pytimetk 2.4.0 Release Notes

Overview

This release introduces significant enhancements to visualization capabilities, integrates tidy selectors for improved column handling, completes the migration to Ray for parallelism, and includes various performance optimizations and bug fixes. Key themes include better diagnostics plotting, more flexible data manipulation, and improved documentation.

New Features

• Advanced Plotting Diagnostics: Added new APIs for visualizing time series diagnostics. These functions provide interactive and insightful plots to analyze correlation, seasonality, and trends.

  | Function | Description | |---------------------------|-------------| | plot_acf_diagnostics | Plot ACF, PACF, and CCF with interactive dropdowns. | | plot_seasonal_diagnostics | Box/violin plots for seasonal features (e.g., hour, weekday, month). | | plot_stl_diagnostics | Decompose series into observed, season, trend, remainder, and seasonally adjusted components. | | plot_time_series_boxplot | Rolling distribution boxplots with optional smoothers. | | plot_time_series_regression | Fit and visualize linear regressions with observed vs. fitted/residuals views. |