Spatial Analytics with PostGIS, PL/R and R | Crunchy Data Blog
Introduction to Spatial Analytics with PostgreSQL, PostGIS, PL/R and R. First in series of posts introduces PL/R and provides background for sample analysis.
In this article, we will put together some of the basic spatial data types and operations while leveraging PostGIS to build something that resembles a real-world application that can be useful for our daily lives. The focus will be on the database layer of the application, as that’s where most of the GIS magic happens, but we will ultimately build a full-stack application featuring PostGIS database, Java Spring Boot back-end, and HTML/JavaScript front-end.
The all-seeing eye isn't mere symbolism - the all-seeing eye is a fundamental pattern of the Universe - it's how consciousness becomes objectiified int...
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oRm is a lightweight Object-Relational Mapper (ORM) for R. It simplifies database interactions by allowing users to define table models, insert and query records, and establish relationships between models without writing raw SQL. oRm uses a combination of DBI, dbplyr, and R6 to provide compatibility with most database dialects.