Skip to content
FreePro237 ProblemsSQL + Python

Retail SQL & Python Interview Questions

E-commerce and retail analytics covers inventory management, customer lifetime value, basket analysis, and supply chain performance across millions of SKUs. These SQL and Python challenges are modeled after data work at Amazon, Walmart, Target, Shopify, eBay, Etsy, Wayfair, Kroger, Costco, Best Buy, Home Depot, IKEA, and more. Master funnel analysis, cohort retention, demand forecasting, and merchandising metrics.

Retail

237 total problems

SQL134
Python103
Top Companies Hiring in Retail

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

Amazon
Amazon
Walmart
Walmart
Target
Target
Instacart
Instacart
Shopify
Shopify
eBay
eBay
Etsy
Etsy
Wayfair
Wayfair
Chewy
Chewy
Kroger
Kroger
Costco
Costco
Best Buy
Best Buy
Home Depot
Home Depot
IKEA
IKEA
Alibaba
Alibaba
Flipkart
Flipkart
Mercado Libre
Mercado Libre
Rakuten
Rakuten
Faire
Faire
Coupang
Coupang

Difficulty Distribution

Easy

68

29% of problems

Medium

104

44% of problems

Hard

58

24% of problems

Expert

7

3% of problems

What You'll Practice

Customer lifetime value
Basket & cart analysis
Inventory management metrics
Funnel conversion analysis
Cohort retention
Product performance
Supply chain KPIs
Promotional analysis

Topics Covered

22 topics
SQL· 10
aggregationbasic queries filteringcleaning transformdate timefilteringjoinsscenario sqlset operationssubqueries cteswindow functions
Python· 12
eda statisticsfeature engineeringpandas aggregationpandas applypandas basicspandas cleaningpandas datetimepandas filteringpandas mergingpandas reshapingpandas scenariopandas window

All Problems237 total

Open in editor
01
Premium Products Within a SegmentFree
SQLEasy
02
US Customers With Missing PhoneFree
SQLEasy
03
High-Value US Orders (Shipped/Delivered)Free
SQLMedium
04
Orders Flagged for Fraud ReviewFree
SQLHard
05
Active Home Products in Mid-Price BandFree
SQLEasy
06
California (US) Customers with a Phone NumberFree
SQLEasy
07
Confirmed Orders With Captured ChargeFree
SQLEasy
08
Captured Payments via Mobile WalletsFree
SQLEasy
09
Delivered Shipments Using Two-Day ServiceFree
SQLEasy
10
Backorderable Inventory With Low Available UnitsFree
SQLEasy
11
Digital Orders With Successful CollectionFree
SQLEasy
12
Inactive Low-Priced ProductsFree
SQLEasy
13
In-Transit Shipments Without Delivery DateFree
SQLEasy
14
US Orders With Captured Charge (High-Value)Free
SQLMedium
15
Active Products That Have Been OrderedFree
SQLMedium
16
Captured Orders With At Least One Bulk LineFree
SQLMedium
17
Delivered Shipments Backed by Captured ChargeFree
SQLMedium
18
US Customers With At Least One Captured OrderFree
SQLMedium
19
US Orders With Any Two-Day ShipmentFree
SQLMedium
20
Captured Payments for Delivered OrdersFree
SQLMedium
21
Active Home Products Never OrderedFree
SQLMedium
22
Captured Orders That Include Returned ItemsFree
SQLMedium
23
US CA/NY Customers With Any Ship-Method OrderFree
SQLMedium
24
In-Transit Shipments With Captured PaymentsFree
SQLMedium
25
Latest Captured Payment Per CustomerFree
SQLHard
26
Highest-Value Line Per Delivered OrderFree
SQLHard
27
Top Customers by Recent Billed AmountFree
SQLMedium
28
Delivered Orders CountFree
SQLEasy
29
Total Billed Amount for Delivered OrdersFree
SQLEasy
30
Average Billed for Delivered OrdersFree
SQLEasy
31
Max Shipping Fee for Physical ShipmentsFree
SQLEasy
32
Captured Payments Orders CountFree
SQLEasy
33
Canceled Orders CountFree
SQLEasy
34
Total Tax on Delivered OrdersFree
SQLEasy
35
Delivered Orders by StateFree
SQLMedium
36
Captured Payments by MethodFree
SQLMedium
37
Active Products by CategoryFree
SQLMedium
38
Avg Shipping Fee by Service Level (Delivered)Free
SQLMedium
39
Delivered Revenue by CityFree
SQLMedium
40
Recent Delivered Orders by State (60 Days)Free
SQLMedium
41
Units Delivered by ProductFree
SQLMedium
42
Captured Amount by Customer (Delivered Orders)Free
SQLMedium
43
Top Customers by Recent Captured Revenue (90 Days)Free
SQLHard
44
Top Products by Recent Units Delivered (90 Days)Free
SQLHard
45
Orders Above Average BilledFree
SQLEasy
46
Products Above Category Average PriceFree
SQLEasy
47
Lowest Priced Products per CategoryFree
SQLEasy
48
Customers’ Highest-Billed OrdersFree
SQLEasy
49
Products Below Average WeightFree
SQLEasy
50
Customers With Recent Delivered Orders (60 Days)Free
SQLMedium
51
Products Without Delivered Line ItemsFree
SQLMedium
52
Orders Above Average Within Shipping TierFree
SQLMedium
53
Orders With a Captured PaymentFree
SQLMedium
54
Customers Without Refunds in the Last 90 DaysFree
SQLMedium
55
Delivered Shipments by CarrierFree
SQLMedium
56
Products With Deliveries But No Returns (Last 120 Days)Free
SQLHard
57
Top Two Recent Delivered Orders per CustomerFree
SQLMedium
58
Delivered US Purchases by RecencyFree
SQLEasy
59
Largest Captured Payments — Recent FirstFree
SQLEasy
60
Active Products by PriceFree
SQLEasy
61
Latest Captured Payment per PurchaseFree
SQLMedium
62
Top 3 Delivered Purchases per StateFree
SQLMedium
63
Top Two Line Items per PurchaseFree
SQLMedium
64
Two Newest Active Items per CategoryFree
SQLMedium
65
Latest Delivered Shipment per PurchaseFree
SQLMedium
66
Top Two Captured Payments per MethodFree
SQLMedium
67
Customer Running Spend — Last 90 DaysFree
SQLHard
68
Top 3 Line Items per Product — Last 60 DaysFree
SQLHard
69
Recently Delivered Shipments (Newest First)Free
SQLEasy
70
All Orders by Most RecentFree
SQLEasy
71
Orders Placed in the Last 30 DaysFree
SQLMedium
72
Payments Captured in the Last 7 DaysFree
SQLMedium
73
Most Recent Captured Payment per Customer (Last 60 Days)Free
SQLHard
74
Standardize Customer ContactsFree
SQLEasy
75
Normalize Product SKUs and NamesFree
SQLEasy
76
Standardize Order Status and Shipping FieldsFree
SQLEasy
77
Recent Captured Payments (Normalized)Free
SQLMedium
78
Normalized Order Items for Active ProductsFree
SQLMedium
79
Delivered Shipments (Normalized)Free
SQLMedium
80
Delivered Orders with Latest Capture (Normalized)Free
SQLHard
81
Customers from US or CanadaFree
SQLEasy
82
Orders from California or Texas (All)Free
SQLEasy
83
Active Products from Electronics or HomeFree
SQLMedium
84
Customers with Delivered Orders AND Captured PaymentsFree
SQLMedium
85
Products Ordered But Never ReturnedFree
SQLMedium
86
Customers with Orders but No Captured PaymentsFree
SQLHard
87
Active vs Inactive Product Analysis with CTEsFree
SQLHard
88
Premium Merchandising ItemsFree
SQLEasy
89
Captured Payments for In-Progress OrdersFree
SQLMedium
90
Select Product ColumnsFree
PYTHONEasy
91
Filter Delivered OrdersFree
PYTHONEasy
92
Sort Customers by NameFree
PYTHONEasy
93
Filter Premium ElectronicsFree
PYTHONMedium
94
Filter Completed OrdersFree
PYTHONMedium
95
Filter Mid-Range ProductsFree
PYTHONMedium
96
Filter US Customers with Phone NumbersFree
PYTHONHard
97
Filter Electronics ProductsFree
PYTHONEasy
98
Filter Delivered OrdersFree
PYTHONEasy
99
Filter Products by Price RangeFree
PYTHONMedium
100
Filter High-Value Delivered OrdersFree
PYTHONMedium
101
Filter Products by Brand NameFree
PYTHONHard
102
Count Products by CategoryFree
PYTHONEasy
103
Total Revenue by Order StatusFree
PYTHONEasy
104
Average Price by CategoryFree
PYTHONEasy
105
Order Statistics by StatusFree
PYTHONMedium
106
Find Repeat CustomersFree
PYTHONMedium
107
Price Extremes by CategoryFree
PYTHONMedium
108
Category Price Range AnalysisFree
PYTHONMedium
109
Customer Order SummaryFree
PYTHONMedium
110
Product Price as Percentage of Category TotalFree
PYTHONHard
111
Orders with Customer AverageFree
PYTHONHard
112
Top Product per CategoryFree
PYTHONHard
113
Merge Orders with CustomersFree
PYTHONEasy
114
Order Items with Product NamesFree
PYTHONEasy
115
Customers with Order CountsFree
PYTHONEasy
116
Find Orphan RecordsFree
PYTHONMedium
117
High Value Customers OrdersFree
PYTHONMedium
118
Revenue by CategoryFree
PYTHONMedium
119
Order Items Full DetailsFree
PYTHONMedium
120
Find Unmatched ProductsFree
PYTHONMedium
121
Customer Lifetime ValueFree
PYTHONHard
122
Order Share of Customer TotalFree
PYTHONHard
123
Pivot Orders by StatusFree
PYTHONEasy
124
Pivot Revenue by Category and StatusFree
PYTHONMedium
125
Pivot Order Metrics by CountryFree
PYTHONHard
126
Rank Orders by AmountFree
PYTHONEasy
127
Rolling Sum of Order RevenueFree
PYTHONMedium
128
Rolling Average with Min PeriodsFree
PYTHONMedium
129
Dense Rank Products by PriceFree
PYTHONMedium
130
Percent Rank Orders by AmountFree
PYTHONMedium
131
Multiple Window Functions on OrdersFree
PYTHONHard
132
Extract Order Date PartsFree
PYTHONEasy
133
Calculate Shipping DaysFree
PYTHONMedium
134
Group Orders by QuarterFree
PYTHONMedium
135
Drop Customers Missing PhoneFree
PYTHONEasy
136
Uppercase Product CategoriesFree
PYTHONEasy
137
Fill Missing Delivery DatesFree
PYTHONMedium
138
Strip Whitespace from NamesFree
PYTHONMedium
139
Convert Active Flag to BooleanFree
PYTHONMedium
140
Multi-Step Customer CleanupFree
PYTHONHard
141
Categorize Product PricesFree
PYTHONEasy
142
Calculate Dynamic DiscountsFree
PYTHONMedium
143
Calculate Effective Price per ItemFree
PYTHONMedium
144
Delivered Orders by CityFree
PYTHONEasy
145
Customer Order AnalysisFree
PYTHONMedium
146
Order Fulfillment AnalysisFree
PYTHONMedium
147
Customer 360 ViewFree
PYTHONHard
148
Active Electronics ProductsPro
SQLEasy
149
High-Value Orders Above $5KPro
SQLEasy
150
Prime Platinum CustomersPro
SQLEasy
151
Canceled Orders With Promo CodePro
SQLEasy
152
Active Sellers With High RatingPro
SQLMedium
153
Orders With Customer DetailsPro
SQLEasy
154
Order Items With Product InfoPro
SQLMedium
155
Shipments With Carrier and WarehousePro
SQLMedium
156
Payments With Order and Customer ContextPro
SQLMedium
157
Products Never OrderedPro
SQLMedium
158
Customers With No Shipped OrdersPro
SQLHard
159
Order Count by StatusPro
SQLEasy
160
Total Revenue by Product CategoryPro
SQLMedium
161
Avg Order Value by Loyalty TierPro
SQLMedium
162
Return Rate by SellerPro
SQLMedium
163
Top 5 Customers by Total SpendingPro
SQLHard
164
Sellers With High Cancellation RatePro
SQLHard
165
Rank Sellers by RevenuePro
SQLMedium
166
Customer Order Sequence NumberPro
SQLMedium
167
Daily Revenue Running TotalPro
SQLHard
168
Top Product per Category by RevenuePro
SQLHard
169
Carrier Shipping Cost 3-Shipment Moving AveragePro
SQLHard
170
Order Value Change From Prior OrderPro
SQLHard
171
Order Value Quartile AnalysisPro
SQLHard
172
Products Priced Above Category AveragePro
SQLMedium
173
Customers With Both Orders and ReturnsPro
SQLHard
174
Latest Order per CustomerPro
SQLHard
175
Seller Revenue With Rank via CTEPro
SQLHard
176
Categories With Above-Average RevenuePro
SQLHard
177
Recent Orders (Last 30 Days)Pro
SQLEasy
178
Monthly Order Volume TrendPro
SQLMedium
179
Average Delivery Lead Time by Service LevelPro
SQLMedium
180
Late Deliveries by CarrierPro
SQLHard
181
Orders With Shipping Speed CategoryPro
SQLEasy
182
Products With Weight Tier LabelPro
SQLMedium
183
Customer Tier With Order SummaryPro
SQLHard
184
Products Needing Attention — Low Stock or ReturnedPro
SQLMedium
185
Sellers With Orders But No ReturnsPro
SQLMedium
186
Seller Performance ScorecardPro
SQLHard
187
Order Fulfillment Funnel AnalysisPro
SQLHard
188
Customer Lifetime Value SummaryPro
SQLHard
189
Return Financial Impact AnalysisPro
SQLHard
190
Warehouse Inventory Health ReportPro
SQLExpert
191
Marketplace Operations DashboardPro
SQLExpert
192
Prime vs Standard Customer AnalysisPro
SQLExpert
193
Active Product CatalogPro
PYTHONEasy
194
Order Status CountsPro
PYTHONEasy
195
Seller Category SummaryPro
PYTHONMedium
196
Customer Loyalty BreakdownPro
PYTHONMedium
197
Delivered Ship OrdersPro
PYTHONEasy
198
High-Value OrdersPro
PYTHONEasy
199
Prime Customers in Target StatesPro
PYTHONMedium
200
Returned Items With ReasonPro
PYTHONMedium
201
Items Per OrderPro
PYTHONEasy
202
Revenue by Product CategoryPro
PYTHONMedium
203
Average Order Value by Fulfillment TypePro
PYTHONMedium
204
Seller Sales PerformancePro
PYTHONHard
205
Warehouse Inventory SummaryPro
PYTHONHard
206
Orders With Customer NamesPro
PYTHONEasy
207
Order Items With Product DetailsPro
PYTHONMedium
208
Products Without OrdersPro
PYTHONMedium
209
Shipment Tracking With CustomerPro
PYTHONHard
210
Full Order Detail ReportPro
PYTHONHard
211
Rank Customers by SpendingPro
PYTHONMedium
212
Running Total Revenue per SellerPro
PYTHONMedium
213
7-Day Moving Average Order ValuePro
PYTHONHard
214
Daily Revenue Change PercentagePro
PYTHONHard
215
Extract Order Month and YearPro
PYTHONEasy
216
Shipping Duration in DaysPro
PYTHONMedium
217
Monthly Order Volume by Fulfillment TypePro
PYTHONHard
218
Fill Missing Phone NumbersPro
PYTHONEasy
219
Normalize Product PricesPro
PYTHONMedium
220
Standardize Carrier and Service Level DataPro
PYTHONHard
221
Pivot Order Counts by Status and FulfillmentPro
PYTHONMedium
222
Revenue Pivot by Category and SellerPro
PYTHONHard
223
Classify Orders by Value TierPro
PYTHONMedium
224
Order Priority ScorePro
PYTHONHard
225
Compute Discount Rate Per OrderPro
PYTHONMedium
226
Order Value Quartile BucketingPro
PYTHONHard
227
Product Volume FeaturesPro
PYTHONHard
228
Customer Feature MatrixPro
PYTHONExpert
229
Inventory Health FeaturesPro
PYTHONHard
230
Order Value Descriptive StatisticsPro
PYTHONMedium
231
Price vs Quantity CorrelationPro
PYTHONHard
232
Anomalous Order Value Detection (IQR)Pro
PYTHONHard
233
Seller Performance ScorecardPro
PYTHONHard
234
Customer Lifetime ReportPro
PYTHONHard
235
Fulfillment Pipeline AnalysisPro
PYTHONExpert
236
Product Health DashboardPro
PYTHONExpert
237
End-to-End Order ReportPro
PYTHONExpert

Ready to practice Retail?

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