Luminal

The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media.

A web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more.

Deepnote is building the best data science notebook for teams. In the notebook, users can connect their data, explore and analyze it with real-time collaboration and versioning, and easily share and present the polished assets to end users.

It is a hosted Jupyter Notebook service that requires no setup to use and provides free access to computing resources, including GPUs and TPUs. Colab is especially well suited to machine learning, data science, and education.

It is a free open-source mathematics software system licensed under the GPL. It builds on top of many existing open-source packages: NumPy, SciPy, matplotlib, Sympy, Maxima, GAP, FLINT, R and many more.

It is a different kind of notebook. It supports mixing multiple languages in one notebook, and sharing data between them seamlessly. It encourages reproducible notebooks with its immutable data model.

Chart with a single click. Compare queries side by side. Download your work and share it with anyone. If your data is in a CSV, JSON, or XLSX file, loading it is as simple as dropping the file into Franchise.

It is fully in-browser literate notebooks like Jupyter Notebook. It's probably the quickest way to visualize some data with interactivity, do some prototyping, or build a rudimentary dashboard.

It is an end-to-end tool for data science, without writing any code. Import, prepare, analyze, visualize and share in just a few clicks. Build interactive reports, automate workflows and share templates.

It is the easiest way to turn your Python Notebooks into interactive web applications and publish to the cloud. It is dual-licensed. The main features are available in the open-source version. It is perfect for quick demos, educational purposes, sharing notebooks with friends.

It is a reactive notebook for Python. It allows you to rapidly experiment with data and models, code with confidence in your notebook’s correctness, and productionize notebooks as pipelines or interactive web apps.

It is the platform to explore your data, develop and deploy your Python supercharged Notebooks and track the quality of your data using Machine learning.