*This post is part of a series entitled **Spatial is not Special**, where I will illustrate how spatial constructs in SQL provide us with a rich toolset for geographers doing spatial analysis. To illustrate these concepts, I will be showing examples from my book **Statistical Problem Solving in Geography**. Even though PostGRES, SQLServer, MySQL, spatialite, and Oracle all support spatial SQL, these examples will be presented using Manifold GIS. The example dataset is a Manifold 8.0 .map file and can be found **here**.*

Today’s post examines the SQL code necessary to generate the mean center for a geographic data set. Recall from *Statistical Problem Solving in Geography* (third edition), the formula for mean center and the 7 point data set used.

Using our example dataset, and some basic SQL, we can easily generate the code necessary to compute the mean center,

**SELECT avg****(x),****avg****(y)**
**FROM**** Points**

The SQL function **avg** allows us to compute the average of both the *x*, and *y* data columns. However, adding the **NewPoint** function takes both the average x and y coordinates and turns them into a geometry object, and is easily added to the existing SQL syntax:

**SELECT NewPoint(avg****(x),****avg****(y))**
**FROM**** Points**

The next post will examine how to calculate the weighted mean center using SQL. And don’t worry, these examples are going to get more complicated as we go along.

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