Introduction#

libadalina-analytics is a Python library for spatial data analytics.

It provides analysis tools for

  • building geospatial enriched graphs

  • performing network analysis on geospatial data

  • clustering geospatial area to create meaningful regions

  • minimize facility relocations costs

It works with DataFrame and GeoDataFrame objects from pandas and geopandas libraries, and makes use of Apache Sedona, a powerful geospatial processing engine, for efficient spatial data processing.

libadalina-analytics is part of the ADaLinA project that aims to develop a set of tools for the analysis of large-scale spatial data to be integrated into the Amelia homepage platform.

The online documentation is available ad https://libadalinaanalytics-0bbfb4.gitlab.io.

libadalina-analytics is partially funded by the European Union - Next Generation EU, Mission 4, Component 1 CUP J33C22002910001 - GRINS foundation, Project ADALINA.

Requirements#

libadalina-analytics requires Python 3.10 and depends on the following libraries:

  • libadalina-core

  • highspy

  • pydantic

  • scikit-learn

libadalina-analytics has been tested with OpenJDK 17.