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Found 136 Skills
Create interactive maps with markers, heatmaps, routes, and choropleth layers. Use when visualizing geographic data, plotting locations, or creating map-based reports.
Generate interactive graph visualizations in the browser from any data - codebases, infrastructure, relationships, knowledge maps
Use when designing visual interfaces, data visualizations, educational content, or presentations and need to ensure they align with how humans naturally perceive, process, and remember information. Invoke when user mentions cognitive load, visual hierarchy, dashboard design, form design, e-learning, infographics, or wants to improve clarity and reduce user confusion. Also applies when evaluating existing designs for cognitive alignment or choosing between design alternatives.
Build production-grade interactive dashboards with Plotly Dash - enterprise features, callbacks, and scalable deployment
Analyze user conversion funnels, calculate step-by-step conversion rates, create interactive visualizations, and identify optimization opportunities. Use when working with multi-step user journey data, conversion analysis, or when user mentions funnels, conversion rates, or user flow analysis.
Detect whether U.S. inflation pressure is entering a slowdown or reversal phase through the cycle turning points of the CASS Freight Index. It is used to judge whether 'inflation is cooling down' and verify whether the market's macro narrative of interest rate cuts and inflation decline is supported by real economic data.
Calculate the deviation of asset prices relative to the long-term exponential growth trend line, assess whether the current period falls within a historical extreme range, and optionally perform macro factor analysis to evaluate the market regime.
Evaluate the probability and path of copper prices breaking through key levels or entering a 'back-and-fill' pullback to support levels using cross-asset signals (global stock market resilience + Chinese interest rate environment).
A high-level interactive graphing library for Python. Ideal for web-based visualizations, 3D plots, and complex interactive dashboards. Built on plotly.js, it allows users to zoom, pan, and hover over data points in a browser-based environment. Use for interactive charts, web applications, Jupyter notebooks, 3D data visualization, geographic maps, financial charts, animations, time-series analysis, and building production-ready dashboards with Dash.
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.
Provides comprehensive guidance for Lime ECharts including chart creation, configuration, data visualization, and interactive charts. Use when the user asks about Lime ECharts, needs to create charts, visualize data, or work with ECharts features.
A Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Great for exploring relationships between variables and visualizing distributions. Use for statistical data visualization, exploratory data analysis (EDA), relationship plots, distribution plots, categorical comparisons, regression visualization, heatmaps, cluster maps, and creating publication-quality statistical graphics from Pandas DataFrames.