Handle Missing Data Like a Pro: Python Data Cleaning Techniques | RayVision |#DataAnalytics #Python

Master the art of data cleaning! Learn effective strategies to handle missing values in your Python datasets. Discover techniques like deletion, imputation, and more to ensure data quality.

Question: What is the most common approach to handling missing values in a dataset?

A) Deleting rows with missing values
B) Imputing missing values with mean/median
C) Ignoring missing values
D) All of the above
Answer: B) Imputing missing values with mean/median

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