Santiago Cárdenas Jotty
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Data visualization · hackathon

Crime.io

A geospatial exploration of crime data built with Python and Streamlit; the project placed third in a hackathon.

Role
Zone comparison and data visualization
Context
Hackathon project

Visual evidence

Visual evidence03
Public Crime.io interface with filters and an incident map of San Francisco.
Interactive map and filters published in the project repository. Public source
Public Crime.io zone-comparison view.
Public evidence of the zone-comparison module Santiago contributed to. Public source
Public Crime.io query-assistant view.
Public assistant interface included in the repository. Public source

The question

How can isolated records become a spatial reading that helps identify patterns and compare areas?

The build

The project prepares and explores data with Pandas and NumPy, then uses Streamlit and Folium to turn it into an interactive mapping experience.

The result

The solution placed third. The public repository preserves the technical process and makes it possible to review decisions made under a real time constraint.

Key decisions

  1. Turn tabular records into a geographic reading.
  2. Separate data preparation from interactive presentation.
  3. Choose tools that supported iteration within the event window.

Verifiable outcomes

  1. Third place in the hackathon.
  2. Visual exploration of geographic patterns.
  3. Public repository for technical inspection.