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Pro90 ProblemsSQL + Python

Lodging SQL & Python Interview Questions

Booking platforms analyze reservation data, host performance, and pricing dynamics across global markets. These SQL and Python challenges are modeled after work at Airbnb, Booking.com, Expedia, Marriott, Hilton, Hyatt, VRBO, Wyndham, Tripadvisor, IHG, and more. Practice occupancy rate analysis, RevPAR calculation, pricing optimization, booking lead time trends, and host quality metrics.

Lodging

90 total problems

SQL45
Python45
Practice SQLPractice Python
Companies working in Lodging

These practice problems are modeled after the kind of data and analytics challenges teams in this industry typically face.

Airbnb
Airbnb
Booking.com
Booking.com
Expedia
Expedia
Marriott
Marriott
Hilton
Hilton
Hyatt
Hyatt
Wyndham
Wyndham
Choice Hotels
Choice Hotels
IHG
IHG
VRBO
VRBO
Tripadvisor
Tripadvisor
Hopper
Hopper
OYO
OYO
Sonder
Sonder
Vacasa
Vacasa
Cloudbeds
Cloudbeds
RateGain
RateGain
Duetto
Duetto
IDeaS
IDeaS
AirDNA
AirDNA

Company names and logos are trademarks of their respective owners, used here only to describe the kind of data these companies work with. Let's Data Science is not affiliated with, endorsed by, or sponsored by any company shown. Practice problems are original works and are not real interview questions from these companies. Rights & takedowns.

Difficulty Breakdown

90 problems
15 Easy(17%)
32 Medium(36%)
38 Hard(42%)
5 Expert(6%)

What You'll Practice

Occupancy rate analysisRevPAR calculationsBooking funnel metricsHost performance scoringPricing optimizationSeasonal demand patternsGuest satisfaction analysisMarket penetration

Topics Covered

21 topics
SQL · 9
aggregationbasic queries filteringcleaning transformdate timejoinsscenario sqlset operationssubqueries cteswindow functions
Python · 12
eda statisticsfeature engineeringpandas aggregationpandas applypandas basicspandas cleaningpandas datetimepandas filteringpandas mergingpandas reshapingpandas scenariopandas window

All Problems90 total

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