FreePro253 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

253 total problems

SQL148

Python105

Practice SQL Practice Python

Companies working in Retail

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

Amazon

Walmart

Target

Instacart

Shopify

eBay

Etsy

Wayfair

Chewy

Kroger

Costco

Best Buy

Home Depot

IKEA

Alibaba

Flipkart

Mercado Libre

Rakuten

Faire

Coupang

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

253 problems

69 Easy(27%)

107 Medium(42%)

67 Hard(26%)

10 Expert(4%)

What You'll Practice

Customer lifetime valueBasket & cart analysisInventory management metricsFunnel conversion analysisCohort retentionProduct performanceSupply chain KPIsPromotional analysis

Topics Covered

24 topics

SQL · 10

aggregationbasic queries filteringcleaning transformdate timefilteringjoinsscenario sqlset operationssubqueries cteswindow functions

Python · 14

ab testingeda statisticsfeature engineeringml evaluationpandas aggregationpandas applypandas basicspandas cleaningpandas datetimepandas filteringpandas mergingpandas reshapingpandas scenariopandas window

All Problems253 total

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