Advanced Features in edaflowο
This section covers advanced capabilities for power users:
Computer Vision EDA: Class-wise image sample visualization, image quality assessment
Smart Categorical Encoding: Automated selection and application of encoding strategies
Outlier Handling: Multiple statistical methods for robust outlier detection and replacement
Integration with pandas, numpy, scikit-learn, plotly, and more
Customizable display and dark mode support for notebooks
New Advanced Featuresο
Faceted grid visualization: display_facet_grid(df, col, row, hue, kind, β¦)
Feature scaling utility: scale_features(df, columns, method)
Rare category grouping: group_rare_categories(df, column, threshold, new_value)
Figure export API: export_figure(fig, filename, format, dpi)
See the API Reference for details on each advanced function, and the Visualization Guide for code examples.