Member-only storyMilan JanosovFollowTowards Data Science--ShareThe International Union for Conservation of Nature (IUCN) launched several projects to protect wildlife. One of these efforts led to a high-quality global geospatial database containing the habitats of more than 100,000 species. In this article, I explore its subset, focusing on terrestrial mammals.The IUCN’s Red List of Threatened Species database contains more than 150,000 species, with geospatial information about habitats attributed to 80%+ of them. This database’s mere size proposes several challenges, which I may address in a later article. For now, I focus on a smaller subset — the global database consisting of terrestrial mammals with 12,436 records, each corresponding to one habitat patch per species. This mammal-habitat database is based on around four hundred different sources and contains 5,626 species identified by their binomial names, registered between 2008 and 2022. Furthermore, the database includes detailed taxonomic information, such as the order and family of the species. Additionally, a primary strength of the database is that it has detailed geospatial information on habitats in the form of polygon files, which I will explore in more detail later.First, I will introduce and explore the non-geometric features of this dataset and then conduct a few analytical steps specific to the geospatial distribution of the different species. With this analysis, I hope to popularize this data source and encourage future work with potential applications for wildlife protection policies.You may find all the IUCN data sources here, from which I downloaded the Terrestrial Mammals polygon data (search date: 2023–10–02 at 15:30:02)All images in this article were created by the author.1.1. Parse the datasetFirst, let’s parse the database using GeoPandas and see what it contains:----Towards Data Science🎯 Network scientist | 🌏 Geospatial data and data viz expert | ✈️ Chief data scientist @Baoba | 📖 Author @Openbooks | 🎖️ Forbes 30u30Milan JanosovinTowards Data Science--4Damian GilinTowards Data Science--24Khouloud El AlamiinTowards Data Science--20Milan JanosovinTowards Data Science--3Google EarthinGoogle Earth and Earth Engine--Andrew Brott--Simonetta BodojrainData Reply IT | DataTech--North American Geoscientists Organization--LAWRENCE KIMUTAI--Milan JanosovinTowards Data Science--3HelpStatusAboutCareersBlogPrivacyTermsText to speechTeams