Database connection achieved in PostgreSql#1466
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s223973381 merged 4 commits intobackend_workfrom Aug 9, 2025
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Includes Sprint 1: - Fetched 3 insect biodiversity datasets from Melbourne Open Data API - Combined and cleaned datasets to create a unified dataset of insect sightings - Identified unique species, location-based sightings, and seasonal patterns - Visualised distribution on interactive folium maps - Used GeoPandas and Seaborn for plotting and geospatial analysis Includes Sprint 2: - Compared Melbourne species against national GBIF API data to identify species unique to Melbourne - Generated biodiversity heatmaps (species richness by location) - Created taxonomic summaries for top orders, families, and genera - Performed DBSCAN clustering to detect insect density hotspots - Analysed seasonal trends across spring, summer, autumn, and winter - Wrote detailed tutorial explanations under each heading - Replaced all US spelling with AUS English (analyse, visualise, etc.) All checklist items are complete follows the correct template and is ready for review.
DS TEAM UC00042_Tracking_Unique_Insect_Species_in_City_of_Melbourne 100%
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Revised folders and files after database migration from mongoDB to PostgreSQL