As a data scientist, you almost surely use a form of Jupyter Notebooks. Hopefully, you have moved over to the goodness of JupyterLab with its integrated sidebar, tabs, and more. When it first launched in 2018, JupyterLab was great but felt it was missing some things.
Now you can add a visual debugger and there is even a library called nbdev that allows you to author full Python packages and push them to PyPI. JupyterLab has become a complete IDE for data scientists. But one thing was still sub-optimal until recently, code completions.
Trying to use the built-in code completion in JupyterLab gets you something like…
Disclaimer: I’m not affiliated with Anvil, I just love their product.
As more data scientists enter organizations around the world, most will find a very different work environment than what they may have dreamed about at Netflix, Facebook, or Google. At these companies, data scientists are supported by data engineers, machine learning engineers, application developers, and dev-ops specialists. Instead, they will probably find themselves working in a small team, or even by themselves. This poses major issues when a data scientist wants to get their insights, models, and even products out of Jupyter and into production.
Anvil fills in these gaps by allowing you to build a full-stack web app using only Python. You can build a user interface with a simple drag and drop UI (or build it with code if you insist), plot with your favorite Python plotting library (Plotly, Matplotlib, etc.), and then deploy to the web in one click. No servers or containers to deal with. …
The current election saw a switch back to the block voting system used in 1992 and 2008. This system has both positives and negatives, and this system has much larger election districts than the previous single-member districts of the 2016 election. This allows us to more easily analyze the districts with the available data.
To put all of the data together and make it user friendly, I built Songolt, an interactive data explorer that allows the reader to see key indicators of election districts. The indicators covered in the app include: