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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What function would you use to check for missing values in a DataFrame?
💡 Hint: Think of which method allows you to see null values.
Question 2
Easy
How would you remove duplicates from a DataFrame?
💡 Hint: Look for a method that deals with duplication.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the primary purpose of data cleaning?
- To enhance data visualization
- To ensure data accuracy
- To increase data size
💡 Hint: Think about why we start any analysis.
Question 2
True or False: Dropping rows with missing data is always the best solution.
- True
- False
💡 Hint: Consider the balance between data loss and integrity.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You are given a dataset with missing values, duplicates, and outliers. Describe a stepwise approach you would take to preprocess the data for analysis.
💡 Hint: Think through each preprocessing step logically and sequentially.
Question 2
A dataset shows high variance in income values that negatively impact a predictive model's performance. Propose a solution for this issue.
💡 Hint: Consider techniques that adjust data distributions.
Challenge and get performance evaluation