Practice Log Transformation (2.3.2) - Data Wrangling and Feature Engineering

Practice: Log Transformation

Lesson 2.3.2Data Wrangling and Feature Engineering

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9 questions

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6 sample questions

Question 1.
What is log transformation?
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Think about how we handle skewed data.
Question 2.
Name one type of data that can benefit from log transformation.
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Consider data that has extreme values.
3Question 3.
What is the purpose of log transformation?
- To increase data volume
- To compress skewed data
- To eliminate outliers
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Think about the characteristics of the data you're handling.
4Question 4.
True or False: Log transformation can be applied to negative values.
- True
- False
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Consider the properties of logarithmic functions.
Question 5.
You have a dataset of house prices that are heavily skewed. Explain how you would apply log transformation and what the expected outcome would be on your regression analysis.
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Think about how you would represent price changes to clients.
Question 6.
You encounter a dataset with many zero and negative values. How would you handle the log transformation in such a scenario?
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Consider what happens to logs of zero and negative numbers.

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