how do I make R markdown and what to put in it to display these thing for my code below:

# Step $1$: Read and Load Data

$>$ housing$\_$data $<-$ read.csv$("$Housing$.$csv$",$ stringsAsFactors $=$ TRUE$)$

$>$

$>$ # Print first $10$ observations to verify

$>$ head$($housing$\_$data, $10)$

price area bedrooms bathrooms stories mainroad guestroom basement hotwaterheating

$1133000007420423$ yes no no no

$2122500008960444$ yes no no no

$3122500009960322$ yes no yes no

$4122150007500422$ yes no yes no

$5114100007420412$ yes yes yes no

$6108500007500331$ yes no yes no

$7101500008580434$ yes no no no

$81015000016200532$ yes no no no

$998700008100412$ yes yes yes no

$1098000005750324$ yes yes no no

airconditioning parking prefarea furnishingstatus

$1$ yes $2$ yes furnished

$2$ yes $3$ no furnished

$3$ no $2$ yes semi$-$furnished

$4$ yes $3$ yes furnished

$5$ yes $2$ no furnished

$6$ yes $2$ yes semi$-$furnished

$7$ yes $2$ yes semi$-$furnished

$8$ no $0$ no unfurnished

$9$ yes $2$ yes furnished

$10$ yes $1$ yes unfurnished

$>$

$>$ # Step $2$: Subset Columns

$>$ housing$\_$data $<-$ housing$\_$data$[,$ c$("$price$",$ "area", "bedrooms", "stories", "basement", "furnishingstatus"$)]$

$>$

$>$ # Step $3$: Determine Variable Types

$>$ str$($housing$\_$data$)$

'data.frame': $545$ obs. of $6$ variables:

$ price : int $133000001225000012250000122150001141000010850000101500001015000098700009800000...$

$ area : int $74208960996075007420750085801620081005750...$

$ bedrooms : int $4434434543...$

$ stories : int $3422214224...$

$ basement : Factor w$/2$ levels $"$no$",$"yes": $1122221121...$

$ furnishingstatus: Factor w$/3$ levels "furnished","semi$-$furnished",..: $1121122313...$

$>$

$>$ # Step $4$: Summary Statistics

$>$ summary$($housing$\_$data$)$

price area bedrooms stories basement

Min. : $1750000$ Min. : $1650$ Min. :$1\mathrm{.}000$ Min. :$1\mathrm{.}000$ no :$354$

$1$st Qu$.$: $34300001$st Qu$.$: $36001$st Qu$.$:$2\mathrm{.}0001$st Qu$.$:$1\mathrm{.}000$ yes:$191$

Median : $4340000$ Median : $4600$ Median :$3\mathrm{.}000$ Median :$2\mathrm{.}000$

Mean : $4766729$ Mean : $5151$ Mean :$2\mathrm{.}965$ Mean :$1\mathrm{.}806$

$3$rd Qu$.$: $57400003$rd Qu$.$: $63603$rd Qu$.$:$3\mathrm{.}0003$rd Qu$.$:$2\mathrm{.}000$

Max. :$13300000$ Max. :$16200$ Max. :$6\mathrm{.}000$ Max. :$4\mathrm{.}000$

furnishingstatus

furnished :$140$

semi$-$furnished:$227$

unfurnished :$178$

$>$

$>$ # Step $5$: Create Bar Charts for Factors

$>$ # Bar chart for basement

$>$ barplot$($table$($housing$\_$data$basement$),$ main $=$ "Basement", xlab $=$ "Basement", ylab $=$ "Frequency"$)$

$>$

$>$ # Bar chart for furnishingstatus

$>$ barplot$($table$($housing$\_$data$furnishingstatus$),$ main $=$ "Furnishing Status", xlab $=$ "Furnishing Status", ylab $=$ "Frequency"$)$

$>$

$>$ # Step $6$: Create Histograms

$>$ # Histogram for price

$>$ hist$($housing$\_$data$price, main $=$ "Histogram of Price", xlab $=$ "Price"$)$

$>$

$>$ # Histogram for area

$>$ hist$($housing$\_$data$area, main $=$ "Histogram of Area", xlab $=$ "Area"$)$

$>$

$>$ # Step $7$: Create Scatter Plot

$>$ plot$($housing$\_$data$area, housing$\_$data$price, main $=$ "Scatter Plot of Price vs$.$ Area", xlab $=$ "Area", ylab $=$ "Price"$)$

$>$

$>$ # Step $8$: Subset Data

$>$ housing$\_$basement $<-$ housing$\_$data$[$housing$\_$data$basement $==$ "yes", $]$

$>$

$>$ # Print first few lines

$>$ head$($housing$\_$basement$)$

price area bedrooms stories basement furnishingstatus

$312250000996032$ yes semi$-$furnished

$412215000750042$ yes furnished

$511410000742042$ yes furnished

$610850000750031$ yes semi$-$furnished

$99870000810042$ yes furnished

$1198000001320032$ yes furnished

$>$

$>$ # Step $9$: Create Pie Chart

$>$ pie$($table$($housing$\_$basement$furnishingstatus$),$ main $=$ "Furnishing Status Distribution"$)$

$>$

$>$ # Step $1$: Read and Load the Data

$>$ housing$\_$data $<-$ read.csv<