You want to make a dendrogram to show how items are clustered.

Use hclust() and plot the output from it. This can require a fair bit of data preprocessing. For this example, we’ll first take a subset of the countries data set from the year 2009. For simplicity, we’ll also drop all rows that contain an NA, and then select a random 25 of the remaining rows:

library(gcookbook) # For the data set

# Get data from year 2009
c2 <- subset(countries, Year==2009)

# Drop rows that have any NA values
c2 <- c2[complete.cases(c2), ]

# Pick out a random 25 countries
# (Set random seed to make this repeatable)
set.seed(201)
c2 <- c2[sample(1:nrow(c2), 25), ]

c2

                  Name Code Year        GDP laborrate  healthexp infmortality
6731          Mongolia  MNG 2009  1690.4170      72.9   74.19826         27.8
1733            Canada  CAN 2009 39599.0418      67.8 4379.76084          5.2
 ...
5966    Macedonia, FYR  MKD 2009  4510.2380      54.0  313.68971         10.6
10148     Turkmenistan  TKM 2009  3710.4536      68.0   77.06955         48.0