1.4.3 - Data Cleaning and Preprocessing
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Practice Questions
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What is data cleaning?
💡 Hint: Think about why accuracy in data is important.
Name one reason why standardization is important.
💡 Hint: Consider the formats of the data.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What does data cleaning involve?
💡 Hint: It's the opposite of introducing data.
True or False: Standardization ensures that all data points are on the same scale.
💡 Hint: Consistency is key in data analysis.
1 more question available
Challenge Problems
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You inherit a dataset with 20% missing values across various columns. Discuss a comprehensive strategy for addressing these missing values, including potential biases in your approach.
💡 Hint: Categorize missingness and determine an ideal approach of filling in or removing.
You notice that categorical data in your dataset is inconsistent (e.g., 'male' vs 'Male' vs 'M'). Create a step-by-step guide for standardizing this entry.
💡 Hint: Consider the majority format selection or how the analysis might impact result comprehensibility.
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