Jupyter Ascending : The journey from Jupyter Notebook to Jupyter Lab

For many of the researchers and data scientists, Jupyter Notebooks are the de-facto platform when it comes to quick prototyping and exploratory analysis. Right from Paul Romer- the Ex-World bank chief Economist and also the co-winner 2018 Nobel prize in Economics to Netflix, Jupyter Notebooks are used almost everywhere. The browser-based computing environment, coupled with a reproducible document format has made them the choice of tool for millions of data scientists and researchers around the globe. But have we fully exploited the benefits of Jupyter Notebooks and do we know all about the best practises of using it? if not, then this talk is just for you.

Through this talk/demo, I'll like to discuss three main points:

  1. Best Practises for Jupyter Notebooks since a lot of Jupyter functionalities sometimes lies under the hood and is not adequately explored. We will try and explore Jupyter Notebooks’ features which can enhance our productivity while working with them.
  2. In this part, we get acquainted with Jupyter Lab, the next-generation UI developed by the Project Jupyter team, and its emerging ecosystem of extensions. JupyterLab differs from Jupyter Notebook in the fact that it provides a set of core building blocks for interactive computing (e.g. notebook, terminal, file browser, console) and well-designed interfaces for them that allow users to combine them in novel ways. The new interface enables users to do new things in their interactive computing environment, like tiled layouts for their activities, dragging cells between notebooks, and executing markdown code blocks in a console and many more cool things.
  3. Every tool/features come with their set of pros and cons and so does Jupyter Notebooks/Lab and it is equally important to discuss the pain areas along with the good ones.
 
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Outline/Structure of the Demonstration

  • Introduction to Jupyter Notebooks
  • The rise of popularity among Data Scientists

    • Open Source and easily reproducible

    • Support for Multiple File formats

    • Great community support

  • Demo: Best Practises
  • Jupyter Lab: The Next generation of Jupyter Notebook

    • Demo: Features of Jupyter Lab

  • Extensions :Demo
  • Drawbacks

Learning Outcome

This presentation/demo aim is to highlight the following points:

  • Features of Notebooks which are lesser known but highly useful.
  • How to make a smooth transition to Jupyter Lab and get to know its ecosystem and its advantages over a classic notebook. This is necessary since the support to classic notebook will ultimately be withdrawn.
  • The possible drawbacks of Jupyter Notebooks and when it's probably not a good idea to use them.

Target Audience

Anybody who work with Jupyter Notebook for their Data Analysis tasks

Prerequisites for Attendees

Basic Knowledge of working with Jupyter Notebooks

schedule Submitted 3 months ago

Public Feedback

comment Suggest improvements to the Speaker
  • Vishal Gokhale
    By Vishal Gokhale  ~  3 months ago
    reply Reply

    Hi Parul, 

    Thanks for the proposal. This can be a useful talk for many people. However it is not clear how you plan to use the 45 mins duration. Request you to please provide a list of best practices and features of Jupyter lab that you intend to cover.

    Also, most of the attendees would be well aware of the Jupyter notebooks and reasons for popularity. You've also mentioned basic knowledge of Jupyter Notebooks as a prerequisite.
    So it might help to focus on best practices and Jupyter Lab features.
    You may want to consider making it a 20 min crisp talk. 

    Thanks,
    Vishal 

    • Parul pandey
      By Parul pandey  ~  3 months ago
      reply Reply

      Hi Vishal,

      Thanks for the feedback. If you feel the designated audiences will be well versed with Notebook, then I can leave the Notebook part. As far as the Jupyter Lab is concerned, I intend to cover the following aspects in the order in which it is written:

      1. The current state of Notebooks and the reason for migration to Jupyter Lab
      2. Jupyter lab overview and installation 
      3. Demonstration of the basic building blocks of Jupyter lab i.e Notebook, console, terminal and text editor in an integrated format.
      4. creating, opening and saving files in Jupyter Lab.
      5. Collapsible and Drag and Drop capabilities
      6. Demonstration of Markdown capabilities 
      7. Demo of File handlers including CSV, images, vega-lite, geoJSON
      8. Demo showing Support for different languages
      9. Jupyter Lab Extensions: installation and creation.

      If I spend on an average of 5 min on each slide, this will go way past the 20 min timeslot so I opted for 45 min, in case the participants had some questions too. Let me know your thoughts.

      • Naresh Jain
        By Naresh Jain  ~  2 months ago
        reply Reply

        Hi Parul,

        Thank you for sharing the details.

        Based on our experience, we find that these types of topics don't really attract many participants. Because one can google for them and will find videos online which cover these topics in detail.

        We find topics where the speaker shares their personal insights or learning a lot more attractive to attendees. Because they won't be able to find them easily online.

        For example, if you could take a real-world scenario, where you switched from Notebook to Jupyter Lab. Explain the drivers and some of the challenges you had to address to make this move successful. In the context of this scenario, you could highlight some real advantages and why everyone else should seriously considering making the switch.

        If you agree with this, please update your proposal accordingly ASAP as the review team is trying to finalize their votes.


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