This skill should be used when working with CSV files to create interactive data visualizations, generate statistical plots, analyze data distributions, create dashboards, or perform automatic data profiling. It provides comprehensive tools for exploratory data analysis using Plotly for interactive visualizations.
Build a standalone HailoRT inference application.
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
Displays chronological events and activity through timelines, activity feeds, Gantt charts, and calendar interfaces. Use when showing historical events, project schedules, social feeds, notifications, audit logs, or time-based data. Provides implementation patterns for vertical/horizontal timelines, interactive visualizations, real-time updates, and responsive designs with accessibility (WCAG/ARIA).
Builds dashboards, reports, and data-driven interfaces requiring charts, graphs, or visual analytics. Provides systematic framework for selecting appropriate visualizations based on data characteristics and analytical purpose. Includes 24+ visualization types organized by purpose (trends, comparisons, distributions, relationships, flows, hierarchies, geospatial), accessibility patterns (WCAG 2.1 AA compliance), colorblind-safe palettes, and performance optimization strategies. Use when creating visualizations, choosing chart types, displaying data graphically, or designing data interfaces.
Query chart, dashboard, report or build a new one. Answer question using data.
Builds tables and data grids for displaying tabular information, from simple HTML tables to complex enterprise data grids. Use when creating tables, implementing sorting/filtering/pagination, handling large datasets (10-1M+ rows), building spreadsheet-like interfaces, or designing data-heavy components. Provides performance optimization strategies, accessibility patterns (WCAG/ARIA), responsive designs, and library recommendations (TanStack Table, AG Grid).
Mom Test questioning toolkit, JTBD analysis, interview conduct, assumption testing framework, and hypothesis design
源泉徴収票の画像を読み取り構造化データを返す。 他のスキルから呼び出されるほか、直接ユーザーが呼び出すことも可能。
Data visualization with chart selection, color theory, and annotation best practices. Covers chart types (bar, line, scatter, heatmap), axes rules, and storytelling with data. Use for: charts, graphs, dashboards, reports, presentations, infographics, data stories. Triggers: data visualization, chart, graph, data chart, bar chart, line chart, scatter plot, data viz, visualization, dashboard chart, infographic data, data presentation, chart design, plot, heatmap, pie chart alternative
Execute ES|QL (Elasticsearch Query Language) queries, use when the user wants to query Elasticsearch data, analyze logs, aggregate metrics, explore data, or create charts and dashboards from ES|QL results.
Run IV, DiD, and RDD analyses in R with proper diagnostics
Run regression analyses in Stata with publication-ready output tables.
Panel data analysis with Python using linearmodels and pandas.
Clean and transform messy data in Stata with reproducible workflows
Generate publication-ready regression tables in LaTeX.
Create original surveys, benchmarks, and aggregated data nobody else has. Automate data collection for content moats. Triggers on: "create original data", "proprietary data", "survey design", "benchmark study", "original research", "data-driven content", "create a survey", "industry benchmark", "aggregated data", "unique data", "first-party data", "data moat", "generate research data", "create a study", "original statistics", "data nobody else has", "competitive data advantage".
Ejecuta análisis estadístico de variables latentes siguiendo un flujo de trabajo específico (numéricas primero, categóricas después) y aplicando reglas de selección de variables basadas en un umbral de correlación de 0.7.
货拉拉(HLL)数据分析DSL生成器，解析自然语言生成包含维度、指标及复杂算子的JSON查询结构，支持HLL特定财年逻辑及反向指标处理。
读取股票5分钟K线CSV文件，按日期分组，计算基于昨日收盘价的百分比变化，过滤无效数据（长度不一致、NaN、Inf），进行Z-score归一化，并使用TimeSeriesKMeans（DTW/SoftDTW度量）进行聚类。
