Answer-first summary for fast verification
Answer: cleansing and preprocessing raw data.
## 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.
Author: LeetQuiz Editorial Team
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In a data analysis project, data wrangling refers to:
A
cleansing and preprocessing raw data.
B
deriving numeric data from internal and external sources.
C
exploratory data analysis, feature selection, and feature engineering.
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