Using Python to Cleanse and Rationalize Data Challenge
Push your skills to the next level in a live environment
Lab Steps
The hands-on lab is part of this learning path
Beginner
2h 30m
286
Lab challenges are hands-on labs with the gloves off. You jump into an auto-provisioned cloud environment and are given a goal to accomplish. No instructions, no hints. To pass, you'll have a limited time to demonstrate your problem-solving skills and get the checks that inspect the state of your lab environment.
Data cleansing is an important task that every data scientist should be comfortable performing. You will put your basic knowledge of Python to work in this lab challenge in order to perform a simple form of data cleansing on text.
In this lab challenge, you will be provided with a web browser-based integrated development environment (IDE) with an incomplete code file pre-loaded. The challenge mission and code file both describe what you must do to complete the challenge before time runs out. This is a real environment, which means you can prove your knowledge in an applied situation, leaving behind multiple choice questions for a dynamic performance-based exam situation.
Updates
February 7th, 2021 - Added a hint to explain how to compare your code against the expected output
What will be assessed
- Python functions
- String operations
- User-defined functions
Intended audience
- Budding data scientists
- Python beginners
Prerequisites
- Completion of the Practical Data Science with Python learning path is recommended
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