I’ve been using Plotly and Dash for a while to create various interactive visualizations, but I recently came across a tool that provides real-time traffic data specific to the city I am in now. I’m curious about how to integrate this real-time data into a dynamic dashboard using Plotly Dash, particularly when dealing with multiple data streams like traffic congestion, average speed, and incidents.
My main challenge is ensuring that the data updates in real-time on the dashboard without causing significant performance issues. I’ve read about using dcc.Interval in Dash for periodic updates, but I’m not sure how to efficiently manage the data flow, especially when the dataset is constantly updating.
Additionally, I’m interested in visualizing traffic congestion levels on a city map, where the road segments are color-coded based on traffic density. I’ve used Mapbox with Plotly before, but I’m not sure how to handle the real-time aspect effectively.
Moreover, I would appreciate some advice on how to display additional data layers, such as accident hotspots or traffic camera feeds, on the same map without overwhelming the user interface. Is there a way to allow users to toggle these layers on and off easily?
Lastly, I’ve noticed that the data provided by the real-time traffic tool for the city I am in now is sometimes incomplete or delayed. Are there best practices within Dash or Plotly to handle such scenarios, like showing placeholder data or notifying the user of data delays?
I’m looking forward to any tips, code snippets, or examples from others who have worked with real-time data in Dash, especially related to traffic or city data visualization. Any guidance on how to optimize the dashboard for performance while maintaining a smooth user experience would be incredibly helpful. Thanks!