「visualization」の検索結果

Design and implement parallax scrolling and scrollytelling data visualizations. Use when the user asks for parallax scrolling, scrollytelling, scroll-driven timelines, sticky graphics, Scrollama, ScrollTrigger, ScrollTimeline, view timelines, rich-media timelines, moviescrollers, scroll-scrubbed charts, staged narrative reveals, or interactive visual stories where scrolling changes a data visualization or media scene.

日本語の概要は準備中です。原文の説明を表示しています。

Build custom data visualizations with D3. Use when the user needs SVG or DOM-based charts, rich annotation, domain-native contextual backgrounds, data joins, custom scales or interactions, scroll-driven SVG scene states, or precise control over browser visualization behavior.

日本語の概要は準備中です。原文の説明を表示しています。

Render data visualizations with Canvas2D. Use when the visualization needs high mark counts, fast redraws, immediate-mode rendering, custom hit testing, or a hybrid Canvas plus SVG or HTML architecture.

日本語の概要は準備中です。原文の説明を表示しています。

Design dashboards and live visualization systems. Use when the user needs monitoring views, streaming charts, coordinated interactions, downsampling, or performance-aware operational visualization.

日本語の概要は準備中です。原文の説明を表示しています。

Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards. Supports both quick visualizations (Plotly Express) and fine-grained customization (graph objects). Outputs interactive HTML or static images (PNG, PDF, SVG).

日本語の概要は準備中です。原文の説明を表示しています。

Comprehensive data visualization toolkit for creating beautiful, mathematically elegant visualizations with D3.js, Chart.js, and custom SVG. Use when (1) building interactive data visualizations, (2) designing color palettes for charts, (3) choosing scales and visual encodings, (4) creating data pipelines from Census/SEC/Wikipedia APIs, (5) crafting narrative-driven data stories, (6) making perceptually accurate charts, or (7) implementing force-directed networks, timelines, or geographic maps.

日本語の概要は準備中です。原文の説明を表示しています。

The analysis and visualization of alternative splicing (AS) events from RNA sequencing data remains challenging. SpliceWiz is a user-friendly and performance-optimized R package for AS analysis, by processing alignment BAM files to quantify read counts across splice junctions, IRFinder-based intron retention quantitation, and supports novel splicing event identification. We introduce a novel visualization for AS using normalized coverage, thereby allowing visualization of differential AS across

日本語の概要は準備中です。原文の説明を表示しています。

This R package supports interactive visualization of multi-channel images and segmentation masks generated by imaging mass cytometry and other highly multiplexed imaging techniques using shiny. The cytoviewer interface is divided into image-level (Composite and Channels) and cell-level visualization (Masks). It allows users to overlay individual images with segmentation masks, integrates well with SingleCellExperiment and SpatialExperiment objects for metadata visualization and supports image do

日本語の概要は準備中です。原文の説明を表示しています。

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.

日本語の概要は準備中です。原文の説明を表示しています。

Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards. Supports both quick visualizations (Plotly Express) and fine-grained customization (graph objects). Outputs interactive HTML or static images (PNG, PDF, SVG).

日本語の概要は準備中です。原文の説明を表示しています。

Apply data visualization in reproducible local data workflows with version-aware APIs, explicit assumptions, and validation. Use when the user chooses data visualization or its strengths fit the task.

日本語の概要は準備中です。原文の説明を表示しています。

Production guidance for converting sourced data and approved claims into truthful, accessible, deterministic animated visualizations with D3. Use for data-driven charts, maps, networks, hierarchies, transitions, annotations, responsive video variants, frame-by-frame browser rendering, and visualization QA; not for generic dashboards, unsourced decorative charts, or ordinary motion graphics without a data contract.

日本語の概要は準備中です。原文の説明を表示しています。

Assists with building custom interactive data visualizations using D3.js. Use when creating charts, graphs, maps, force layouts, or hierarchical diagrams that require fine-grained control beyond what charting libraries provide. Trigger words: d3, data visualization, chart, svg, scales, force graph, treemap, choropleth.

日本語の概要は準備中です。原文の説明を表示しています。

Generate waveform visualizations from audio files. Use when a user asks to create waveform images, build audio player visualizations, generate waveform data for web players, create podcast episode previews, build audio thumbnails, render waveform PNGs for social media, extract peak data as JSON, or integrate waveform generation into audio processing pipelines. Covers audiowaveform CLI, JSON/binary data output, and web player integration.

日本語の概要は準備中です。原文の説明を表示しています。

Use when turning any content into clear, professional visualizations - board slides, reports, proposals, research summaries, training materials, technical diagrams, infographics, process flows, timelines, benchmarks, waterfall charts, or data-backed visual specs for any audience.

日本語の概要は準備中です。原文の説明を表示しています。

Grammar of graphics, chart type selection, color theory, interactive visualization, dashboards, and the principles of honest, effective data display. Covers Tufte's data-ink ratio, Bertin's visual variables, perceptual principles, accessibility, small multiples, annotation, and the full workflow from exploratory plots to publication-quality graphics. Use when creating charts, designing dashboards, critiquing visualizations, or choosing how to display data.

日本語の概要は準備中です。原文の説明を表示しています。

Install and configure the putior R package for workflow visualization. Covers CRAN and GitHub installation, optional dependencies (mcptools, ellmer, shiny, shinyAce, logger, plumber2), and verification of the complete annotation-to-diagram pipeline. Use when setting up putior for the first time, preparing a machine for workflow visualization tasks, when a downstream skill requires putior to be installed, or restoring an environment after an R version upgrade or renv wipe.

日本語の概要は準備中です。原文の説明を表示しています。

Create interactive maps, elevation profiles, and spatial visualizations from GPX tracks, waypoints, or route data using R (sf, leaflet, tmap) or Observable (D3, deck.gl). Covers data import, coordinate system handling, map styling, and export to HTML or image formats. Use when visualizing a planned or completed tour route on an interactive map, creating elevation profiles for hiking or cycling routes, overlaying waypoints and POIs on a basemap, or building a web-based trip dashboard.

日本語の概要は準備中です。原文の説明を表示しています。

Create R-based pictogram glyphs for skill, agent, or team icons in the visualization layer. Covers concept sketching, ggplot2 layer composition using the primitives library, color strategy, registration in the appropriate glyph mapping file and manifest, rendering via the build pipeline, and visual verification of the neon-glow output. Use when a new entity has been added and needs a visual icon for the force-graph visualization, an existing glyph needs replacement, or when batch-creating glyphs for a new domain.

日本語の概要は準備中です。原文の説明を表示しています。

Chọn đúng biểu đồ, kể chuyện với số liệu, và tránh误导 — dựa trên nguyên tắc từ Kieran Healy (Data Visualization, Princeton 2019) và taxonomy từ AntV chart-visualization-skills. Dùng khi cần quyết định loại chart, trình bày insight cho stakeholder, hoặc kiểm tra xem figure có gây hiểu lầm không. Để vẽ Python thực tế, chuyển sang matplotlib / seaborn / scientific-visualization.

日本語の概要は準備中です。原文の説明を表示しています。

Create, standardize, or update step-by-step algorithm visualizations for a given problem ID. Use when the user mentions 'visual', 'visualization', 'animate', or 'step-by-step' alongside a problem ID in /problem/:id format.

日本語の概要は準備中です。原文の説明を表示しています。

Publication-quality statistical visualization with mandatory best practices. Use when creating plots, charts, figures, or any data visualization. Enforces accessibility, uncertainty display, proper labeling, and statistical accuracy.

日本語の概要は準備中です。原文の説明を表示しています。

Expert in visualizing and explaining braid theory, knot mathematics, and topological concepts for educational purposes. Use for creating interactive visualizations, explainer cards, step-wise animations, and translating abstract algebra into intuitive understanding. Activate on keywords: braid theory, knot visualization, σ notation, crossing diagrams, Yang-Baxter, topological education. NOT for general math tutoring, pure knot invariant computation, or non-educational knot theory research.

日本語の概要は準備中です。原文の説明を表示しています。

Expert in turning data visualizations into compelling video and animation content for social media and marketing. Activate on: data commercial, animated chart, data storytelling video, chart animation, Remotion data video, Motion Canvas, Flourish animation, D3 animation, data viz social media, dashboard recording, data narrative video. NOT for: static data visualization (use data-viz-2025), general video editing (use video-processing-editing), full video production pipeline (use ai-video-production-master).

日本語の概要は準備中です。原文の説明を表示しています。