5.2 - Learning Objectives
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Practice Questions
Test your understanding with targeted questions
What does data quality refer to?
💡 Hint: Think about the characteristics that make data usable.
Name one technique to handle missing data.
💡 Hint: Think about common approaches you've learned.
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Interactive Quizzes
Quick quizzes to reinforce your learning
Which of the following is a common issue in data quality?
💡 Hint: Consider what happens to data when there are repeated entries.
True or False: Normalization is used to scale data to a specific range.
💡 Hint: What range are we typically targeting with normalization?
1 more question available
Challenge Problems
Push your limits with advanced challenges
Given a dataset with missing values, outline a strategy to handle these issues while preserving the dataset's integrity.
💡 Hint: Think about the context and significance of each data field.
How would you write a Python function that detects and removes duplicates based on specific columns?
💡 Hint: Understand how to apply `drop_duplicates()` within a function context.
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Reference links
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