QuestionQuestion

Introduction
The lab is about finding and evaluating clusters that contains data with similar properties.

Your task
The lab is about discovering some new places here in Se that may be suitable for IKEA department stores. You shall do this by using the k-means method. To your help, you have a text file, data.txt, which contains important features for many of Sweden's municipalities. In this context may the English term municipality be translated to the Sv term kommun. There are already existing IKEA-stores in the municipalities Haparanda, Helsingborg, Jönköping, Kalmar, Karlstad, Linköping, Malmö, Stockholm, Uddevalla, Uppsala, Älmhult and Örebro.

You are free to use the development environment that you think is most practical for this task, to run the k-mean method and draw diagrams; R or Excel.

Solution PreviewSolution Preview

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install.packages("cluster")
install.packages("fpc")
library(cluster)
library(fpc)
set.seed(123)

#PART 1: Preparing the data

#Reading data into R data frame
df <- read.csv("data.txt", sep = "\t")

#Taking features for clustering

ikea <- as.matrix(df[,4:12]) #9 features

#Row names

rownames(ikea) <- df$Kommun_name...
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