Explanation

Option A is correct because data wrangling specifically refers to the process of cleaning and transforming raw data into a usable format. This includes handling missing values, removing duplicates, standardizing formats, and dealing with outliers.

Option B is incorrect because deriving numeric data from sources is part of data collection or data acquisition, not data wrangling.

Option C is incorrect because exploratory data analysis, feature selection, and feature engineering typically occur after data wrangling. These are separate stages in the data analysis pipeline that build upon the cleaned data.