Challenge: Preparing a Dataset for Machine Learning

You are given a flights dataset as a list of rows. Load it into a DataFrame using createDataFrame and prepare it for a binary classification task – predicting whether a flight is delayed (Delay == 1). Complete all steps and store results in the specified variables:

1. Fill nulls in Delay and Length with 0;
2. Add a binary label column LABEL – 1 if Delay == 1, otherwise 0;
3. Add IS_WEEKEND – 1 if DayOfWeek >= 6, otherwise 0;
4. Apply StringIndexer to Airline → AIRLINE_IDX;
5. Assemble Length, Time, IS_WEEKEND, and AIRLINE_IDX into a vector column FEATURES;
6. Store the final DataFrame in ml_df and count its rows in ml_count.

Print ml_count and show all rows of LABEL, AIRLINE_IDX, FEATURES.