RESALE VALUE PREDICTION

Introduction:-

The purpose of this project is to predict price of used cars and bikes as it is
difficult with this economic condition to predict. The prices of new cars in the industry is fixed by the manufacturing company with some additional costs added by the Government in the form of taxes. So, customers buying a new car can be assured of the money they invest to be necessary. But due to the increased price of new cars customers can’t buy new cars which are of high cost. There is a need for a used car price prediction system to effectively determine the necessity of the car using a variety of features. Even though there are websites that offers this service, their prediction method may not be the best. Besides, different models and systems may contribute on predicting power for a used car’s actual market value. It is important to know their actual market value while both buying and selling.

by predicting used cars (0r) bikes the market value can help both buyers and sellers. If used car owners understand what makes a car good, what the important features in the used car, then they may consider this features and offer a better service.

PROBLEMS OCCURED:-

So sns.scatterplot() has no base function which can plot the values.
hence it fails to print a plot of the values as no previous plt (plot) objects were creating hence here we are creating a function for plotting the values thereby removing this error and giving reusability for the function for later future use to plot diagrams for better visualization

Here the Seller has only one value, while offerType and a/b test are not closely connected for the analysis. I still don’t know how to use the dateCrawled column. Therefore I modify the dataframe dropping all those features. I remove lastSeen, dateCreated and postalCode as well as because don't think they will be useful for a price prediction.