1) Explore the numerical predictors and outcome (FARE) by creating a correlation table,
heat map, and examining some scatterplots between FARE and those predictors. What
seems to be the best single predictor of FARE?
2) Explore the categorical predictors (Excluding the first four) by creating the pivot table
with the average fare in each category. Which categorical predictors seems best for
predicting FARE?
3)Find a model with the regression model for predicting the average fare on a new route:
(3.1) Convert categorical variables into dummy variables. Then, partition the data
into training and test sets. The model will be fit to the training data and
evaluated on the test set.
PLEASE USE PYTHON , JUPYTER NOTEBOOK
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