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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What function do you use to check for missing values in pandas?
💡 Hint: Think about functions that check for the presence of values.
Question 2
Easy
What represents a missing value in a DataFrame?
💡 Hint: Consider how NaN is used in your datasets.
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 does the isnull() function do in pandas?
- Identifies missing values
- Summarizes data
- Converts data types
💡 Hint: Consider what you need to track missing entries.
Question 2
True or False: Missing values do not affect the integrity of a dataset.
- True
- False
💡 Hint: Reflect on how missing data could mislead your analysis.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You are given a dataset with several columns. Write Python code to check for missing values in the Age and Income columns only, and print a summary of these values.
💡 Hint: Focus on selecting specific columns in your DataFrame.
Question 2
Explain the potential consequences of ignoring missing values in data and how it could impact your analysis.
💡 Hint: Consider the importance of data integrity in analytics.
Challenge and get performance evaluation