. Awesome Notebooks by Jupyter Naas
Lastly, we will discuss Awesome Notebooks by Jupyter Naas. Awesome Notebook is a project by Jupyter Naas to create the largest catalogue of production-ready Jupyter Notebook templates. There is an abundance of free Jupyter Notebook templates from which you can choose.
The project consists of many professional Jupyter Notebook templates with specific use cases. From AI development to analysing business funnels to YouTube video download, there are so many templates you can choose from.
Many of the templates require you to understand how to work as a data scientist, so learning how to use Python as a data scientist would help you use these templates. Once you understand what you need, this template collection will help your work.
Conclusion
Jupyter Notebook is an environment used by many professional data scientists as many data science breakthroughs happen in this platform. One of its nice features is that it is easily shareable and can become a template that many can use.
In this article, we have discussed five free Jupyter Notebook templates that can be used to boost your data science activity. The templates are:
- Cookiecutter Template for Python data science projects
- Data Science Notebooks Templates by Coen Meintjes
- Data Science Projects by Yusuf Cinarci
- Data Science Projects by Sukman Singh
- Awesome Notebooks by Jupyter Naas
Cornellius Yudha Wijaya is a data science assistant manager and data writer. While working full-time at Allianz Indonesia, he loves to share Python and data tips via social media and writing media. Cornellius writes on a variety of AI and machine learning topics.
