Interview Questions

Catherine T. - "We want sales to grow, in order to have a growth in revenue. And customer usage as well as it allows to see if our product lead more engagement from our users. So to be able to see this overall evolution I would make a line chart for both : Sales : with month on x-axis and sales revenue on y-axis Customer Usage : with month on x-axis and a KPI allowing to measure customer usage (nblogins or nbsessions or nbgamesplayed, ... depending on the industry) on y-axis Moreover, after knowing th"See full answer

Tian H. - "google photos: edit, organize, search, and backup your photos. both android and iOS users can use google photos. together with the google drive, users can have 15 gigabytes free storage. photos market: main competitor, apple photos. this is a relatively mature market with two biggest players. when evaluating the acquisition, retention/engagement, rev, we would focus more on the retention. Higher retention and more usage are also strong signals of upgrading to larger storage and rev growth. "See full answer

Palak A. - "By looking at QPS prolly! I mean that's the success metric for it after all, right? Maybe not, love to know your thoughts down below."See full answer

Sriharsha K. - "I had this experience many a times. Normally underperformer is bottleneck to the team. Its not inly a unproductive person, it also choke other person's time who is try to help that person. I normally try to analyze reason for underperformance. It could be person in wrong place, he/she may need technical training, person may not be motivated for some reasons OR person has no potential. I had underperformer in my team who was not able to implement a design I suggested. Team lead was not able to c"See full answer

Rishabh L. - "Pizza Ordering System orderdetail - orderdetailid (PK), orderid (FK), itemid (FK), itemqty, itemized_price order - orderid (PK), customerid (FK), orderdate, locationid (FK), ordertype (DINEIN, PICKUP, DELIVERY), refid (dineinid, pickupid, deliveryid), subtotal, tax, tip, totalamount, payment_method (CASH, CARD) location - locationid (PK), locationdesc, city, state, startdate, enddate customer - customer_id (PK), name, address (nullable), phone (nullable), dob (d"See full answer

Manik K. - "Agile methodologies are chosen by organizations to enhance delivery speed, integrate shorter feedback loops, and provide incremental value to customers. However, the suitability of Agile depends on several factors, including the nature of the work, team structure, and organizational objectives. From my experience, for teams focused on new feature development, Scrum tends to be more effective. Scrum’s structured cadence—emphasizing backlog grooming, sprint planning, and regular retrospective"See full answer

Caleb S. - " import pandas as pd def findimprovingstudents(transcript: pd.DataFrame) -> pd.DataFrame: summary = transcript.pivottable(index='studentid', values = 'yearlygpa', aggfunc = 'sum',columns = 'year').resetindex() summary['average_gpa'] = round((summary[2023] + summary[2022] + summary[2021])/3,2) return summary(summary[2023] > summary[2022]) & (summary[2022] > summary[2021])] #yn > yn-1, yn-1 > yn-2, yn-3 debug your co"See full answer

Sean L. - " import pandas as pd from datetime import datetime def findfastestlike(log: pd.DataFrame) -> pd.DataFrame: log=log.sortvalues(['userid','timestamp']) #get the prev event, time by user log['prevevent'] = log.groupby('userid')['event'].shift(1) log['prevtimestamp'] = log.groupby('userid')['timestamp'].shift(1) True only on rows where the previous event was a login and the current event is a like log['loginlike'] = (log['prevevent'] == 'log"See full answer

Sean L. - " debug your code below departments = pd.DataFrame({ 'id': [1, 2, 3, 4, 5], 'name': ['Reporting', 'Engineering', 'Marketing', 'Biz Dev', 'Silly Walks'] }) employees = pd.DataFrame({ 'id': [1, 2, 3, 4, 5, 6], 'first_name': ['John', 'Ava', 'Cailin', 'Mike', 'Ian', 'John'], 'last_name': ['Smith', 'Muffinson', 'Ninson', 'Peterson', 'Peterson', 'Mills'], 'salary': [20000, 10000, 30000, 20000, 80000, 50000], 'department_id': [1, 5, 2, 2, 2, 3] }) projects = p"See full answer

Chao peter Y. - "The question is incomplete --- the code only passes if you return the data frame sorted by BOTH department name AND rank. While in the problem description, it mentions to only rank by department name: "The results should be ordered by department name." Not a big difference I know, but students shouldn't need to look into the solution to get the necessary knowledge to answer the question."See full answer