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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
Top Companies Hiring in Lodging

Questions are relevant for real analytics problems data science teams solve at these companies.

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

Difficulty Distribution

Easy

15

17% of problems

Medium

32

36% of problems

Hard

38

42% of problems

Expert

5

6% of problems

What You'll Practice

Occupancy rate analysis
RevPAR calculations
Booking funnel metrics
Host performance scoring
Pricing optimization
Seasonal demand patterns
Guest satisfaction analysis
Market 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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01
Active Five-Star HotelsPro
SQLEasy
02
Refundable Rate PlansPro
SQLEasy
03
Ocean View King Bed RoomsPro
SQLEasy
04
High-Value Direct BookingsPro
SQLMedium
05
Platinum Guests With EmailPro
SQLEasy
06
Reservations With Property DetailsPro
SQLEasy
07
Bookings With Guest and Room InfoPro
SQLMedium
08
Reservations With Cancellation PolicyPro
SQLMedium
09
Guest Reviews With Property ContextPro
SQLMedium
10
Room Types Never Booked DirectlyPro
SQLHard
11
Guests Who Never Left a ReviewPro
SQLMedium
12
Booking Volume by ChannelPro
SQLEasy
13
Total Revenue per PropertyPro
SQLMedium
14
Average Nightly Rate by Room TypePro
SQLMedium
15
Cancellation Rate by Booking ChannelPro
SQLMedium
16
Top 5 Guests by Lifetime SpendPro
SQLHard
17
Properties With High No-Show RatePro
SQLHard
18
Rank Properties by Total RevenuePro
SQLMedium
19
Guest Booking Sequence NumberPro
SQLMedium
20
Daily Revenue Running Total per PropertyPro
SQLHard
21
Most Expensive Booking per PropertyPro
SQLHard
22
Property Rating With 3-Review Moving AveragePro
SQLHard
23
Revenue Change From Prior BookingPro
SQLHard
24
Room Occupancy Quartile AnalysisPro
SQLHard
25
Properties Above Average RevenuePro
SQLMedium
26
Guests Booking Direct and OTAPro
SQLHard
27
Latest Booking per GuestPro
SQLHard
28
Revenue Summary With Rank via CTEPro
SQLHard
29
Channels With Above-Average ADRPro
SQLHard
30
Recent Bookings in August 2024Pro
SQLEasy
31
Monthly Booking Volume TrendPro
SQLMedium
32
Average Booking Lead Time by ChannelPro
SQLMedium
33
Late Cancellations Within Free PeriodPro
SQLHard
34
Bookings With Stay Length CategoryPro
SQLEasy
35
Revenue With Commission Tier LabelPro
SQLMedium
36
Guest Loyalty Status NormalizedPro
SQLHard
37
Properties With Bookings or ReviewsPro
SQLMedium
38
Guests Who Booked But Never ReviewedPro
SQLMedium
39
Property Revenue ScorecardPro
SQLHard
40
Channel Performance ReportPro
SQLHard
41
Guest Lifetime Value SummaryPro
SQLHard
42
Cancellation and No-Show Financial ImpactPro
SQLHard
43
Payment Reconciliation AuditPro
SQLHard
44
Property Operations DashboardPro
SQLExpert
45
OTA Commission vs Direct Booking AnalysisPro
SQLHard
46
Active Property ProfilesPro
PYTHONEasy
47
Room Type Bed DistributionPro
PYTHONEasy
48
Guest Loyalty Tier SummaryPro
PYTHONEasy
49
Rate Plan Overview by MealPro
PYTHONMedium
50
Active Direct-Channel ReservationsPro
PYTHONEasy
51
High-Value Checked-Out BookingsPro
PYTHONMedium
52
Refundable Rate Plans With MealsPro
PYTHONMedium
53
Premium Guest Luxury StaysPro
PYTHONHard
54
Reservations Count by ChannelPro
PYTHONEasy
55
Total Revenue by PropertyPro
PYTHONMedium
56
Average Review Rating by PlatformPro
PYTHONMedium
57
Property Booking MetricsPro
PYTHONHard
58
Channel Commission AnalysisPro
PYTHONHard
59
Reservations with Guest NamesPro
PYTHONEasy
60
Payments with Booking ChannelPro
PYTHONMedium
61
Room Types Without ReservationsPro
PYTHONMedium
62
Review Details with PropertyPro
PYTHONHard
63
Full Reservation HierarchyPro
PYTHONHard
64
Rank Properties by RevenuePro
PYTHONMedium
65
Running Total Revenue per PropertyPro
PYTHONMedium
66
Seven-Day Moving Average OccupancyPro
PYTHONHard
67
Daily Revenue Change vs Previous DayPro
PYTHONHard
68
Reservation Booking Month and YearPro
PYTHONEasy
69
Booking Lead Time CalculationPro
PYTHONMedium
70
Monthly Booking Volume by ChannelPro
PYTHONHard
71
Fill Missing Guest ContactsPro
PYTHONMedium
72
Normalize Payment AmountsPro
PYTHONMedium
73
Standardize Booking ChannelsPro
PYTHONHard
74
Reservation Count by Channel and StatusPro
PYTHONMedium
75
Property Revenue by Booking ChannelPro
PYTHONHard
76
Classify Reservations by Value TierPro
PYTHONMedium
77
Guest Value ClassificationPro
PYTHONHard
78
Compute Occupancy RatePro
PYTHONMedium
79
Reservation Value Quartile BucketingPro
PYTHONHard
80
Time-Based Booking FeaturesPro
PYTHONHard
81
Property Performance MatrixPro
PYTHONExpert
82
Review Text FeaturesPro
PYTHONHard
83
Nightly Rate Descriptive StatsPro
PYTHONMedium
84
Rating vs Revenue CorrelationPro
PYTHONHard
85
Anomalous Booking Amount DetectionPro
PYTHONHard
86
Property Performance ScorecardPro
PYTHONHard
87
Guest Lifetime Value ReportPro
PYTHONHard
88
Full-Funnel Booking ReportPro
PYTHONExpert
89
Channel Profitability ClassificationPro
PYTHONExpert
90
Housekeeping Efficiency AnalysisPro
PYTHONExpert

Ready to practice Lodging?

90 SQL and Python challenges built from real lodging data. Graded instantly in your browser — no setup required.