Share Your App - Explore Page - May 2025

Dash Python
1

Thank you for your interest in submitting your Dash app to the Plotly Explore Page platform, visited by thousands of Dash users daily.

Current submissions cycle will go until May 31, 2025.

To submit your app, please reply to this thread directly.

Please refer to the following suggestions when building and submitting your app. The more suggestions your app adheres to, the more likely it is to be added to the Explore Page.

  • Apps in the following categories are encouraged: Energy & Utilities, Business, Predictive Analytics & Forecasting, NLP, Connecting to APIs
  • App should look as good or better than the current apps on the platform
  • App should use different data than the other apps and try to cover a unique story
  • Content/story should be neutral or positive
  • App with live data that updates itself is encouraged
  • App that goes beyond exploratory analysis – app that perform advanced analytics
  • App that uses 3rd-party libraries (e.g., SciPy, spaCy, TensorFlow, Scikit-learn)
  • App that solves real-life problems, app that could have practical use cases
  • App content and results should be easy to access (we discourage requiring log-ins or uploading data as a precursor to seeing the full app).

The Plotly Example Apps team will review the apps submitted and update this post with the names of the apps that have been selected.

Happy Dash app building!

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I’d like to submit my app, Energy Demand Dashboard, for consideration on the Plotly Explore Page.

Energy Demand Dashboard is a Dash app focused on the interactive visualization and forecasting of California’s hourly energy demand. The app fetches live data from the EIA API (CAISO) and uses advanced machine learning models (LightGBM, XGBoost, stacking) for real-time forecasting. Users can also upload their own CSV data for custom analysis.

Key features:

  • Live Data: Automatically updates with real hourly demand from the EIA API.
  • Advanced Analytics: Includes distribution, seasonality, variability, and outlier detection.
  • Forecasting: Real-time, interactive forecasts using a stacking ensemble of ML models.
  • Model Transparency: Feature importance and model details are clearly displayed.
  • User-Friendly: No login required; the app is fully accessible and mobile responsive.
  • Unique Data Story: Focuses on California’s energy demand, a topic not covered by other Explore Page apps.
  • Practical Use Case: Useful for anyone interested in energy consumption trends and forecasting.

Code and more info: GitHub - LanderAgirre/energy_demand

2 Likes
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Thank you @landeragirre . Do you plan to deploy this app to the web?

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Thanks! Yes, that’s the intention.

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hi @landeragirre
Thank you for submitting your app.

Please send me a Direct Message as soon as you data app webpage is complete.

Thank you,