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

Converts CSV, Excel, or JSON data into a polished, interactive visual report page with KPI cards, charts, data tables, and insights.

Creates interactive, publication-quality charts with 40+ types, hover tooltips, zoom, and web-embeddable exports for dashboards and exploratory analysis.

Run standard single-cell RNA-seq analysis pipelines: QC, normalization, dimensionality reduction, clustering, differential expression, and visualization using Scanpy.

30.2k · bundle

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

orchestra-research

Experiment Tracking Swanlab

Track ML experiments with open-source run logging, local or self-hosted dashboards, and media visualization using SwanLab.

10.4k · bundle

nimoqup046-collab

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

lucaspmarie-a11y

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

Analyzes uploaded data files with full Python access, producing cleaned datasets, statistical reports, charts, and dashboards via the CellCog coding agent.

Create, analyze, and visualize complex networks and graphs in Python using NetworkX, including graph construction, algorithms, generators, I/O, and plotting.

Performs geospatial vector data analysis with GeoPandas, including reading/writing shapefiles, GeoJSON, GeoPackage, and PostGIS, geometric operations, spatial joins, overlays, coordinate transformations, and map visualization.

leandrobenjaminl

Guides data analysis, EDA, and ML tasks by teaching, diagnosing MCPs, and deciding with the user, offering multiple options and documenting decisions.

Power Bi Report Design Consultation

Guides the design of effective, user-friendly, and accessible Power BI reports with optimal chart selection and layout design.

Performs differential expression analysis on label-free quantitative (LFQ) proteomics data from MaxQuant and DIA-NN outputs, including preprocessing, imputation, statistical testing, and visualization.

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.

schattenspiegel

Build, verify, and debug interactive Python visualizations with Plotly, including Plotly Express, graph_objects, subplots, facets, hover/customdata, axes, legends, FigureWidget events, and HTML/image export.

Cja Executive Briefing

Generates a polished, leadership-ready performance briefing with KPI tiles, executive narrative bullets, and a driver analysis — all as a print-ready HTML document.

Create, analyze, and visualize complex networks and graphs in Python with NetworkX, including graph algorithms, community detection, synthetic network generation, and multiple I/O formats.

30.2k · bundle

Process and analyze high-throughput sequencing data with deepTools for quality control, normalization, comparison, and publication-quality visualizations of ChIP-seq, RNA-seq, and ATAC-seq experiments.

30.2k · bundle

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