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  1. Leverage big data tools, such as Apache Spark, from Python, R, and Scala. Explore that same data with pandas, scikit-learn, ggplot2, and TensorFlow.

    • Install

      Project Jupyter’s tools are available for installation via...

    • Try

      Project Jupyter builds tools, standards, and services for...

    • Jupyterlite

      Jupyterlite - Project Jupyter | Home

    • Get Involved

      Jupyter is a community of data enthusiasts who believe in...

    • Documentation

      An interactive Python kernel and REPL. Reference. APIs....

    • News

      The Jupyter Blog. JupyterLab 3 end of maintenance. The...

    • Governance

      By The Jupyter Book community To the extent possible under...

    • Security

      The Jupyter Notebook is a web-based interactive computing...

  2. Project Jupyter’s tools are available for installation via the Python Package Index, the leading repository of software created for the Python programming language. This page uses instructions with pip, the recommended installation tool for Python.

    • Jupyter Lab vs Jupyter Notebook
    • Advantages of Using Jupyter Lab and Notebook
    • How to Install Jupyter Notebook and Lab
    • Start and Explore Jupyterlab
    • Your First Steps in A Notebook
    • Jupyterlab Plugins
    • Ipython
    • Jupyter Notebook in Vscode
    • Keep Learning

    JupyterLab is a web-based, interactive development environment. It’s most well known for offering a so-called notebook called Jupyter Notebook, but you can also use it to create and edit other files, like code, text files, and markdownfiles. In addition, it allows you to open a Python terminal, as most IDEs do, to experiment and tinker. JupyterLab ...

    Python application developers often prefer and work with a regular Python IDE like VSCode, which facilitates debugging, unit testing, deployment, and version management. In contrast, (data) scientists and data analysts have a different focus and often prefer a Notebook-style IDE. Let’s look at some of the advantages these notebooks have to offer.

    Like all Python software, installing Jupyter Lab is a breeze. I’ll demonstrate how to install with both Pip and Conda. One thing to note beforehand: I recommend installing this system-wide. I usually stress the importance of using a virtual environment. However, I feel that tools like this you want to install once.

    How to open Jupyter Lab from the command line

    If you followed the installation instructions, you should be able to start Jupyter Lab with:

    How to open Jupyter Notebook from the command line

    If you only want to start a Notebook, use this:

    Adding to your PATH

    If you get an error like “command not found,” don’t panic. Unfortunately, some systems don’t have the .local/bin directory in the $PATHvariable.

    If you start Jupyter Lab or Notebook, it will automatically open your browser. If it didn’t, you can go to http://localhost:8888/ manually to open it. Once there, create a new Notebook, e.g., by clicking File -> New -> Notebook. I created a new Notebook named ‘First steps’ in the following screenshot. There are a couple of noteworthy things to see:...

    If you click on the puzzle icon at the left of the screen, you’ll get a list of plugins that can be installed directly. There are lots of plugins, and many of them will add extra visualization capabilities or integration with products like Tableau.

    Internally, Jupyter Notebooks use a project called IPython. If you tend to use the Python REPL a lot, I recommend you to read our page on IPythonsince it is an excellent alternative to the regular REPL. I use it a lot personally, and I can’t recommend it enough! For example, it’s worth it just for its terrific auto-completion, and if you are used t...

    If you’re a VSCode fan, like me, you need to check out the VSCode extension that allows you to create and work with notebooks directly inside a VSCode tab. If you open up the command pallet, e.g., with ctrl + shift + p, start typing “Jupyter” to create, open, and export Notebooks.

    This article is part of a free Python Tutorial. You can browse the tutorial with the navigation buttons at the top and bottom of the article or use the navigation menu. Want to learn more? Here are some great follow-up reads: 1. Learn about NumPy, the foundation of data science in Python. 2. It’s always worth visiting the official project websitefo...

  3. Project Jupyter builds tools, standards, and services for many different use cases. This page has links to interactive demos that allow you to try some our tools for free online, thanks to mybinder.org, a free public service provided by the Jupyter community.

  4. Google Colaboratory. Colab 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. Open Colab New Notebook.

  5. Jul 11, 2024 · The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. Jupyter has support for over 40 different programming languages and Python is one of them.

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  7. Jupyter notebooks is an open-source web-based Python editor which runs in your browser. It allows a combination of text written in a html-like format known as "markdown", such as the block...

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