Results for “ma-plot”

76 skills

Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly;...

brycewang-stanford

Econometrics skill for generating publication-quality figures for top economics journals. Activates when the user asks about: "econometric figure", "publication figure", "journal figure", "AER figure", "QJE figure", "event study plot", "coefficient plot", "coefplot", "binned scatter", "binscatter", "RDD plot", "parallel trends plot", "kernel density", "distribution plot", "time series plot", "map", "figure formatting", "academic plot", "论文图表", "学术图", "系数图", "事件研究图", "散点图", "分布图", "趋势图", "回归可视化"

Alterlab Seaborn

Builds statistical plots with the seaborn Python library and pandas DataFrame integration, on attractive matplotlib-based defaults. Use for quick exploration of distributions, relationships, and categorical comparisons — box plots, violin plots, swarm/strip plots, KDE/histograms, pair plots, joint plots, regression plots, correlation heatmaps, and faceted small multiples (relplot/displot/catplot/lmplot). For interactive/hover/zoom charts defer to alterlab-plotly; for exact journal/manuscript styling (column widths, point fonts, CMYK, vector export) defer to alterlab-scientific-viz; for low-level custom matplotlib figures defer to alterlab-matplotlib (seaborn integrates with it for fine-tuning). Part of the AlterLab Academic Skills suite.

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).

Automates genome-wide association studies from genotype files to publication-ready results, running PLINK2 QC and REGENIE regression with Manhattan and QQ plots.

metinduraktr-44

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).

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Biblioteca interativa de visualização de dados científicos e estatísticos para Python. Use ao criar gráficos, plots ou visualizações incluindo scatter plots, gráficos de linhas, gráficos de barras, heatmaps, plots 3D, mapas geográficos, distribuições estatísticas, gráficos financeiros e dashboards. Suporta visualizações rápidas (Plotly Express) e personalização refinada (graph objects). Gera HTML interativo ou imagens estáticas (PNG, PDF, SVG).

Manage novel data — chapters, characters, plots — from the terminal fast. Use when outlining chapters, tracking characters, organizing plot timelines.

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).

intelli-verse-x

Ivx Plot Structure

This skill should be used when the user asks to "create a plot arc", "story structure", "add a plot point", "story timeline", "track foreshadowing", "pacing", "act structure", "story arc", "plot outline", or wants to plan and manage the narrative structure of a story.

Matlab Build Chart

Create and customize MATLAB charts and plots. Plot types (line, scatter, bar, histogram, heatmap, surface), axes configuration, annotations, data tips, interactive plots, animation, multiple axes with tiledlayout, colororder, and performance optimization. Works for standalone figures, Live Scripts, and uifigure apps. Use when plotting data, customizing axes, adding annotations or interactivity, animating charts, or arranging multiple axes. Triggers: plot, chart, graph, axes, uiaxes, annotation, data tips, animation, tiledlayout, colororder, heatmap, scatter, figure, visualization, export.

Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.

metinduraktr-44

Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.

Create publication-quality statistical graphics in Python with dataset-oriented plotting, semantic mapping, and automatic statistical estimation.

Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.

Foundational plotting library. Create line plots, scatter, bar, histograms, heatmaps, 3D, subplots, export PNG/PDF/SVG, for scientific visualization and publication figures.

Create static, animated, and interactive plots using Python's foundational visualization library, with guidance on both pyplot and object-oriented APIs.

Create publication-quality static, animated, and interactive plots with fine-grained control over every element using Matplotlib's pyplot and object-oriented APIs.

30.2k · bundle

Create publication-quality statistical graphics directly from tabular datasets, covering relational, distribution, categorical, regression, and matrix plots with minimal code.

Performs differential expression analysis on bulk RNA-seq or pseudo-bulk count matrices with QC, PCA, and contrast testing.

Create publication-quality statistical graphics in Python with seaborn, covering relational, distribution, and categorical plots with pandas integration.

Create publication-quality statistical graphics with dataset-oriented plotting, multivariate analysis, and automatic statistical estimation using minimal code.

30.2k · bundle

Tao Train Mask Auto Encoder

Train, evaluate, export, and run inference for Masked Auto-Encoder (MAE) models for self-supervised pretraining and fine-tuning of visual representations.

nimoqup046-collab

Create publication-quality statistical graphics in Python with dataset-oriented plotting, multivariate analysis, automatic statistical estimation, and multi-panel figures.

Data Visualization

Create clear, effective charts and dashboards from structured data using matplotlib, seaborn, and plotly. Use when the user requests data visualization or provides relevant inputs for this workflow.

Scientific Visualization

Create publication-ready scientific figures with multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and journal-specific formatting using matplotlib, seaborn, and plotly.

30.2k · bundle

UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.

Perform nonlinear dimensionality reduction, 2D/3D embeddings, clustering preprocessing, supervised or semi-supervised UMAP, DensMAP, AlignedUMAP, and Parametric UMAP workflows using the umap-learn library.

30.2k · bundle

Create publication-quality static, animated, and interactive plots with fine-grained control over every element, from basic charts to multi-panel figures, with export to PNG, PDF, and SVG.

Academic Plotting

Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.

orchestra-research

Academic Plotting

Generates publication-quality figures for ML papers, including architecture diagrams via Gemini and data-driven charts via matplotlib/seaborn.

10.4k · bundle

leandrobenjaminl

Data Visualization

Crea gráficos profesionales con Matplotlib, Seaborn y Plotly, desde exploración rápida hasta visualizaciones publicables, eligiendo el tipo de gráfico adecuado para cada historia de datos.

Tao Train Mask Auto Label

Trains, evaluates, and runs inference for Mask Auto-Label (MAL) weakly-supervised segmentation models using ViT-MAE backbones with minimal point or box annotations.

Nemo Mbridge Resiliency

Configure fault tolerance, straggler detection, preemption, in-process restart, and re-run state machine for Megatron Bridge training jobs.

Matlab Model Ams Systems

Model a Phase-Locked Loop (PLL) IC from its datasheet or system specs using Mixed-Signal Blockset. Without this skill, agents universally select the wrong solver and produce non-functional PLL models — 100% of unguided attempts fail. Covers Integer-N, Fractional-N, Dual Modulus architectures, loop filter design, lock time optimization, VCO phase noise configuration, and msbPllArchitectures/msbPllFoundation block assembly. Use when: PLL modeling, frequency synthesizer design, phase noise simulation, lock time analysis, charge pump design, loop filter tuning, datasheet-to-model, Mixed-Signal Blockset PLL, msbPllArchitectures.

在MATLAB绘制的直方图上叠加标记局部峰值，不显示文本标签，并支持自定义标记样式（如蓝色实心倒三角）。