Helper to make a conditionally formatted table of kmeans centroids with ggplot2

plot_centroids_table.R

library(ggplot2)
library(dplyr)
library(tidyr)

plot_centroids_table <- function(kmeans_object) {
  n_clusters <- nrow(kmeans_object$centers)

  plot_df <- data.frame(t(kmeans_object$centers))
  names(plot_df) <- paste("Cluster", 1:n_clusters)
  plot_df$feature_name <- rownames(plot_df)
  plot_df <- pivot_longer(plot_df, cols = -feature_name)

  ggplot(plot_df, aes(x = name, y = feature_name, fill = value)) +
    geom_tile() +
    geom_text(aes(label = round(value, 2)), color = "white") +
    labs(x = "", y = "")
}

plot_mean_by_label_table <- function(your_data, label_column,
                                     summary_func = mean,
                                     drop_cols = c()) {
  your_data[, drop_cols] <- NULL

  your_data$group_name <- paste("Cluster", your_data[[label_column]])
  your_data[[label_column]] <- NULL

  plot_df <- your_data |>
    group_by(group_name) |>
    summarise_all(summary_func) |>
    pivot_longer(-group_name)

  ggplot(plot_df, aes(x = group_name, y = name, fill = value)) +
    geom_tile() +
    geom_text(aes(label = round(value, 2)), color = "white") +
    labs(x = "", y = "")
}