A naukri.com initiative
Marktechpost
1w
289
A Coding Implementation for Building Python-based Data and Business intelligence BI Web Applications with Taipy: Dynamic Interactive Time Series Analysis, Real-Time Simulation, Seasonal Decomposition, and Advanced Visualization
- This tutorial delves into creating an interactive dashboard using Taipy for dynamic data-driven applications.
- Taipy simplifies the development of interactive visual analytics and real-time simulations.
- Installation of Taipy and statsmodels is crucial for building Python-based BI web applications.
- Key libraries like NumPy, Matplotlib, and statsmodels are imported for building interactive dashboards.
- The reactive state container in Taipy enables real-time updates based on parameter changes.
- The update_simulation function generates synthetic time series data with trend, seasonal, and noise components.
- The dashboard allows customization of trend coefficient, seasonal amplitude, noise level, and time horizon.
- Simulation results are visualized with plots showing the simulated time series and seasonal decomposition.
- The Taipy-powered dashboard offers real-time updates and in-depth analysis capabilities.
- Overall, this tutorial showcases how Taipy integrates with popular tools for creating advanced BI web applications.
Read Full Article
17 Likes
For uninterrupted reading, download the app