Visualization

Build dense analytics dashboards with candlestick, depth, heatmap and gauge charts

Profile scientific data, pick the right figure type and build journal-ready plots

Build charts, dashboards and Chart.js data reports from CSV or Excel files

Choose and generate the right business chart for your current dataset

Plan a business data dashboard with the right metrics and layout

Turn research data into dark-mode inline SVG charts for blog posts

Apply publication figure rules for font sizes, tick marks, legends and 300 dpi output

Add line, bar, area, pie or scatter charts to a PortalJS dataset showcase

Show a GeoJSON dataset on an interactive Leaflet map in a PortalJS showcase

Build dashboards, metric trees and self-serve analytics people actually use

Standardize chart fonts, colors, legends and captions for paper and release figures

Generate Circos configs for circular genomics plots of variants and networks

Style flow cytometry gating plots in a consistent publication look

Restyle meta-analysis forest plots as review-ready publication figures

Interpret scientific graphs and charts and write clear figure captions

Beautify gene expression heatmaps with clustering trees and annotation tracks

Plot sample clustering dendrograms to check QC, batches and sample similarity

Build fine-grained, publication-ready charts in Python with matplotlib

Draw Baujat plots to find the studies driving meta-analysis heterogeneity

Draw forest plots for binary event data from study counts in a CSV

Draw forest plots for continuous outcomes from means, SDs and sample sizes

Draw survival meta-analysis forest plots from hazard ratios in a CSV

Draw funnel plots and run Egger and Begg tests for publication bias

Draw radial (Galbraith) plots to check heterogeneity across meta-analysis studies

Interpret meta-analysis forest plots and write statistical figure legends

Draw ROB2 risk-of-bias traffic light and summary bar plots for trials

Draw leave-one-out sensitivity forest plots for meta-analysis results

Build interactive Krona charts of metagenomic taxonomic profiles

Style phylogenetic trees into review-ready figures with clear labels and colors

Build interactive Plotly charts with hover, zoom and embeddable web output

Draw Sankey or alluvial plots of sample groups across stages like risk or subtype

Make statistical plots like box, violin, pair plots and heatmaps with seaborn

Build survival curves with number-at-risk tables for review-ready figures

Reduce abundance or OTU matrices with UMAP or t-SNE to check group separation

Replace Venn diagrams of more than four sets with clearer UpSet plots

Write detailed text descriptions of medical images and charts for readers

Label volcano plots of differential expression results with key genes

Generate R or Python code for volcano plots of differential expression results

Profile data and build journal-ready figures with checks for common chart mistakes

Build standalone D3.js charts as HTML or SVG from local data files

Plot desired vs actual quadrotor trajectories and tracking errors in matplotlib

Design KPI dashboards with metric selection, layouts and real-time monitoring

Build interactive data science charts as HTML from real tables and model results

Generate, debug and restyle VChart charts from specs, screenshots or React code

Install, compose and animate Bklit UI charts in React and Next.js apps

Turn plain-language chart style requests into exact Bklit UI components

Migrate Recharts charts to Bklit UI after inventorying each chart

Turn eval study numbers into on-brand charts and check them with Playwright

Guidance for choosing and building charts from data for an agent