Kmeans: Wrong size of clusters

I am running Kmeans algorithm in R on Heart Disease UCI dataset. I am supposed to get 2 clusters with 138 165 size for each like what in the data set.

Steps:

1. Store dataset in a data frame:

df <- read.csv(".../heart.csv",fileEncoding = "UTF-8-BOM")

2. Extract the features:

features = subset(df, select = -target)

3. Normalize it:

normalize <- function(x) {
  return ((x - min(x)) / (max(x) - min(x)))
}

features = data.frame(sapply(features, normalize))

4. Run the algorithm:

set.seed(0)
cluster = kmeans(features, 2)
cluster$size

Output:

[1]  99 204

Why?