Passenger demand data for a transportation company 2014

The data is of booking attempts of passengers for seats for point to point travel between cities. The booking attempts are captured irrespective of capacity constraints and hence include seat allocated, on hold for reservation on the same or alternate vehicle, or refunded due to unavailability. However customer initiated cancellations are deducted from booking attempts. The data is anonymized to protect corporate information. The fields of the given comma separated csv files are as below First row is header. Total number of data rows: 923822 a) booking_key : Primary key. Unique for each booking. b) travel_dt : date of the travel c) time_of_day: This is intended departure time of the journey from boarding city. This is broken into different time groups of a 24 hour day. Defined as Departure Time BETWEEN '00:00:01' AND '01:00:00' THEN 1 Departure Time BETWEEN '01:00:01' AND '09:00:00' THEN 2 Departure Time BETWEEN '09:00:01' AND '12:00:00' THEN 3 Departure Time BETWEEN '12:00:01' AND '15:00:00' THEN 4 Departure Time BETWEEN '15:00:01' AND '18:00:00' THEN 5 Departure Time BETWEEN '18:00:01' AND '21:00:00' THEN 6 Departure Time BETWEEN '21:00:01' AND '24:00:00' THEN 7 d) from_city : unique code number of the city (boarding ) e) to_city : unique code number of the city (deboarding) f) adjusted demand : (Booking + on_hold + refunded ) - Cancellation g) booking_tstamp : TImestamp of the booking. Necessary to create an incremental demand chart h)week_day : day of the week Monday = 0, Sunday = 6. j) Week_of_Year : Week of the year The data is ordered by travel_dt, time_of_day, from_city, to_city. The data is generated by MySQL database using MYSQL syntax.