Interpreting the skgstat variogram plot

Question

I'm attempting to use a variogram to understand some spatial data I'm working with - but I'm having trouble interpreting some part of the results when I plot this data and its distribution. Please bare with me! I'll give you an example, the accompanying plot, and ask questions here.

Example Code

import numpy as np
import skgstat as skg

coordinates = np.random.rand(10)*10
values = np.random.rand(10)*10
 
V = skg.Variogram(coordinates=coordinates, values=values,n_lags=5)
print(V)
V.plot()

Output

spherical Variogram
-------------------
Estimator:         matheron
Effective Range:   2.33
Sill:              10.72
Nugget:            0.00

I understand the sill/nugget/estimator and such, but I'm confused with these things:

1. Primarily - I have 10 random values for my coordinates. Why on earth does the sum of the attached histogram display over thirty samples included? What are these representing?
2. Does the lag necessarily represent the equivalent X value?

Answer 1

I've realized what I'm interpreting in the Histogram.

The N doesn't necessarily denote the number of samples - but instead the number of pairs denoted by:

npairs = n(n-1)/2. 

This works out to be the same quantity of points available in the histogram.