Spatial analysis · 4 min
Count points inside each area
Customers per territory, crimes per ward, shops per county, and why raw counts can mislead.
Spatial analysis
From dots to a table
A map with a thousand dots is hard to read. Counting how many fall in each area turns it into a table: 140 customers in the North, 85 in the West.
This is the flip side of tagging. Tagging writes the area onto each point; counting writes the number of points onto each area.
Lesson notes
Everything from the cards above, on one page to come back to.
From dots to a table
A map with a thousand dots is hard to read. Counting how many fall in each area turns it into a table: 140 customers in the North, 85 in the West.
This is the flip side of tagging. Tagging writes the area onto each point; counting writes the number of points onto each area.
Counts favour big areas
A big area usually holds more of everything simply because it is big. A raw count can make a huge rural county look busier than a small, packed city.
Divide by the area to get a density (per km²), or by the population to get a rate (per 1,000 people). Then areas of different sizes can be compared.
More than a count
If the points carry a number, such as sales, you can add it up per area as well: total sales per territory, or the average or highest.
In MapGO this is Count points in polygons, in the Process tools. It adds a count column to every area, and optionally the sum, mean, lowest or highest of a number column. A point on a shared edge counts in both areas.
Questions
How do I count points in polygons without GIS software?
Put both layers on the MapGO workspace map and run Count points in polygons from the Process tools. It runs in your browser.
Should I map counts or densities?
When areas differ a lot in size, densities (per km²) or rates (per person) compare fairly. Raw counts mostly show which areas are biggest.