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Jupyter

Multi-language interactive computing environments.
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What is Jupyter?

The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media.
Jupyter is a tool in the Data Science Notebooks category of a tech stack.
Jupyter is an open source tool with 6.6K GitHub stars and 2.7K GitHub forks. Here鈥檚 a link to Jupyter's open source repository on GitHub

Who uses Jupyter?

Companies
120 companies reportedly use Jupyter in their tech stacks, including Intuit, SendGrid, and Checkr.

Developers
343 developers on StackShare have stated that they use Jupyter.

Jupyter Integrations

Python, Plotly, Apache OpenWhisk, Kubeflow, and Datastax Enterprise are some of the popular tools that integrate with Jupyter. Here's a list of all 9 tools that integrate with Jupyter.

Why developers like Jupyter?

Here鈥檚 a list of reasons why companies and developers use Jupyter
Jupyter Reviews

Here are some stack decisions, common use cases and reviews by companies and developers who chose Jupyter in their tech stack.

Guillaume Simler
Guillaume Simler
at Velchanos.io | 4 upvotes 20.3K views
Jupyter
Jupyter
Anaconda
Anaconda
Pandas
Pandas
IPython
IPython

Jupyter Anaconda Pandas IPython

A great way to prototype your data analytic modules. The use of the package is simple and user-friendly and the migration from ipython to python is fairly simple: a lot of cleaning, but no more.

The negative aspect comes when you want to streamline your productive system or does CI with your anaconda environment: - most tools don't accept conda environments (as smoothly as pip requirements) - the conda environments (even with miniconda) have quite an overhead

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Mark Melnykowycz
Mark Melnykowycz
Artist - Scientist - Wearable Computing at idezo GmbH | 1 upvotes 3.6K views
Jupyter
Jupyter

When integrated with cloud platforms it's an easy way to code and test data science projects. The web-based nature makes it easy to transition between coding on your local machine or the cloud. Jupyter

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Jupyter
Jupyter
G Suite
G Suite

I use Jupyter and JupyterLab specifically because it's such a great interface for Python, SQL, data exploration, and data viz. Documentation is built into the design of a notebook, and it's commonly used enough in people's workloads that not much educating is required.

I know some on G Suite like using CoLab, but it runs pretty slow and disconnects runtimes often.

Here's a fun little example to make it feel more real Jupyter/CoLab Example

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Jupyter Alternatives & Comparisons

What are some alternatives to Jupyter?
Apache Zeppelin
A web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more.
PyCharm
PyCharm鈥檚 smart code editor provides first-class support for Python, JavaScript, CoffeeScript, TypeScript, CSS, popular template languages and more. Take advantage of language-aware code completion, error detection, and on-the-fly code fixes!
IPython
It provides a rich architecture for interactive computing with a powerful interactive shell, a kernel for Jupyter. It has a support for interactive data visualization and use of GUI toolkits. Flexible, embeddable interpreters to load into your own projects. Easy to use, high performance tools for parallel computing.
SageMath
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.
Franchise
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.
See all alternatives

Jupyter's Followers
350 developers follow Jupyter to keep up with related blogs and decisions.
AlvaroAbarca
fabiano filho
Tyler Churchill
Moe S3k
Mario Burbano
Scott Serich
Shambhavi Thakur
patk_ai
Victor Manuel Hernandez
Linus Kohl