Loading...
Loading...
Found 257 Skills
Expert data analysis covering SQL, visualization, statistical analysis, business intelligence, and data storytelling.
The foundational library for creating static, animated, and interactive visualizations in Python. Highly customizable and the industry standard for publication-quality figures. Use for 2D plotting, scientific data visualization, heatmaps, contours, vector fields, multi-panel figures, LaTeX-formatted plots, custom visualization tools, and plotting from NumPy arrays or Pandas DataFrames.
Data analysis expert for statistics, visualization, pandas, and exploration
Plotly Chart Generator - Auto-activating skill for Visual Content. Triggers on: plotly chart generator, plotly chart generator Part of the Visual Content skill category.
Analyze historical downtrend durations and generate interactive HTML histograms showing typical correction lengths by sector and market cap.
Implements Syncfusion .NET MAUI Pyramid Chart (SfPyramidChart) for visually representing hierarchical, proportional, and parts-to-whole data using pyramid-shaped segments. Use this for pyramid charts, hierarchical data visualization, proportional data display, or segment-based charts. This skill covers installation, data binding, legends, tooltips, data labels, appearance customization, and gradients.
Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.
Create powerful interactive charts with Apache ECharts - balanced ease-of-use and customization
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.
Guide for creating Observable Notebooks 2.0, the open-source notebook system for interactive data visualization and exploration. Use this skill when creating, editing, or building Observable notebooks.
Analyze CSV files, generate summary statistics, and create visualizations using Python and pandas. Use when the user uploads, attaches, or references a CSV file, asks to summarize or analyze tabular data, requests insights from CSV data, or wants to understand data structure and quality.
Build apps on Databricks Apps platform. Use when asked to create dashboards, data apps, analytics tools, or visualizations. Invoke BEFORE starting implementation.