Capgemini Data Engineering Interview: Solve Problems with Dictionary & List Comprehension

Preparing for a Capgemini Data Engineering interview? One of the most commonly asked questions involves solving problems using different Python approaches, such as dictionary data structures and list comprehension. In this video, we break down a real interview question and solve it using both methods. What you’ll learn in this video: ✅ Using dictionary data structures for efficient data handling. ✅ Optimizing solutions with list comprehension in Python. ✅ Comparing both approaches to understand time complexity and performance. ✅ Best practices for structuring and explaining your answers in interviews. Dataset is as follows: data = [ (1, "Sagar", 23, "Male", 68.0), (2, "Forest", 35, "Female", 90.0), (3, "Alexa", 40, "Male", 79.1), (4, "jennie", 40, "Female", 80.1), (5, "Master", 40, "Male", 90.1), ] schema = "Id int,Name string,Age int,Gender string,Marks float" df = spark.createDataFrame(data, schema) To check complete solution refer the Github: Github link: https://github.com/shilpadata/pyspark_databricks/blob/main/interview-playlist/Capgemini_1.py If you're targeting a Capgemini Data Engineer, Data Analyst, or Python Developer role, mastering these concepts will give you an edge in your interview. 📌 Subscribe to Shilpa Data Insights for expert guidance on data engineering, Python interview prep, and coding best practices! Don't forget to like, subscribe, and hit the notification bell for more deep-dive tutorials on Databricks and big data analytics! Link to Spark playlist: https://www.youtube.com/playlist?list=PLHcpPiCf7ryZf8GAFKcFuYmOxswcCOGz4 Link to Databricks playlist: https://www.youtube.com/playlist?list=PLHcpPiCf7ryZLNLvSsglM05lJXaWngHUH Link to Databricks certification : https://www.youtube.com/playlist?list=PLHcpPiCf7ryZrusmfkgteZvSMO16hagP5 Link to Big data: https://www.youtube.com/playlist?list=PLHcpPiCf7ryYfIrrJBQDa0Vw9BXIY-mUD Directly connect with me on:- https://topmate.io/shilpa_das10 #Databricks #DeltaTables #LakehouseArchitecture #TimeTravel #BigData #DataEngineering #DataScience #OptimizeCommand #VacuumCommand #DatabricksTutorial