Your question is Exploratory Data Analysis With Outliers. Take a moment with it on the right.
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Perform exploratory data analysis on a given data set, identify outliers, handle them, and plot them.
Use Python with pandas and NumPy to profile schema, missingness, distributions, and numeric relationships. Apply and justify an outlier strategy such as IQR, z-score, winsorization, removal, or retention, and show before-and-after results with clear visualizations. Preserve an audit-friendly output containing original values, treatment decisions, and summary statistics.