09-19, 12:05–12:40 (Europe/Amsterdam), Mondriaan
Struggling with static reports? This talk introduces Shiny for Python, a framework for crafting interactive web apps in minutes. Leverage your Python skills (pandas, matplotlib) to design user-friendly dashboards for real-time data analysis. Ideal for data scientists of all levels (no Shiny for R experience required).
Working on a data project is incredibly interesting but it conveying their content to others can be very challenging. Visualizing your data could be the key to getting that extra input on your project that will push it to the next level. But since your main focus is probably on the data project itself you probably want a way to quickly visualize your data that’s where shiny for python comes in to the picture.
Shiny for python enables you to create visualizations directly from python code so no javascript/html knowledge is required to visualize your data and deploy it as a web application so everybody can interact with it. And you can keep using your trusty pandas, numpy, matplotlib libraries you’re already familiar with for transforming since your still working within the python ecosystem.
Shiny for python is not the only way to do this as dash & streamlit have a similar purpose. However one of the main advantages of shiny for python is that it’s more intuitive to use compared to dash which requires stateless callbacks and independent self-contained app components which adds a lot of complexity. Which is similar to the advantage streamlit has over dash but streamlit requires the whole script to run again when you change a single variable which isn’t the case in shiny for python. So shiny for python strikes the balance between in simplicity & performance.
So if turning your python code into an interactive dashboard sounds interesting to you, make sure to stop by!
Responsible for Posit in the Benelux
Medior Data engineer at AXI & python enthusiast with a passion for making interesting data topics more broadly accesible.