Compute cluster centroids (mean x/y per cluster) — compute

Computes the centroid of each cluster by taking the mean of the `x` and `y` coordinates for each `cluster` level.

Usage

compute_centroids(df)

Arguments

df: A `data.frame` containing at least the columns `cluster`, `x`, and `y`. `cluster` can be any type accepted by `aggregate()` grouping (e.g., integer, factor, character). `x` and `y` must be numeric.

Value

A `data.frame` with one row per cluster and columns:

cluster: Cluster identifier.
x: Mean x-coordinate for the cluster.
y: Mean y-coordinate for the cluster.

Details

This is a thin wrapper around aggregate using FUN = mean. Missing values are handled according to `mean()`'s default behavior (i.e., `NA`s will propagate unless you pre-handle them).

Examples

df <- data.frame(
  cluster = c(1, 1, 2, 2),
  x = c(0, 2, 10, 12),
  y = c(1, 3, 5, 7)
)
compute_centroids(df)
#>   cluster  x y
#> 1       1  1 2
#> 2       2 11 6