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lab challenge

Using Python to Cleanse and Rationalize Data Challenge

Difficulty: Beginner
Duration: Up to 2 hours and 30 minutes
Students: 486
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Get challenged in a real environmentProve your skills in a real-world, provisioned environment.
Push your limitsComplete an unguided mission within the time limit.
See resultsTest your problem-solving skills and track your progress.

Description

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

Prerequisites

  • Completion of the Practical Data Science with Python learning path is recommended

Intended audience

  • Budding data scientists
  • Python beginners

What will be assessed

  • Python functions
  • String operations
  • User-defined functions

Covered topics

Development
Python

Mission

Use Python to Cleanse and Rationalise Data Challenge

Lab Rules