Plots

anomalies_chart()

Plot time-series signals with detected anomaly regions highlighted in red.

confusion_matrix()

Plot a confusion matrix heatmap comparing predicted vs actual binary classes.

data_table()

Render the dataframe as a styled table with Wizata theme colors.

feature_importance()

Plot the top-N feature importances of a trained model as a horizontal bar chart.

Scans context.models for a model whose underlying trained_model exposes feature_importances_

(RandomForestRegressor, RandomForestClassifier, GradientBoostingClassifier, etc.). Uses

ml_model.input_columns for feature labels. Bars are sorted ascending so the most important

feature is at the top when rendered.

Property: top_n (default 15) — maximum number of features to display.

parallel_coordinates()

Plot parallel coordinates colored by anomaly type for multi-dimensional analysis.

process_variability()

Parallel coordinates plot showing process configurations variability, colored by a quality

outcome. Columns are ordered by type: telemetry, setpoints, recommendations, calculated,

with the target/quality column last. Each axis label is prefixed with a type tag

([T], [SP], [REC], [C], [Q]) for quick identification.

Column selection:

• color_by: property name of the quality column used for coloring (defaults to

context.properties['target_feat'] if set, otherwise the last numeric column).

• color_reverse: set to true (default) when a LOWER color_by value is better

(e.g. residual_co2) — low values will be green. Set to false when higher is better

(e.g. 'good_bottles') — high values will be green.

r_squared()

Plot actual vs predicted scatter with R-squared coefficient and reference diagonal.

setpoint_recommendation()

Compare current vs recommended setpoint values as a grouped bar chart with a summary table.

Auto-pairs columns ending in '_recommended' with the matching setpoint column, validated via

context.datapoints BusinessType.SET_POINTS. Uses the last row (most recent state). The top half

shows a horizontal grouped bar chart (Current vs Recommended) with type-colored labels; the

bottom half is a summary table with Setpoint | Current | Recommended | delta | delta (%).

ts_chart()

Plot all dataframe columns as time-series lines over the index.