Data comes in all shapes and sizes and often government data is geospatial in nature. Often times data science programs & tutorials ignore how to work with this rich data to make room for more advanced topics. Our MinneMUDAC competition heavily utilized geospatial data but was processed to provide students a more familiar format. But as good scientists, we should use primary sources of information as often as possible.
Come to this talk to get a basic understanding of how to read, write, query and perform simple geospatial calculations on Minnesota Tax shapefiles with Python.
As always data & code will be provided.
https://github.com/SocialDataSci/Geospatial_Data_with_Python
@dreyco676
https://www.linkedin.com/in/johnhogue/
