Practice Removing Duplicates (5.5) - Data Cleaning and Preprocessing - Data Science Basic

Practice: Removing Duplicates

Lesson 5.5Data Cleaning and Preprocessing

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8 questions

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3 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
2 questions · about 1 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is a duplicate in a dataset?
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Think about how counting the same person twice affects totals.
Question 2.
What is the function used to remove duplicates in pandas?
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Think about terms that start with 'd' for 'duplicate'.
3Question 3.
What is the primary reason for removing duplicates in data?
- To simplify the code
- To obtain accurate analysis
- To make data look nicer
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Think about how mistakes in counting can affect results.
4Question 4.
True or False? The method drop_duplicates() removes duplicates based on specific column values only.
- True
- False
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What does the default behavior do?
Question 5.
You have a customer DataFrame where customers are listed multiple times with the same purchasing behavior. Describe the steps you would take to ensure that your analysis considers each customer only once.
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What are the two main pandas functions you recall?
Question 6.
Consider a dataset of test scores. If two students have identical scores listed multiple times, what effect would that have on the average score, and how would you address it?
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Why is it critical to have unique scores for accurate statistics?

4 more questions in this section. Enroll free to practise them all.