str(data)

## 'data.frame':    4526 obs. of  12 variables:
##  $ Posted.On        : Date, format: "2022-05-18" "2022-05-13" ...
##  $ BHK              : num  2 2 2 2 2 2 2 1 2 2 ...
##  $ Rent             : num  10000 20000 17000 10000 7500 7000 10000 5000 26000 10000 ...
##  $ Size             : num  1100 800 1000 800 850 600 700 250 800 1000 ...
##  $ Floor            : chr  "Ground out of 2" "1 out of 3" "1 out of 3" "1 out of 2" ...
##  $ Area.Type        : chr  "Super Area" "Super Area" "Super Area" "Super Area" ...
##  $ Area.Locality    : chr  "Bandel" "Phool Bagan, Kankurgachi" "Salt Lake City Sector 2" "Dumdum Park" ...
##  $ City             : chr  "Kolkata" "Kolkata" "Kolkata" "Kolkata" ...
##  $ Furnishing.Status: chr  "Unfurnished" "Semi-Furnished" "Semi-Furnished" "Unfurnished" ...
##  $ Tenant.Preferred : chr  "Bachelors/Family" "Bachelors/Family" "Bachelors/Family" "Bachelors/Family" ...
##  $ Bathroom         : num  2 1 1 1 1 2 2 1 2 2 ...
##  $ Point.of.Contact : chr  "Contact Owner" "Contact Owner" "Contact Owner" "Contact Owner" ...

link

table(data$Area.Type)

## 
##  Built Area Carpet Area  Super Area 
##           2        2100        2424

table(data$BHK)

## 
##    1    2    3    4    5    6 
## 1166 2248 1004   95    6    7

table(data$Bathroom)

## 
##    1    2    3    4    5    6    7 
## 1474 2276  673   80   16    5    2

table(data$City)

## 
## Bangalore     Delhi Hyderabad   Chennai   Kolkata    Mumbai 
##       875       586       860       880       523       802

table(data$Furnishing.Status)

## 
##      Furnished Semi-Furnished    Unfurnished 
##            613           2129           1784

c(min(as.Date(data$Posted.On)), max(as.Date(data$Posted.On)))

## [1] "2022-04-23" "2022-07-11"

data <- data[data$Area.Type == "Carpet Area", ]
data <- data[data$BHK <= 3, ]
data <- data[data$City == "Mumbai", ]

str(data)

## 'data.frame':    648 obs. of  5 variables:
##  $ Rent             : num  70000 45000 75000 33000 32000 30000 28000 33500 85000 35000 ...
##  $ Size             : num  750 450 1100 480 500 490 518 700 777 650 ...
##  $ BHK              : num  2 1 3 1 1 1 2 2 2 2 ...
##  $ Furnishing.Status: chr  "Furnished" "Furnished" "Unfurnished" "Semi-Furnished" ...
##  $ Bathroom         : num  2 1 3 2 2 2 2 2 2 2 ...

summary(data)

##       Rent             Size             BHK        Furnishing.Status 
##  Min.   :  5500   Min.   : 160.0   Min.   :1.000   Length:648        
##  1st Qu.: 32000   1st Qu.: 500.0   1st Qu.:1.000   Class :character  
##  Median : 48000   Median : 700.0   Median :2.000   Mode  :character  
##  Mean   : 52943   Mean   : 721.7   Mean   :1.909                     
##  3rd Qu.: 70000   3rd Qu.: 888.0   3rd Qu.:2.000                     
##  Max.   :130000   Max.   :1600.0   Max.   :3.000                     
##     Bathroom    
##  Min.   :1.000  
##  1st Qu.:2.000  
##  Median :2.000  
##  Mean   :2.029  
##  3rd Qu.:2.000  
##  Max.   :5.000