This lab demonstrates how to perform a clustering analysis in BigQuery GIS using Python and Jupyter notebooks. The lab leverages the built-in DBScan clustering function in BigQuery GIS to cluster street trees in San Francisco from the Google public datasets. It also shows how to analyze the cluster results using the pandas library within Python.
Learning Objectives
Upon completion of this lab you will be able to:
- Interact with BigQuery GIS datasets within Jupyter notebooks
- Perform a clustering analysis on
GEOGRAPHYdata - Use
pandasto analyze cluster analysis results
Intended Audience
This lab is intended for:
- GIS engineers
- Data engineers dealing with location-based data
- Developers looking to leverage geospatial information
- Data scientist leveraging geospatial data
Prerequisites
You should possess:
- Basic understanding of relational databases and ANSI SQL
- Basic understanding of Python
- Familiarity with BigQuery GIS's
GEOGRAPHYdatatype
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