Objective

Create a comprehensive list of all suburbs within a specific radius around the user's inputted work coordinates.

Implementation Details

To classify suburbs effectively, postal codes were used as the primary differentiating factor. Each postal code represents a specific suburb, which would later be used in Phase 2 for calculating commute distances and quality of life metrics.

Technical Implementation

  • APIs Used:
    • Geopy API - For geographical calculations
    • Geonames API - For postal code data retrieval
    • Google Maps API - For coordinate mapping
  • Data Processing:
    • Retrieved JSON of postal codes within specified radius
    • Extracted center point coordinates for each postal code
    • Stored data in a structured DataFrame for further analysis

Data Structure

The final output of this phase is a DataFrame containing:

  • Postal codes for each suburb
  • Center point coordinates (latitude/longitude)
  • Suburb names and boundaries
  • Distance from work location