5.3 - Handling Missing Data
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Practice Questions
Test your understanding with targeted questions
What does NaN stand for in a dataset?
💡 Hint: Think about what missing data implies.
What is one method to handle missing data?
💡 Hint: Consider ways to eliminate incompleteness.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What does NaN stand for?
💡 Hint: Consider what 'missing' means.
What is one method to handle missing data?
💡 Hint: Think about how completeness affects data quality.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Given a dataset with missing values in multiple columns, provide a Python code to impute using both mean and median.
💡 Hint: Remember to import the necessary libraries first.
Discuss a scenario where imputing data could introduce bias and provide a suggestion to mitigate this.
💡 Hint: Think about distribution shapes and imputation differences.
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