Data Analyst Coding Interview Questions

Mohit C. - "-- LTV = Sum of all purchases made by that user -- order the results by desc on LTV select u.user_id, sum(a.purchase_value) as LTV from user_sessions u join attribution a on u.sessionid = a.sessionid group by u.user_id order by sum(a.purchase_value) desc"See full answer

Arshad P. - "Schema is wrong - id from product is mapped to id from transactions, id from product should point to product_id in transcations table"See full answer

Gabriel P. - "Hi, my solution gives the exact numerical values as the proposed solution, but it doesn't pass the tests. Am I missing something, or is this a bug? def findrevenueby_city(transactions: pd.DataFrame, users: pd.DataFrame, exchange_rate: pd.DataFrame) -> pd.DataFrame: gets user city for each user id userids = users[['id', 'usercity']] and merge on transactions transactions = transactions.merge(user_ids, how='left"See full answer

Harshitha B. - " SELECT * FROM( SELECT c.first_name, c.last_name, t.receipt_number, COUNT(*) OVER (PARTITION BY c.customerid) AS noof_offences FROM customers c JOIN transactions t ON c.customerid = t.customerid WHERE t.receipt_number LIKE '%999%' OR t.receipt_number LIKE '%1234%' OR t.receipt_number LIKE '%XYZ%' ) sub WHERE noofoffences > 1 ; `"See full answer

Diyorbek T. - " import pandas as pd import numpy as np def findoverstretchedemployees(departments: pd.DataFrame, employees: pd.DataFrame, projects: pd.DataFrame, employees_projects: pd.DataFrame) -> pd.DataFrame: Make a copy to avoid modifying original dataframe projects = projects.copy() Convert dates to datetime projects["startdate"] = pd.todatetime(projects["start_date""See full answer