Use the Cars93 data set from the built-in package "MASS" available in R.

You are to analyse the data using unsupervised learning.

1) Preparing the data

CAN YOU JUST POST THE CODE FROM R FOR ME PLEASE; THIS IS JUST AN IDEA, DOESNT HAVE TO BE THE SAME

Preparing the data

Move "Model" to column1. One way is to use the dplyr library from the tidyverse package.

Let the model names be your rownames (not to be used as data, but will be the name of each row). See James textbook, page 55 for some guidance.

Ensure that the data is complete before doing the analysis. Look for "NA" entries, especially in the "Rear.seat.room" and "Luggage.room" columns. You may choose to replace "NA" with 0.

Look at the spelling of "Chrysler" as you go down the column. Fix the error.

"Cylinders" has a non-numeric term. Make an appropriate decision.

If necessary, replace qualitative data with quantitative data.

For binary data, e.g. Origin: USA/non-USA can be coded 1 or 0. Do you need two columns, or one? You can use the dummy( ) function from the dummies package.