Complete a regression analysis on the data set flight price.csv$.$ The dataset contains information on flights for Indian airline companies. The goal is to predict flight prices, which is the last column in the data set.

Review the notes found in full$\_$classification.html to learn how to preprocess the data.

Apply the following steps.

Delete the two columns 'Unnamed: $0\text{'}$ and 'flight'.

Split the dataset using the code

flight$\_$train, flight$\_$test $=$ train$\_$test$\_$split$($flight$,$ random$\_$state $=2,$ train$\_$size $=250000,$ shuffle $=$ True$)$

Show statistical values for numerical attributes.

Show frequency values for categorical attributes.

Preprocess the training data similarly to what was done in full$\_$classification.html$.$

Train a regression model on the training data. Use the algorithm RandomForestRegressor$($random$\_$state$=1).$

Apply the same preprocessing on the test data.

Make predictions on the test data.

Output the log mean squared error: np$.$log$($np$.$mean$($np$.$square$($y$\_$pred $-$ y$\_$test$)))$

The value I obtain is $15\mathrm{.}8.$