Pro90 ProblemsSQL + Python
Logistics SQL & Python Interview Questions
Shipping and delivery companies track parcel journeys, driver performance, and network efficiency across complex supply chains. These SQL and Python challenges are modeled after data work at Amazon Logistics, FedEx, UPS, DHL, XPO Logistics, Maersk, Flexport, CH Robinson, Uber Freight, ShipBob, and more. Build skills in on-time delivery analysis, route optimization, cost-per-shipment metrics, carrier performance, and warehouse efficiency.
Companies working in Logistics
These practice problems are modeled after the kind of data and analytics challenges teams in this industry typically face.
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 Distribution
Easy
16
18% of problems
Medium
31
34% of problems
Hard
38
42% of problems
Expert
5
6% of problems
What You'll Practice
On-time delivery analysis
Route efficiency metrics
Network capacity planning
Cost per shipment
Driver performance
Carrier comparison
SLA compliance tracking
Last-mile analytics
Topics Covered
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
01
Active Parcel CarriersPro
SQLEasy02High-Value Overnight OrdersPro
SQLEasy03Delivered International ShipmentsPro
SQLEasy04Perishable or Hazardous ProductsPro
SQLEasy05Gold-Tier Business CustomersPro
SQLMedium06Orders With Customer DetailsPro
SQLEasy07Shipments With Carrier and Warehouse InfoPro
SQLMedium08Order Line Items With Product DetailsPro
SQLMedium09Delivery Exceptions With Carrier ContextPro
SQLMedium10Orders Without ShipmentsPro
SQLMedium11Late Deliveries With Full ContextPro
SQLHard12Order Volume by StatusPro
SQLEasy13Total Order Revenue per WarehousePro
SQLMedium14Average Freight Cost by CarrierPro
SQLMedium15On-Time Delivery Rate by CarrierPro
SQLMedium16Top 5 Customers by Total Order ValuePro
SQLHard17Warehouses With High Cancellation RatePro
SQLHard18Rank Carriers by Shipment VolumePro
SQLMedium19Customer Order Sequence NumberPro
SQLMedium20Daily Shipping Cost Running Total per WarehousePro
SQLHard21Most Expensive Shipment per CarrierPro
SQLHard22Carrier Freight Cost 3-Shipment Moving AveragePro
SQLHard23Order Value Change From Prior OrderPro
SQLHard24Shipment Weight Quartile AnalysisPro
SQLHard25Carriers Above Average Freight CostPro
SQLMedium26Customers Using Ground and Express ShippingPro
SQLHard27Latest Shipment per CustomerPro
SQLHard28Warehouse Revenue With Rank via CTEPro
SQLHard29Service Levels With Below-Average Freight CostPro
SQLHard30Recent Orders (Last 30 Days)Pro
SQLEasy31Monthly Order Volume TrendPro
SQLMedium32Average Delivery Lead Time by Service LevelPro
SQLMedium33Late Deliveries by Carrier and Delay DurationPro
SQLHard34Orders With Shipping Speed CategoryPro
SQLEasy35Shipments With Weight Tier LabelPro
SQLMedium36Customer Tier With Order SummaryPro
SQLHard37Countries With Customers or ShipmentsPro
SQLMedium38Customers With Shipments But No ExceptionsPro
SQLMedium39Warehouse Performance ScorecardPro
SQLHard40Carrier Performance ReportPro
SQLHard41Customer Lifetime Value SummaryPro
SQLHard42Delivery Exception Financial ImpactPro
SQLHard43Shipment SLA Compliance AuditPro
SQLHard44Warehouse Operations DashboardPro
SQLExpert45Domestic vs International Shipping AnalysisPro
SQLHard46Active Carrier ProfilesPro
PYTHONEasy47Order Status CountsPro
PYTHONEasy48Product Category SummaryPro
PYTHONEasy49Warehouse Capacity OverviewPro
PYTHONMedium50Delivered Domestic OrdersPro
PYTHONEasy51High-Value Express ShipmentsPro
PYTHONMedium52Unresolved Damage ExceptionsPro
PYTHONMedium53Gold Customer International OrdersPro
PYTHONHard54Orders Per WarehousePro
PYTHONEasy55Total Freight Cost by CarrierPro
PYTHONMedium56Average Shipping Cost by Service LevelPro
PYTHONMedium57Shipment Stats by Destination CountryPro
PYTHONHard58Customer Order SummaryPro
PYTHONHard59Orders With Customer NamesPro
PYTHONEasy60Shipments With Carrier DetailsPro
PYTHONMedium61Carriers Without ShipmentsPro
PYTHONMedium62Shipment Warehouse and Carrier DetailsPro
PYTHONHard63Full Order Line DetailPro
PYTHONHard64Rank Carriers by Freight RevenuePro
PYTHONMedium65Running Total Shipping Cost Per CustomerPro
PYTHONMedium667-Day Moving Average Freight CostPro
PYTHONHard67Daily Order Volume ChangePro
PYTHONHard68Order Month and Year ExtractionPro
PYTHONEasy69Shipment Transit DaysPro
PYTHONMedium70Monthly Order Volume by CountryPro
PYTHONHard71Fill Missing Customer ContactsPro
PYTHONEasy72Normalize Freight CostsPro
PYTHONMedium73Categorize Delivery ExceptionsPro
PYTHONHard74Pivot Order Counts by Country and StatusPro
PYTHONMedium75Pivot Freight Revenue by Carrier and Service LevelPro
PYTHONHard76Classify Shipments by Weight TierPro
PYTHONMedium77Order Priority ScorePro
PYTHONHard78Cost Per Kg and Cost Per M3Pro
PYTHONMedium79Shipment Freight Quartile BucketingPro
PYTHONHard80Time-Based Order FeaturesPro
PYTHONHard81Carrier Performance Feature MatrixPro
PYTHONExpert82Order Value and Weight FeaturesPro
PYTHONHard83Shipping Cost Descriptive Statistics by Service LevelPro
PYTHONMedium84Freight Cost vs Weight Correlation by CarrierPro
PYTHONHard85Anomalous Freight Cost DetectionPro
PYTHONHard86Carrier Performance ScorecardPro
PYTHONHard87Customer Shipping ReportPro
PYTHONHard88Warehouse Throughput AnalysisPro
PYTHONExpert89Exception Resolution DashboardPro
PYTHONExpert90End-to-End Order Fulfillment ReportPro
PYTHONExpertReady to practice Logistics?
90 SQL and Python challenges built from real logistics data. Graded instantly in your browser — no setup required.