804건 · 관련도순
METAINFORMANT rules for directory src/metainformant/metabolomics/visualization. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
METAINFORMANT rules for directory src/metainformant/gwas/visualization. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
METAINFORMANT rules for directory src/metainformant/ecology/visualization. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
METAINFORMANT rules for directory src/metainformant/epigenome/visualization. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
METAINFORMANT rules for directory src/metainformant/gwas/visualization/genomic. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
METAINFORMANT rules for directory src/metainformant/gwas/visualization/population. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
METAINFORMANT rules for directory src/metainformant/gwas/visualization/statistical. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
METAINFORMANT rules for directory src/metainformant/gwas/visualization/interactive. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
METAINFORMANT rules for directory scripts/gwas/visualization. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
METAINFORMANT rules for directory scripts/visualization. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
METAINFORMANT rules for directory docs/visualization. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
METAINFORMANT rules for directory examples/visualization. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implements data visualization charts in Flutter using the fl_chart package (v1.2.0). Supports LineChart, BarChart, PieChart, ScatterChart, RadarChart, and CandlestickChart with implicit animations, touch interactivity, and pan/zoom transformations. Use when building any Flutter chart, graph, or data visualization — including line graphs for trends, bar charts for comparisons, pie/donut charts for proportions, scatter plots for distributions, radar charts for multi-axis comparisons, or candlestick charts for financial OHLC data. Also use when customizing chart axes, titles, tooltips, grid lines, touch callbacks, chart animations, or chart zoom/pan behavior.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implement, review, or improve data visualizations using Swift Charts. Use when building bar, line, area, point, pie, or donut charts; when adding chart selection, scrolling, or annotations; when plotting functions with vectorized BarPlot, LinePlot, AreaPlot, or PointPlot; when customizing axes, scales, legends, or foregroundStyle grouping; or when creating specialized visualizations like heat maps, Gantt charts, stacked/grouped bars, sparklines, or threshold lines.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build genome-browser-style multi-track figures with pyGenomeTracks (config-driven), Gviz (R), and IGV batch screenshotting. Covers BigWig coverage tracks, BED/peak overlays, gene-model rendering, Hi-C matrix tracks, BedPE link arcs, spike-in-aware normalization, and the bamCoverage --normalizeUsing trap. Use when producing publication figures of genomic loci with stacked aligned tracks (coverage, peaks, genes, interactions) for ChIP-seq, ATAC-seq, RNA-seq, Hi-C, or generic locus visualization.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build circular genome visualizations using circlize (R), pyCirclize (Python), or Circos (Perl CLI) with ideogram tracks, multi-data tracks (scatter, histogram, heatmap), chord/link arcs for interactions, and explicit circos.clear() between plots. Covers when circular is appropriate vs when Cartesian wins (Cleveland-McGill 1984), karyograms, and chromosome adjacency in chord diagrams. Use when adjacency on the circle conveys meaning — chromosome-level overview, structural variants, Hi-C interactions, cross-genome comparisons.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard - Google's ML visualization toolkit
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Publication-quality physics plots — vector fields, streamlines, contour maps, 3D surfaces, phase space, spectrograms, and animations. Optimized for journal submission with LaTeX labels, proper colormaps, and multi-panel layouts.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV/HDF5/Arrow/Parquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that do not fit in memory.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Publication-quality molecular visualization. 2D structure drawings (PNG/SVG), molecule grids with property annotations, scaffold highlighting, protein-ligand interaction diagrams, and interactive 3D views.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Visualize biological networks (PPI, gene-regulatory, co-expression, pathway) with layout algorithm choice (ForceAtlas2, Fruchterman-Reingold, Kamada-Kawai, hive plots), edge bundling, community-based coloring, and reproducible seeds using NetworkX, PyVis, igraph, and Cytoscape automation. Use when rendering biological networks for static publication, interactive HTML exploration, or Cytoscape-format export.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build genome-browser-style multi-track figures with pyGenomeTracks (config-driven), Gviz (R), and IGV batch screenshotting. Covers BigWig coverage tracks, BED/peak overlays, gene-model rendering, Hi-C matrix tracks, BedPE link arcs, spike-in-aware normalization, and the bamCoverage --normalizeUsing trap. Use when producing publication figures of genomic loci with stacked aligned tracks (coverage, peaks, genes, interactions) for ChIP-seq, ATAC-seq, RNA-seq, Hi-C, or generic locus visualization.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.