Templatify & What it Does

Templatify is an extension for JupyterLab that allows users to create templates based on uploaded data from a csv file to more easily conduct data analysis. We decided to create a template extension that allows users to select a csv file and choose the types of data analysis that they'd like to perform. These analyses can range from histograms, scatter plots, to correlation matrices.

Inspiration

When thinking about what we could work on for this hackathon, we really had to understand how the Jupyter Lab ecosystem worked. We found that this platform is widely used by data scientists while they are collecting, organizing, and analyzing their data.

Upon learning more about why people loved using JupyterLab, we started to understood that their userbase really appreciated the multipurpose and usable tools that the application provided. Thus, we also wanted to provide additional tools to users to streamline their work and make it easier to analyze.

How we built it

Front-end: TypeScript, React, JS

Back-end: Python

Challenges we ran into

As with learning any new platform and ecosystem, it took us awhile to really understand how to use JupyterLab in conjunction with the skills that we currently have. We spent a lot of time early on setting up our environment and following along with tutorials to make sure we understood both the tools and userbase we were making the extension for.

Accomplishments that we're proud of

We're really proud that we were able to accomplish as much as we did given the time constraints on a new platform. We're also think that Templatify is a good idea and could eventually be a really usable extension to JupyterLab ecosystem.

What we learned

We really learned how to work in our group of two to solve a lot of the issues that we were having. It was really beneficial having an extra set of eyes and a fresh mind when someone was stuck on an issue for a really long time.

Another cool thing that we learned was how much preparation it took for data scientists to really excel at in their role.

What's next for Templatify

Although we're not sure of how far we want to take the project, we firmly believe that Templatify could really be useful for users looking for a quick Jupyter Notebook template. We would potentially like to revisit this project at a later date when we're more familiar with JupyterLab.

Team

Bosco Chan: https://github.com/BoscoCHW

Linda Ngoc Nguyen: https://github.com/iflinda

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