Datasets: The dataset includes the number of trips in the US, the number of people staying home and not staying home for Week1 – 32 (Trips_by_Distance.csv) and the Full-distance data for one of the 32 weeks (Trips_Full_Data.csv). BTS are provided with a large volume of data to process, and the analysis needs to be repeated frequently. They are interested in answers to the questions given below. Please support your analysis of each question with Python code and graphical plots / graphical visualizations. Questions: a. How many people are staying at home per week? How far are people travelling when they don’t stay home all week? b. Identify the dates that more than 10,000,000 people conducted 10-25 Number of Trips and compare them using a scatterplot to when the same number of people (> 10,000,000) conducted 50-100 Number of trips. Please discuss and evaluate your outcomes. c. Develop a model to predict the frequency of people to travel taking into consideration the length of the trip (scatterplot is expected) and evaluate the model performance using the appropriate metrics (i.e. RMSE, R2). Please discuss and evaluate the quality of your modelling outcomes. d. Visualize the number of travellers by distance-trips, display the visual (plots), and, discuss and critically evaluate the outcomes. Answer the above questions (a.– d.) using sequential processing vs parallel computing (with 10 and 20 processors) while displaying your outcomes using the appropriate figures (tables/plots).