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6/27/2026
Mastering the "Quantified Self": Building a Blazing-Fast Heart Rate Dashboard with DuckDB and Streamlit

Mastering the "Quantified Self": Building a Blazing-Fast Heart Rate Dashboard with DuckDB and Streamlit

Short summary

This tutorial guides developers through building a high-performance health dashboard using DuckDB (a columnar analytics engine), Streamlit, and Plotly. DuckDB achieves 5-10x speed improvements over Pandas for analytical queries on time-series data. Includes working Python code, setup instructions, and performance benchmarks for querying large CSV datasets in real-time.

  • •DuckDB's vectorized execution processes time-series data 5-10x faster than traditional Pandas for 100k+ rows
  • •Step-by-step tutorial builds an interactive heart rate dashboard with Streamlit and Plotly visualization
  • •Practical code examples show CSV ingestion, SQL aggregation, and moving average calculations

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