Plugins

4 plugins

Python Data Visualization

For data scientists to create static and interactive plots using Python libraries.

12 skills · plugin

Write B2B Case Study

Write a compelling B2B case study using the STAR framework with research and data visualization.

3 skills · plugin

Analyze Single-Cell RNA-Seq

Analyze single-cell RNA-seq data using Scanpy, including quality control, normalization, clustering, marker gene identification, and visualization.

9 skills · plugin

@brycewang-stanford

Twelve IEEE VIS-specific skills for the IEEE Visualization Conference and its journal-integrated IEEE TVCG publication model, grounded in the IEEE VIS 2026 call, ieeevis.org, IEEE Xplore/TVCG, the Precision Conference System, and dblp.

2 skills · plugin

Results for “visualization”

56 skills

Data Visualization

Design clear, accessible data visualizations with appropriate chart selection and styling.

lucaspmarie-a11y

Creates interactive, publication-quality visualizations in Python with 40+ chart types, including hover, zoom, pan, and web-embeddable output.

Generates spectrograms and multi-panel audio feature visualizations from audio files via a command-line tool.

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

Generates spectrograms and multi-panel audio feature visualizations (mel, chroma, MFCC) from audio files via a Go CLI.

Data Storytelling

Transform raw data into compelling narratives with structured story frameworks, visualization techniques, and presentation templates for executive audiences.

More results

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

Manipulate phylogenetic trees, detect evolutionary events, integrate NCBI taxonomy, and create publication-quality visualizations using the ETE toolkit.

30.2k · bundle

Data Visualization

Create clear, effective data visualizations with chart selection, color theory, and annotation best practices using the inference.sh CLI.

Create, analyze, and visualize complex networks and graphs in Python, covering graph construction, algorithms, generators, I/O, and visualization.

Create data-driven charts with Vega-Lite and Vega, covering bar, line, scatter, heatmap, area, radar, and word cloud visualizations from structured data arrays.

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.

Applied Big Data Design

Performs design operations in the big-data domain, including hypothesis testing, statistical analysis, and data visualization using ML frameworks.

Numerical computing with MATLAB and GNU Octave for matrix operations, data analysis, visualization, and scientific computing, including script execution and syntax guidance.

Automates sequencing quality control by running FastQC and MultiQC, extracting quality metrics, and generating publication-ready visualizations via a CLI or MCP stdio server.

lucaspmarie-a11y

Creates, manipulates, and analyzes complex networks and graphs using the NetworkX Python package, including graph algorithms, synthetic network generation, I/O, and visualization.

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）。

Cleans datasets, detects anomalies, generates reports, and creates visualizations using pandas, scikit-learn, and plotting libraries to turn raw data into client-ready deliverables.

Creates interactive Plotly visualizations in Python, covering Express and Graph Objects for scatter, line, bar, heatmap, 3D, and geographic charts, plus subplots, styling, and HTML export.

Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard.

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

Create publication-quality statistical graphics from tabular datasets with minimal code, supporting multivariate analysis, statistical estimation, and complex multi-panel figures.

Create terminal-based charts and visualizations from CSV, JSON, or piped data using tools like YouPlot, Termgraph, Gnuplot, and more.

schattenspiegel

Build, review, debug, or test declarative statistical visualizations in Python with Altair and Vega-Lite, including chart marks, typed encodings, transforms, parameters, layers, facets, and specification export.

Create interactive, publication-quality visualizations with 40+ chart types, hover, zoom, pan, and web embedding. Choose between Plotly Express and Graph Objects for dashboards, exploratory analysis, and presentations.

Create interactive, publication-quality visualizations with 40+ chart types, including scatter, bar, line, 3D, maps, and financial charts, with support for hover, zoom, pan, subplots, and export to HTML or static images.

nimoqup046-collab

Creates interactive, publication-quality visualizations in Python with 40+ chart types, including scatter, bar, heatmap, 3D, and financial charts, plus subplots, styling, and export to HTML or static images.

leandrobenjaminl

Crea dashboards interactivos con Streamlit: carga de datos, filtros, gráficos y despliegue.

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

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

Creates interactive, publication-quality charts with hover, zoom, and pan, plus static exports and Dash integration.

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

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

30.2k · bundle

nimoqup046-collab

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

Perform numerical computing, matrix operations, data analysis, and scientific visualization using MATLAB or GNU Octave.

30.2k · bundle

Analyze single-cell RNA-seq data with Scanpy, covering quality control, normalization, dimensionality reduction, clustering, marker gene identification, and visualization.