makepath presented at the 10th meetup of PyData Trinidad and Tobago (PyData T&T).
PyData T&T is a welcoming community for locals interested in data science, analytics, machine learning, or deep learning. It provides opportunities for technology industry professionals and enthusiasts of all skill levels to learn about the latest developments in the Open Source Python and data science community.
The PyData scene in Trinidad and Tobago is ripe for explosion on a global scale. This is largely due to the rising talent in the region and a focus on balancing both first and third world needs.
With continued encouragement, support, and access to technical resources and mentors, the Python scene in Trinidad and Tobago will take off in an exciting way.
For the 10th Meetup of PyData T&T, makepath Co-Founder and Principal, Brendan Collins, demonstrated how the open source libraries xarray-spatial and RTXpy can be used for spatial data science.
Open Source GIS and Python for Geospatial
Using a Geographic Information System (GIS) is somewhat analogous to performing spatial data science using Python.
The xarray-spatial library, which Brendan created, provides tools for solving common geospatial problems as part of the broad ecosystem of Open Source GIS tools.
Dask: To scale calculations across different machines.
RTXpy provides xarray-spatial its own c extension for ray tracing using CUDA.
This allows xarray-spatial to quickly address complex spatial data science questions with its raster analysis functions.
Getting Started with Xarray-Spatial
The best way to get started using xarray-spatial is to review the User Guide.
The xarray-spatial User Guide includes notebooks of examples and test data to help users learn how to leverage the library and key raster analysis tools, such as the multispectral or pathfinding tools.