6. Computing and Data

Data Wrangling — Quiz

Test your understanding of data wrangling with 5 practice questions.

Practice Questions

Question 1

Which of the following data wrangling techniques is most appropriate for standardizing inconsistent text entries in a categorical variable, such as 'gender' or 'marital status'?

Question 2

An insurance dataset contains a 'claim date' column and a 'policy start date' column. To calculate the duration a policy was active before a claim was made, which data transformation technique is most suitable?

Question 3

In an insurance dataset, a column named 'premium amount' contains negative values, which are logically impossible. What is the most appropriate action to take for these negative values during data cleaning?

Question 4

A data analyst observes that the 'age' column in an insurance dataset has values like 0 and 150, which are outside the plausible range for human age. Which data validation check would identify these erroneous entries?

Question 5

Consider an insurance dataset where the 'claim amount' column is heavily right-skewed. Which data transformation technique would be most effective in making the distribution more symmetrical and suitable for linear models?