Data wrangling (also called data munging) refers to transforming raw, messy, or unstructured data into a clean and structured format suitable for analysis.
Option A: Correct. Raw data often contains missing values, duplicates, or irregular formats. Wrangling prepares it for conventional analytics and machine learning.
Option B: Incorrect. Wrangling does not involve "modified meaning"; it focuses on cleaning, structuring, and integrating.
Option C: Incorrect, since only A is correct.
Option D: Incorrect, because wrangling is explicitly described in A.
Thus, the correct answer is Option A.
[Reference:, DASCA Data Scientist Knowledge Framework (DSKF) – Data Engineering Practices: Data Wrangling & Preprocessing.]
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