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Found 134 Skills
Create Vega and Vega-Lite visualizations with ES|QL data sources in Kibana. Use when building custom charts, dashboards, or programmatic panel layouts beyond standard Lens charts.
Answer data questions -- from quick lookups to full analyses. Use when looking up a single metric, investigating what's driving a trend or drop, comparing segments over time, or preparing a formal data report for stakeholders.
Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.
This skill should be used when analyzing CSV datasets, handling missing values through intelligent imputation, and creating interactive dashboards to visualize data trends. Use this skill for tasks involving data quality assessment, automated missing value detection and filling, statistical analysis, and generating Plotly Dash dashboards for exploratory data analysis.
Design and build dashboards that track key performance indicators. Select relevant metrics, visualize data effectively, and communicate insights to stakeholders.
基于给定文字内容创建精美信息图。当用户请求创建信息图时使用。
LayerChart Svelte 5 patterns. Use for chart components with tooltip snippets, Chart context access, and all Svelte 5 snippet patterns for tooltips, gradients, highlights, and axes.
Fast Python framework for building interactive web apps, dashboards, and data visualizations without HTML/CSS/JavaScript. Use when user wants to create data apps, ML demos, dashboards, data exploration tools, or interactive visualizations. Transforms Python scripts into web apps in minutes with automatic UI updates.
Build self-contained interactive HTML dashboards with Chart.js, dropdown filters, and professional styling. Use when creating dashboards, building interactive reports, or generating shareable HTML files with charts and filters that work without a server.
Designs effective KPI dashboards with proper metric selection, visual hierarchy, and data visualization best practices. Use when building executive dashboards, creating analytics views, or presenting business metrics.
Data analysis best practices with pandas, numpy, matplotlib, seaborn, and Jupyter notebooks.
Create simple, responsive charts quickly with Chart.js