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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is data wrangling?
π‘ Hint: Think about how you would prepare data for analysis.
Question 2
Easy
Why is handling missing data important?
π‘ Hint: Consider the implications of missing information.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the primary goal of data wrangling?
π‘ Hint: Think about what steps are involved before analysis can happen.
Question 2
True or False: Cleaning data is the only aspect of data wrangling.
π‘ Hint: Consider the various processes involved in data preparation.
Solve and get performance evaluation
Push your limits with challenges.
Question 1
Imagine you have a dataset with 1000 entries, of which 250 have missing values. How would you approach cleaning this data to prepare for analysis?
π‘ Hint: Think about the trade-offs between data loss and accuracy.
Question 2
Discuss an instance where outlier values in a dataset could mislead an analysis. What steps would you take to prevent this?
π‘ Hint: Consider methods youβve learned about detecting outliers.
Challenge and get performance evaluation