$1.$ Load the R data LifeCycleSavings, from the datasets package, in your R session.

Marks $(1)$

$2.$ Use the values of the variable pop$15$ and ddpi to create two new categorical variables named Pop$15$Cat and ddpiCat, respectively, each with three categories, $$High$($top $25\%),$Medium$($ middle $50\%)$ and $$low$($bottom $25\%).$ Show your codes.

$1.$ Hint: To do this, you must find a function to obtain the required cut$-$off points and then another function to implement the binning of the variables. Marks $(4)$

$3.$ Count $($frequency of$)$ cases within each new categorical variable. Show codes and output. Marks $(2)$

$4.$ Use a visualization tool to display the relationship between the variables,

sr and Pop$15$Cat, stratified by ddpiCat, on a single plot.

Comment on the plot $$ do you observe any relationship between the three variables?

You must use ggplot$2$ for visualization. Wherever applicable, your plots must have proper labelling and legends. Marks $(5)$

please provide me code and explaination.