widely_hclust {widyr}

Cluster pairs of items into groups using hierarchical clustering

Description

Reshape a table that represents pairwise distances into hierarchical clusters, returning a table with item and cluster columns.

Usage

widely_hclust(tbl, item1, item2, distance, k = NULL, h = NULL)

Arguments

tbl

Table

item1

First item

item2

Second item

distance

Distance column

k

The desired number of groups

h

Height at which to cut the hierarchically clustered tree

See Also

cutree

Examples

library(gapminder)
library(dplyr)

# Construct Euclidean distances between countries based on life
# expectancy over time
country_distances <- gapminder %>%
  pairwise_dist(country, year, lifeExp)

country_distances

# Turn this into 5 hierarchical clusters
clusters <- country_distances %>%
  widely_hclust(item1, item2, distance, k = 8)

# Examine a few such clusters
clusters %>% filter(cluster == 1)
clusters %>% filter(cluster == 2)