Tutorial: Mean Center, Median Center and Central Feature(Plug-in Method)

Q: Find the Median Center and Central Feature of Starbucks Stores in Gangnam, Seoul.

Before you begin this tutorial, do the following first:

• Install the Spatial Analyzer Plugin
• Start Spatial Analyzer
• Add Starbucks Layer
• Add a Basemap

Finding the Median Center and Central Feature

[1] At the top of the screen, click the Processing menu, then click Toolbox. The Processing Toolbox panel will appear on the right side of the window.

[2] In the Processing Toolbox, expand SpatialAnalyzer at the bottom. Under Spatial Central Tendency, double-click Centers (Mean Center, Median Center, Central Feature)

[3] In the Spatial Central Tendency window, ensure Median Center and Central Feature are checked, then click Run. (By default, Mean Center, Median Center, and Central Feature are selected.)

Weight Field lets you compute weighted centers using an attribute instead of pure distance. Examples include seating capacity, sales revenue, or number of employees. If you choose “sales revenue,” the resulting mean or median center will shift toward higher-revenue areas.

Group Field computes centers separately for each category when your data is classified. For example, if there is an administrative-district attribute, selecting that field will calculate centers per district. This method is discussed further in cluster analysis.

Result

Three point layers representing the Mean Center, Median Center, and Central Feature are created.