sales price prediction
We should not use time series concept here. You have to do a pair plot analysis to find your best predictor. I do not think index column is much useful here. I feel length, width or breadth are features if you classify the vehicles as sedan, suv or small car. Not sure if it be of much help in predicting the price. If you add more breadth to the dataset, make sure you have enough depth or training examples

Do a heat map and find the co-relation between the feature and target variable as well. You can remove those features which does not have good co-relation with the target variable.

Try to start with Linear regression model, since you have to predict the price. then move on to more complex models. Random forest regressor is also a good choice for smaller datasets