My question seems a little bit vague. Put it in this way:
I have a set of coordinates(latitude and longitude) in an area(a city) and I want to quantify their separation. for example, they will get a low score if they are all at the same location(actually this should be the lowest score), and they will get a high score if they are very separated. For example, if you imagine how a set of charges would arrange themselves on a circular conducting plate, that should maximise their separation- this state would get the highest "separation" score.
As I have thousands of coordinates in the area, so I want to find a very efficient way to calculate that. Another problem I am thinking about is that: my coordinates are all latitude and longitude which cannot reflect the distance in meter correspondingly (i.e., at different latitudes, same longitude difference corresponds to different distance in meter), so should I also consider this in the spread calculation?
So does anyone know of any algorithms or approaches or theory I can use to do this, in the most mathematically respectable way? I am a newbie in this concept and in python, and I appreciate it a lot if you could give me some ideas.
Thank you all, Gladys