arunprsh / SageMaker-Data-Wrangler-L400-Workshop

SageMaker Data-Wrangler L400 Workshop

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SageMaker Data Wrangler L400 Workshop

Use Case

  • Predict hotel booking cancellations

Dataset

  • Hotel Booking Demand dataset - This data set contains booking information for a city hotel and a resort hotel, and includes information such as when the booking was made, length of stay, the number of adults, children, and/or babies, and the number of available parking spaces, among other things.

    Hotel Booking

Description of the columns

Column Name Description
hotel Type of the hotel (H1 = Resort Hotel or H2 = City Hotel)
is_canceled Value indicating if the booking was canceled (1) or not (0)
lead_time Number of days that elapsed between the entering date of the booking into the PMS and the arrival date
arrival_date_year Year of arrival date
arrival_date_month Month of arrival date
arrival_date_week_number Week number of year for arrival date
arrival_date_day_of_month Day of arrival date
stays_in_weekend_nights Number of weekend nights (Saturday or Sunday) the guest stayed or booked to stay at the hotel
stays_in_week_nights Number of week nights (Monday to Friday) the guest stayed or booked to stay at the hotel
adults Number of adults
children Number of children
babies Number of babies
meal Type of meal booked. Categories are presented in standard hospitality meal packages: Undefined/SC – no meal package; BB – Bed & Breakfast; HB – Half board (breakfast and one other meal – usually dinner); FB – Full board (breakfast, lunch and dinner)
country Country of origin. Categories are represented in the ISO 3155–3:2013 format
market_segment Market segment designation. In categories, the term TA means “Travel Agents” and TO means “Tour Operators”
distribution_channel Booking distribution channel. The term TA means “Travel Agents” and TO means “Tour Operators”
is_repeated_guest Value indicating if the booking name was from a repeated guest (1) or not (0)
previous_cancellations Number of previous bookings that were cancelled by the customer prior to the current booking
previous_bookings_not_canceled Number of previous bookings not cancelled by the customer prior to the current booking
reserved_room_type Code of room type reserved. Code is presented instead of designation for anonymity reasons.
assigned_room_type Code for the type of room assigned to the booking. Sometimes the assigned room type differs from the reserved room type due to hotel operation reasons (e.g. overbooking) or by customer request. Code is presented instead of designation for anonymity reasons.
booking_changes Number of changes/amendments made to the booking from the moment the booking was entered on the PMS until the moment of check-in or cancellation
deposit_type Indication on if the customer made a deposit to guarantee the booking. This variable can assume three categories: No Deposit – no deposit was made; Non Refund – a deposit was made in the value of the total stay cost; Refundable – a deposit was made with a value under the total cost of stay.
agent ID of the travel agency that made the booking
company ID of the company/entity that made the booking or responsible for paying the booking. ID is presented instead of designation for anonymity reasons
days_in_waiting_list Number of days the booking was in the waiting list before it was confirmed to the customer
customer_type Type of booking, assuming one of four categories: Contract - when the booking has an allotment or other type of contract associated to it; Group – when the booking is associated to a group; Transient – when the booking is not part of a group or contract, and is not associated to other transient booking; Transient-party – when the booking is transient, but is associated to at least other transient booking
adr Average Daily Rate as defined by dividing the sum of all lodging transactions by the total number of staying nights
required_car_parking_spaces Number of car parking spaces required by the customer
total_of_special_requests Number of special requests made by the customer (e.g. twin bed or high floor)
reservation_status Reservation last status, assuming one of three categories: Canceled – booking was canceled by the customer; Check-Out – customer has checked in but already departed; No-Show – customer did not check-in and did inform the hotel of the reason why
reservation_status_date Date at which the last status was set. This variable can be used in conjunction with the ReservationStatus to understand when was the booking canceled or when did the customer checked-out of the hotel

Outline

Machine Learning Life Cycle

Data Preparation

Amazon SageMaker

Data Wrangler

Getting started with Data Wrangler

Exploratory Data Analysis (in progress)

Data Transformations (in progress)

Integration with other SageMaker components (in progress)

Security & Permissions (in progress)

Multi-account Patterns (in progress)

Useful Resources (in progress)


Contributors

Contributor Alias
Arunprasath Shankar arunprsh@
Vadim Omeltchenko vadimo@
Aleksandr Patrushev patrushe@
Jason Nicholls nicjas@
Yevgeniy Ilyin ilyiny@
Neelam Koshiya nkkoshiy@
Peter Chung pechung@
Amogh Gaikwad gaiamogh@
Alex Voitau voitau@
Amogh Gaikwad gaiamogh@

About

SageMaker Data-Wrangler L400 Workshop

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