Visualization¶
Interactive plots for exploratory analysis, forecast inspection, seasonal decomposition, correlation diagnostics, model selection geometry, and evaluation dashboards. All charts are built with Plotly.
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How to Visualize Correlations
Pairwise correlation heatmaps, scatter matrices, cross-correlation at multiple lags, and lag scatter plots for multivariate time series diagnostics.
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How to Visualize Forecast Evaluation Results
Use plot_calibration, plot_score_per_step, and plot_forecast to diagnose forecast accuracy and interval calibration visually.
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Exploratory Visualization
Exploratory time series visualisation with raw series plots, rolling statistics overlays, seasonal overlays, subseries diagnostics, distribution boxplots, missing data pattern auditing, outlier detection, and resampling comparison.
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Forecast Visualization
Visualise point forecasts from single and multiple models, decomposition pipeline components, and time weight decay functions with interactive Plotly.
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How to Visualize Model Selection Results
Visualise CV fold geometry with expanding and sliding window splitters and hyperparameter search results with plot_splits and plot_cv_results_scatter.
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Seasonal Analysis
Seasonal overlays, subseasonal structure, ACF/PACF correlation patterns, and STL decomposition for monthly, quarterly, and long-cycle datasets.
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How to Visualize Signal Processing
Butterworth low-pass filtering with frequency spectrum analysis and phase shift inspection on half-hourly electricity demand data using Plotly.
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How to Visualize Forecasts
Plot point forecasts, compare multiple models, render prediction interval bands, inspect residual diagnostics, and check interval calibration.