Handling missing data Numerical Data Simple Imputer

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Simple Imputer is a practical solution for filling missing numerical values in a dataset. This method replaces missing entries with the mean, median, or a specified constant, providing a straightforward approach to address and mitigate the impact of missing numerical data in your dataset. • Code Used: https://github.com/campusx-official/1... • ============================ • Do you want to learn from me? • Check my affordable mentorship program at : https://learnwith.campusx.in/s/store • ============================ • 📱 Grow with us: • CampusX' LinkedIn: / campusx-official • CampusX on Instagram for daily tips: / campusx.official • My LinkedIn: / nitish-singh-03412789 • Discord: / discord • E-mail us at [email protected] • ⌚Time Stamps⌚ • 00:00 - Intro • 00:37 - Handling Missing Numerical Data • 03:33 - Mean / Median Imputation • 07:55 - Code Demo • 17:15 - Imputation using SKlearn • 20:15 - Arbitarry Value Imputation • 22:40 - Code Demo • 25:57 - End of Distribution Imputation • 30:09 - Outro

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