DataverseLabs/pyinterpolate
Kriging | Poisson Kriging | Variogram Analysis
This tool helps geologists, GIS experts, and social scientists analyze spatially correlated data to predict values at unmeasured locations. You input data points with known values (like sensor readings or population counts per area), and it outputs predicted values and their uncertainty for new points or areas. It's especially useful for understanding how phenomena are distributed across a landscape or region.
174 stars and 1,034 monthly downloads. Available on PyPI.
Use this if you need to make accurate predictions of environmental conditions, resource concentrations, or socio-economic indicators across a geographical area where you only have measurements at certain points or aggregated within larger regions.
Not ideal if your data points are completely independent of their location or if you are looking for general statistical analysis rather than spatial interpolation.
Stars
174
Forks
30
Language
Python
License
—
Category
Last pushed
Mar 19, 2026
Monthly downloads
1,034
Commits (30d)
0
Dependencies
8
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