Glassdoor users rated their interview experience at InkRevenue as 100% positive with a difficulty rating score of 3 out of 5 (where 5 is the highest level of difficulty). Candidates interviewing for Junior Data Analyst and rated their interviews as the hardest, whereas interviews for Junior Data Analyst and roles were rated as the easiest.
The interview process includes four rounds:
An HR round to assess cultural fit, an aptitude round testing logical and analytical abilities, a technical round focusing on data analyst skills such as Excel and Python basics, and a final manager round to evaluate your overall suitability for the role.
Interview questions [1]
Question 1
1. What are the differences between lists and tuples in Python, and how does this distinction relate to Pandas operations?
2. What is a DataFrame in Pandas, and how does it differ from a Series?
3. Can you explain how to handle missing data in Pandas, including the difference between 'fillna()' and 'dropna()'?
4. Describe the process of renaming a column in a Pandas DataFrame.
5. What is the purpose of the 'groupby' function in Pandas, and provide an example of its usage?
1. Picture this: Netflix has seen a decline in the number of new subscribers from urban areas but an uptick from rural regions. Frame a strategy to leverage this trend and ensure consistent growth across both demographics.
2. Uber is contemplating launching a new service named "Uber Tours" in major tourist cities. This would be a guided tour using an Uber. Define the critical metrics you'd consider to gauge the initial success of this service.
Python code for
Armstrong number
Prime number
Palindrome