What are Missing Values? 🤔
Missing values occur when no data value is stored for a variable in an observation. This can happen for several reasons such as skipped questions in surveys, or data corruption. In data science, handling missing values properly is crucial for accurate analysis.
Why do They Matter? 🚀
Missing values can introduce biases, reduce the efficiency of models, and lead to incorrect conclusions. Techniques like imputation, omission, or using algorithms that account for missing data are necessary for robust data processing.
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