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Online assessment : It consisted 6 questions in totall all based on a small given data set in excel . It can be easily answered by applying basic excel knowledge and formula. Screening Interview : It was around 30 minutes screening round online in which mixed questions were asked by the interviwer like about myself , strength and weakness , future career goals , etc. Then he asked me basic types of JOINs in SQL after which he asked about python pandas and numpy basic things like what it is used for and do you have knowledge about it or not . Then the interview ended with me asking 2 basic question to him about the role Technical Interview : The interview consisted 3 problem statements in total as following The first problem was based on python dictionary on to which operations was needed to be performed using python . For example : data_set = [ {'Word' : 'Rahul' , 'unpaid':500 , 'paid' : 600} , {'Word' : 'Rahul' , 'unpaid':200 , 'paid' : 80} , {'Word' : 'Disha' , 'unpaid':502 , 'paid' : 330} , {'Word' : 'Viren' , 'unpaid':500 , 'paid' : 600} ] the data was like above shown on to which i had to do certain operations like get the 2nd and 7th element from the data set , insert the new data in the data set ,get the resultant data as data_set = [ {'Word' : 'Rahul' , 'unpaid':700 , 'paid' : 680} , {'Word' : 'Disha' , 'unpaid':502 , 'paid' : 330} , {'Word' : 'Viren' , 'unpaid':500 , 'paid' : 600} ] After this there was 3 tables given on to which using pandas operations was supposed to be done . Like joining the table , getting data based on certain condition etc. In the last problem there were multiple tables given and using SQL query I had to join the tables and get the relevant information like city name , dealer name , and also hard code a certain values in the sql query itself and get the desired output . At last the inteviewer asked me explain in details about the joins , what are lambda function in python , delete vs truncate vs drop . So overall the experience was good , the interviwers were chill and very helpfull as they were giving me hints wherever it was required .
avatar

Jr. Data Analyst

Interviewed at CarWale

3.6★
Dec 7, 2023

Online assessment : It consisted 6 questions in totall all based on a small given data set in excel . It can be easily answered by applying basic excel knowledge and formula. Screening Interview : It was around 30 minutes screening round online in which mixed questions were asked by the interviwer like about myself , strength and weakness , future career goals , etc. Then he asked me basic types of JOINs in SQL after which he asked about python pandas and numpy basic things like what it is used for and do you have knowledge about it or not . Then the interview ended with me asking 2 basic question to him about the role Technical Interview : The interview consisted 3 problem statements in total as following The first problem was based on python dictionary on to which operations was needed to be performed using python . For example : data_set = [ {'Word' : 'Rahul' , 'unpaid':500 , 'paid' : 600} , {'Word' : 'Rahul' , 'unpaid':200 , 'paid' : 80} , {'Word' : 'Disha' , 'unpaid':502 , 'paid' : 330} , {'Word' : 'Viren' , 'unpaid':500 , 'paid' : 600} ] the data was like above shown on to which i had to do certain operations like get the 2nd and 7th element from the data set , insert the new data in the data set ,get the resultant data as data_set = [ {'Word' : 'Rahul' , 'unpaid':700 , 'paid' : 680} , {'Word' : 'Disha' , 'unpaid':502 , 'paid' : 330} , {'Word' : 'Viren' , 'unpaid':500 , 'paid' : 600} ] After this there was 3 tables given on to which using pandas operations was supposed to be done . Like joining the table , getting data based on certain condition etc. In the last problem there were multiple tables given and using SQL query I had to join the tables and get the relevant information like city name , dealer name , and also hard code a certain values in the sql query itself and get the desired output . At last the inteviewer asked me explain in details about the joins , what are lambda function in python , delete vs truncate vs drop . So overall the experience was good , the interviwers were chill and very helpfull as they were giving me hints wherever it was required .

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