Exploring Eco topics with Python
summary
Shows exact datasets and code: numpy pandas matplotlib geopandas networkx xarray rioxarray inside prepared Jupyter notebooks, not high-level promises. Filters 1,689 pangolin trades down to 612 usable records and builds a network graph of exporter→importer edges; aggregates 138 unique trade relationships. Loads EPA GHGRP data to find 118 US university facilities responsible for ~96 million tCO2e (2011–2021) and makes interactive folium maps. Processes Landsat bands into NDVI, produces a pixel-based land-cover map (four classes) — it runs but sensor/band differences and coarse assumptions limit strict comparability.
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chapters (8)
- 0:00Introduction
- 1:03Tutorial overview
- 10:57Wildlife trade exploration
- 1:02:04Carbon footprint intro
- 1:03:53Carbon footprint with Python
- 1:58:23Deforestation intro
- 2:01:37Deforestation notebook
- 2:56:07Q&A
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