semantic-link-functions-geopandas

What it is and what it does

This package extends FabricDataFrame with geospatial semantic functions that automatically appear in autocomplete when your data contains location columns and appropriate metadata. It bridges Microsoft's Fabric data model with the geopandas geospatial ecosystem, allowing you to convert a FabricDataFrame with latitude and longitude columns into a GeoDataFrame for spatial analysis.

The package uses the @semantic_function decorator pattern to register functions that inspect data types, column metadata (such as Power BI data categories), and actual data values to determine when they should be available. This means functions like is_holiday or geospatial operations show up contextually rather than cluttering every namespace. It's designed for developers working with Fabric data who need to perform geographic operations without manual function discovery or explicit imports.

Use it for:

• Convert Fabric datasets with latitude/longitude columns to GeoDataFrames for spatial analysis and mapping
• Automatically surface location-aware functions in IDE autocomplete when working with geographic data
• Integrate Power BI data categories with geopandas workflows for seamless geospatial operations
• Build data pipelines that combine Fabric's semantic metadata with folium-based map visualizations
• Classify geographic data using mapclassify within a Fabric-native data structure

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Adds geospatial semantic functions to FabricDataFrame, enabling automatic discovery and application of location-aware operations based on detected latitude/longitude columns and metadata.

Yes, if you work with Fabric data and need geospatial operations. The package is actively maintained, has low install friction, carries a permissive MIT license, and integrates cleanly with geopandas. However, it is in beta status and has modest adoption (16 repository stars), so expect potential API changes and verify compatibility with your specific versions of geopandas and mapclassify before production use.

Install

semantic-link-functions-geopandas on PyPI

pip install semantic-link-functions-geopandas

uv add semantic-link-functions-geopandas

poetry add semantic-link-functions-geopandas

Installing semantic-link-functions-geopandas

Before you install

Active maintenance with a recent release (24 days old). Low install friction with four runtime dependencies. Repository shows modest activity (16 stars), and the package is in beta status.

License in practice

MIT License permits free use, modification, and distribution with minimal restrictions, making it suitable for both open-source and commercial projects.

Quickstart

pip install semantic-link-functions-geopandas

from sempy.fabric import FabricDataFrame

df = FabricDataFrame(
    {"country": ["US", "AT"], "lat": [40.7128, 47.8095], "long": [-74.0060, 13.0550]},
    column_metadata={"lat": {"data_category": "Latitude"}, "long": {"data_category": "Longitude"}}
)
df_geo = df.to_geopandas(lat_col="lat", long_col="long")

Requires Python 3.10 or later; depends on geopandas, folium, mapclassify, and semantic-link-sempy being installed and compatible.

Verify before relying

• Whether semantic function discovery works reliably across different data category metadata schemas
• Performance characteristics when working with large geospatial datasets
• Compatibility with specific versions of geopandas, folium, and mapclassify beyond the minimum Python 3.10 requirement

Package facts

Evidence: semantic_link_functions_geopandas-0.14.2-py3-none-any.whl

Tags

More Scientific/Engineering packages