20 - Low-code/no-code Geospatial Data Analysis in Foundry

What applications should I use to conduct analysis of Geospatial data in Foundry?

In this lesson, you'll explore the use of Contour, Quiver, and the Foundry Map for analyzing and presenting data without the use of code.

Foundry's code-based applications add valuable geospatial insights, too. For example, technical data analysts and data scientists can use Code Workbook to apply common libraries for parsing and analyzing geodata, e.g., performing spatial joins, finding geographic overlaps between datasets. These libraries include (but are not limited to):

• GDAL / ogr2ogr ↗: Versatile package of geodata transformations and conversions between various formats
• Geopandas ↗: Extends the datatypes used by Pandas to allow spatial operations on geometric types
• Apache Sedona ↗: A Pyspark extension for spatial data at scale
• H3 ↗: Hexagon-based geo-indexing library especially useful for geoindexing and grouping shapes
• Shapely ↗: Common shape operations, including intersections, buffers, and transformations
• Pyproj ↗: A Python interface to PROJ — a cartographic projections and coordinate transformations library
• Geospatial-tools: Python library for performing common transformations on vector geospatial data pipelines in Foundry