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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What function do we use to detect missing values in a pandas DataFrame?
💡 Hint: Think about what method checks for NaN values.
Question 2
Easy
Which method would remove all rows with missing data?
💡 Hint: Consider the action of dropping missing entries.
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
Which function is used to drop rows with missing values in pandas?
- dropna()
- remove_na()
- isnull()
💡 Hint: It starts with 'drop' and deals with NaN.
Question 2
True or False: Z-score is used to detect outliers.
- True
- False
💡 Hint: Consider what Z represents in statistical contexts.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a dataset with a 'Height' column in centimeters, write a function to find and remove outliers based on the IQR method. Explain each step taken.
💡 Hint: Remember to define Q1 and Q3 before filtering!
Question 2
Create a DataFrame with duplicate entries of a fictional customer dataset. Write code to identify and display these duplicates before using drop_duplicates() to remove them. Explain why this step is necessary.
💡 Hint: Think of duplicates like repeating unwanted guests at a party who mess up the fun!
Challenge and get performance evaluation