如何使用分类和数值数据is R创建分层集群？

Question

I want to create a hierarchical cluster to show types of careers and the balance that those who are in those careers have in their bank account. I a dataset with two variables, job and balance:

              job balance
1       unemployed    1787
2         services    4789
3       management    1350
4       management    1476
5      blue-collar       0
6       management     747
7    self-employed     307
8       technician     147
9     entrepreneur     221
10        services     -88

I want the result to look like this:

Where A, B ,C etc are the job categories.

Can anyone help me start this or give me some help?

I have no idea how to begin.

Thanks!

Answer 1

You can start by using the dist and hclust functions.

df <- read.table(text = "              job balance
1       unemployed    1787
2         services    4789
3       management    1350
4       management    1476
5      blue-collar       0
6       management     747
7    self-employed     307
8       technician     147
9     entrepreneur     221
10        services     -88")

dist computes the distance between each element (by default, the euclidian distance):

distances <- dist(df$balance)

You can then cluster you values using the distance matrix generated above:

clusters <- hclust(distances)

By default, hclust applies complete-linkage clustering to your data. Finally, you can plot your results as a tree:

plot(clusters, labels = df$job)

Here, we clustered all the entries in your data frame, that's why some jobs are duplicated. If you want to have a single value per job, you can for example take the mean balance for each job using tapply :

means <- tapply(df$balance, df$job, mean)

And then cluster the jobs:

distances <- dist(means)
clusters <- hclust(distances)
plot(clusters)

You can then try to use other distance measures or other clustering algorithms (see help(dist) and help(hclust) for other methods).