MLS-C01 Exploratory Data Analysis Practice Question

Correct answer & explanation

Removing rows with negative transaction amounts is the most appropriate approach during EDA. The negative values are data entry errors, not legitimate transactions. Removing them cleans the dataset without introducing bias from imputation or transformation. Option A is incorrect because imputing negative values with the median would treat the errors as missing data, but they are not missing; they are erroneous. This could distort the distribution. Option C is incorrect because taking absolute values would convert errors into positive values, adding noise and misrepresenting the data (e.g., a negative $100 error becomes a legitimate $100 transaction). Option D is incorrect because capping negative values at zero would create a spike at zero and distort the distribution, treating errors as valid zero amounts. Therefore, removal is the cleanest approach for erroneous data.