The lab is about finding and evaluating clusters that contains data with similar properties.
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.
This material may consist of step-by-step explanations on how to solve a problem or examples of proper writing, including the use of citations, references, bibliographies, and formatting. This material is made available for the sole purpose of studying and learning - misuse is strictly forbidden.install.packages("cluster")
#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
rownames(ikea) <- df$Kommun_name...