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Co-authored-by: nilbuild <4921183+nilbuild@users.noreply.github.com>
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src/data/roadmaps/python-data-analysis/content/geopandas@-Bxn2sj2NjHLhRZrPIi0n.md
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# GeoPandas
GeoPandas is an open-source library that extends the capabilities of pandas by allowing spatial operations on geometric types. It simplifies working with geospatial data by enabling the use of familiar data structures like GeoSeries and GeoDataFrame, which store and manipulate vector-based geographic information. Through its integration with libraries like Shapely and PyGEOS, it allows you to perform complex geometric operations such as spatial joins, projections, and distance calculations using straightforward syntax.
Visit the following resources to learn more:
- [@official@GeoPandas Docs](https://geopandas.org/en/stable/docs.html)
- [@official@Introduction to GeoPandas](https://geopandas.org/en/stable/getting_started/introduction.html)
- [@video@Geospatial Python - Full Course for Beginners with Geopandas](https://www.youtube.com/watch?v=0mWgVVH_dos)
src/data/roadmaps/python-data-analysis/content/geospatial-analysis@SWrijRzSZxhnSYDwv1_pH.md
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# Geospatial Analysis
Geospatial analysis is the process of gathering, manipulating, and mapping data that is tied to specific geographic locations on the Earth's surface. It involves using tools and libraries to perform spatial operations, such as calculating distances between coordinates, analyzing geographic patterns, or visualizing datasets on interactive maps. By integrating coordinate systems and geometric shapes into data workflows, this analysis allows for a deeper understanding of how physical location influences various trends and phenomena.
Visit the following resources to learn more:
- [@article@Introduction to Python for Geographic Data Analysis](https://pythongis.org/)
- [@article@Spatial analysis with Python](https://spatial-analytics.readthedocs.io/en/develop/lessons/L1/intro-to-python-geostack.html)
- [@video@GeoSpatial Analysis With Python For Beginners](https://www.youtube.com/watch?v=IRJC67zm6nk)