Exercise $2$ Data Preprocessing and Visualization

Using the given BENGALURU HOUSE PRICES DATASET, perform data preprocessing

and answer the following questions.

Find the missing values in the DataFrame and replace them with the right missing values.

However, if a column has more than $15\%$ missing values then drop $($or remove$)$ the column

from the DataFrame except for the location, size and total$\_$sqft columns because the house

prices are directly dependent on these three crucial parameters. In fact, the rate of a house is

reported as a cost per unit area of the house.

Drop $($or remove$)$ the rows containing the missing values in the location, size, and total$\_$sqft

columns. Additionally, drop any row which contains nonsensical values in the context of

houses.