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GeoPandas: easy, fast and scalable geospatial analysis in Python

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GeoPandas: easy, fast and scalable geospatial analysis in Python
FOSDEM 2018

The goal of GeoPandas is to make working with geospatial vector data in python easier. GeoPandas (https://github.com/geopandas/geopandas) extends the pandas data analysis library to work with geographic objects and spatial operations.

Pandas is a package for handling and analysing tabular data, and one of the drivers of the popularity of Python for data science. GeoPandas combines the capabilities of pandas and shapely (python interface to the GEOS librabry), providing geospatial operations in pandas and a high-level interface to multiple geometries to shapely. It combines the power of whole ecosystem of geo tools by building upon the capabilities of many other libraries including fiona (reading/writing data with GDAL), pyproj (projections), rtree (spatial index), ... Further, by working together with Dask, it can also be used to perform geospatial analyses in parallel on multiple cores or distributed across a cluster. GeoPandas enables you to easily do operations in python that would otherwise require a spatial database such as PostGIS.

Speakers: Joris Van den Bossche