I have many well-documented Python Jupyter workflows available to demonstrate spatial data analytics and geostatistics workflows with GeostatsPy in my PythonNumericalDemos repository. Click this link to download all my workflows.
GeostatsPy Python Package Available on PyPI
I'm the primary author of the opensource GeostatsPy Python package for spatial data analytics. The GeostatsPy Package brings GSLIB: Geostatistical Library (Deutsch and Journel, 1998) functions to Python. GSLIB is an extremely robust and practical set of code for building spatial modeling workflows. I needed it in Python to support my students in my Data Analytics, Geostatistics, and Machine Learning courses so I spent most of weekends in the Spring 2019 semester coding just-in-time for my students!
To install GeostatsPy type the following in a Python terminal window:
pip install geostatspy
The source code is available in my GeostatsPy repository. Click this link to download the source code.
MICHAEL J. PYRCZ, Ph.D., P.Eng., Associate Professor
Cockrell School of Engineering, Jackson School of Geosciences
and Bureau of Economic Geology
The University of Texas at Austin, Austin, Texas, USA