| name | plotly-visualization |
| version | 1.0.0 |
| category | data |
| description | Generate interactive Plotly and Matplotlib visualizations from DataFrames with configurable templates and multi-format support. |
| type | reference |
| globs | ["src/assetutilities/common/visualization/**","src/assetutilities/common/visualizations.py","src/assetutilities/common/visualization.py"] |
| alwaysApply | false |
| tags | [] |
| scripts_exempt | true |
Plotly Visualization Skill
Overview
This skill provides comprehensive visualization capabilities using both Plotly (interactive) and Matplotlib (static) backends. It enables generation of line plots, scatter plots, polar plots, bar charts, timelines, and multi-series visualizations from pandas DataFrames with YAML-driven configuration.
Key Components
Visualization Class (visualizations.py)
Main matplotlib-based visualization engine:
generate_time_line(data, plt_settings) - Create timeline visualizations from DataFramefrom_df_array(df_array, plt_settings) - Plot multiple DataFrames as arrayfrom_df_columns(df, plt_settings) - Generate line, scatter, polar, or bar plots from DataFrame columns
VisualizationTemplatesPlotly (visualization_templates_plotly.py)
Plotly template generator for interactive charts:
get_xy_line_df(custom_analysis_dict) - XY line plot templatesget_x_datetime_input_plotly(custom_analysis_dict) - DateTime-based plot templates
Specialized Modules
visualization_xy.py - XY coordinate plottingvisualization_polar.py - Polar coordinate systemsvisualization_common.py - Shared utilities
Usage Patterns
Public-facing risk / incident infographics
When generating infographic statistics from incident, safety, reliability, or risk datasets, treat the evidence taxonomy as part of the visualization contract. Before rendering:
- name each metric with its exact evidence scope;
- persist numerator evidence (
matched_incident_ids) and exclusions (excluded_incident_ids);
- show denominators alongside percentages;
- avoid broad substring classifiers that can overcount (
weather, sank, overboard are common traps);
- include caveats in both stats JSON and rendered HTML;
- run adversarial review on metric semantics before merging or publishing.
See references/risk-infographic-evidence-taxonomy.md for the checklist and false-positive examples.
YAML Configuration Structure
visualization:
type:
