웹 기반 통계 분석 SPA 개발 스킬. 이상치 탐지(Outlier Detection)와 행별 통계 분석(Row Statistics)을 수행하는 React 애플리케이션 구현. Z-Score, IQR, MAD, Grubbs, Winsorize 이상치 탐지와 T-test, ANOVA 통계 분석 지원. Copy & Paste 또는 CSV/TXT 파일 드래그 앤 드롭으로 데이터 입력, Recharts를 활용한 시각화 기능 포함. 모든 데이터는 로컬에서만 처리되며 네트워크 전송 없음.
Teach Bayesian approaches to meta-analysis including prior specification, MCMC methods, and interpretation of posterior distributions. Use when users want to incorporate prior knowledge, need probabilistic interpretations, or are working with sparse data.
Clean and standardize vehicle insurance CSV/Excel data. Use when handling missing values, fixing data formats, removing duplicates, or standardizing fields. Mentions "clean data", "handle nulls", "standardize", "duplicates", or "normalize".
Configure chart axis mappings and display options for all chart types in Drizzle Cube.
Generate the social value report from CSV inputs by detecting CSVs, anonymising them, and producing a month-by-month markdown report.
This skill should be used when the user asks "Chart.js gradients", "Chart.js linear gradient", "Chart.js radial gradient", "custom Chart.js chart type", "extend Chart.js", "derived chart type", "custom Chart.js scale", "Chart.js programmatic events", "Chart.js setActiveElements", "Chart.js custom controller", or needs help with advanced Chart.js v4.5.1 techniques.
ParaView scientific visualization for volume data and meshes. Use this skill when Claude needs to: (1) Visualize 3D volume data (CT, MRI, scientific simulations), (2) Create isosurfaces, slices, volume renderings, (3) Visualize vector fields with streamlines/glyphs, (4) Generate publication-quality screenshots, (5) Work with VTK, EXODUS, RAW, or other scientific data formats
Python 생태계(Jupyter, Pandas, Scikit-learn)를 활용하여 데이터에서 심층적인 인사이트를 도출하는 전문 분석 워크플로우입니다.
Standard and NaN-robust statistical functions for data analysis, histograms, and correlation matrices. Triggers: statistics, mean, nanmean, histogram, corrcoef, percentile, std.
Analyze disk usage across directories, identify large/old directories, and generate storage reports. Use when you need to find directories consuming disk space, identify candidates for cleanup (directories older than X days AND larger than Y MB), sort results by size, or generate disk usage reports. Supports filtering by age and size, automatic sorting by disk space, and file-based report generation.
Data analysis and visualization expert using Python pandas and visualization libraries
R 4.4+ best practices with testthat 3.2, lintr 3.2, and data analysis patterns.
This skill should be used when the user asks "Chart.js plugin", "custom Chart.js plugin", "Chart.js plugin hooks", "Chart.js beforeDraw", "Chart.js afterDraw", "custom chart type", "extend Chart.js", "Chart.js API", "Chart.js update", "Chart.js destroy", "Chart.js methods", "Chart.js events", "Chart.js canvas", "Chart.js TypeScript", "custom scale", "Chart.js DatasetController", "Chart.js Scale", or needs help creating custom Chart.js v4.5.1 plugins, extensions, custom chart types, custom scales, or using the API.
Garante padrões consistentes para relatórios no Easy Budget (filtros, exportação, visualização).
Provides CollectionView alternatives for AvaloniaUI using DataGridCollectionView and ReactiveUI. Use when filtering, sorting, or grouping collections in AvaloniaUI applications.
Write structured experiment sections (methods + results + discussion) for NQS + SQD projects in this repository, based on contents of results/ and figures/.
Aggregate-only summarizer for K18 QC artifacts; produces summary outputs and appends manifest rows when format is confirmed.
Guide statistical analysis of NFL data using nflreadpy MCP tools. Use when analyzing real NFL statistics for research, validation, or comparison.
