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Martin Fleischmann - A Gentle Introduction to Spatial Data in the Pandas Ecosystem [PyData Prague]
Discover the basics of spatial data with GeoPandas, an extension of Pandas that integrates geospatial data and provides spatial operations and analysis capabilities in the Pandas ecosystem.
- GeoPandas is an extension of Pandas that integrates geospatial data, providing spatial operations and analysis capabilities.
- There are various types of geometry, including points, lines, and polygons, each with different properties and methods.
- A pedestrian can walk between neighboring polygons, but it’s not the same as a pedestrian walking between different groups or clusters.
- Geopandas can perform spatial joins, which allow data from multiple sources to be merged based on spatial relationships.
- The University of Liverpool has a strong relationship with a specific Geospatial Data Science program.
- Geopandas can be used for spatial clustering, recognizing patterns and grouping data points based on spatial proximity.
- There are various coordinate reference systems (CRS) that define the spatial relationships between points.
- Chocolatey is used to automate the installation of libraries and frameworks.
- Packages in the PySAL family, such as libPySAL and pycell, provide additional geospatial functionality.
- The DASK Geopandas library uses the DASK infrastructure to scale up geospatial computing.
- OSMnx is a library used to load OpenStreetMap data directly into Pandas.
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The
geometryattribute of a GeoPandas DataFrame can be used to perform spatial operations and analysis. -
read_fileis used to read spatial data files, such as GeoJSON, into a GeoPandas DataFrame. - Spatial weights can be used to analyze spatial relationships between data points.
- There are different levels of spatial hierarchy, including global, national, regional, and local.
- Polygons can be split into different parts or partitions based on spatial relationships.
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Geopandas provides various methods for spatial operations, including
distance,length, andarea. -
There are various spatial predicates, such as
touches,intersects, andwithin. - Spatial data can be analyzed using various libraries and frameworks, including those from the PySAL family.
- Geopandas provides various tools for visualizing spatial data, including plotting and map-making capabilities.