name: plotly description: >- Plotly interactive visualization. Express and Graph Objects: scatter, line, bar, heatmap, 3D, geographic charts; subplots; styling; export. Use when interactivity (hover/zoom) is needed. For static figures use plotnine; for GIS use geopandas. metadata: audience: research-coders domain: python-library library-version: "6.x" skill-last-updated: "2026-03-28"

Plotly Skill

Plotly interactive visualization library for Python. Covers Plotly Express and Graph Objects for scatter, line, bar, histogram, box, heatmap, 3D, and geographic charts; subplots and faceting; styling; and HTML/image export. Use when creating interactive visualizations with hover/zoom/pan, building web-based charts, or producing geographic or 3D plots. Prefer over plotnine when interactivity is required; for spatial analysis, projections, or GIS-style mapping, use geopandas.

Quick reference for creating interactive data visualizations with Plotly, featuring both the high-level Plotly Express API and low-level Graph Objects.

What is Plotly?

Plotly is an interactive visualization library for Python:

• Interactive: Hover, zoom, pan, and select built-in
• Two APIs: Plotly Express (simple) and Graph Objects (flexible)
• Web-based: Renders as HTML/JavaScript, works in notebooks and browsers
• Wide chart support: 40+ chart types including statistical, scientific, financial, and geographic

How to Use This Skill

Reference File Structure

Quick Decision Trees

"I need to create a chart"

What kind of chart?
├─ Scatter plot → ./references/charts.md
├─ Line chart → ./references/charts.md
├─ Bar chart → ./references/charts.md
├─ Histogram → ./references/charts.md
├─ Box/Violin plot → ./references/charts.md
├─ Heatmap → ./references/charts.md
├─ 3D/Maps/Financial → ./references/charts.md (Other Chart Types)
└─ Not sure → ./references/quickstart.md

"I need multiple charts"

Multiple panels?
├─ Same chart, split by category → ./references/subplots-facets.md (faceting)
├─ Different charts in grid → ./references/subplots-facets.md (make_subplots)
├─ Shared axes → ./references/subplots-facets.md
└─ Secondary y-axis → ./references/subplots-facets.md

"I need to customize appearance"

What to customize?
├─ Overall theme → ./references/styling.md (templates)
├─ Colors → ./references/styling.md
├─ Titles/labels → ./references/styling.md
├─ Axes → ./references/styling.md
├─ Legend → ./references/styling.md
└─ Hover info → ./references/styling.md

"I need to save/export"

Export format?
├─ Interactive HTML → ./references/export.md
├─ Static image (PNG/SVG/PDF) → ./references/export.md
├─ JSON for API → ./references/export.md
└─ Embed in webpage → ./references/export.md

"Something isn't working"

Common issues?
├─ Figure not showing → ./references/gotchas.md
├─ Image export fails → ./references/gotchas.md
├─ Performance issues → ./references/gotchas.md
├─ px vs go confusion → ./references/gotchas.md
└─ Column/data errors → ./references/gotchas.md

File-First Execution in Research Workflows

Important: In data research pipelines (see CLAUDE.md), all visualizations are generated through script files in scripts/stage8_analysis/, not interactively. This ensures auditability and reproducibility.

The pattern:

1. Write plot code FIRST to scripts/stage8_analysis/{step}_{plot-name}.py
2. Execute via Bash with automatic output capture wrapper script
3. Validation results get automatically embedded in scripts as comments
4. If failed, create versioned copy for fixes

Closely read agent_reference/SCRIPT_EXECUTION_REFERENCE.md for the mandatory file-first execution protocol covering complete code file writing, output capture, and file versioning rules.

See:

• agent_reference/WORKFLOW_PHASE4_ANALYSIS.md — Stage 8 (Analysis & Visualization)

The examples below show Plotly syntax. In research workflows, wrap them in scripts following the file-first pattern.

Quick Reference

Essential Imports

import plotly.express as px          # High-level API
import plotly.graph_objects as go    # Low-level API
from plotly.subplots import make_subplots  # For subplots
import plotly.io as pio              # For export/config

Plotly Express Pattern

import plotly.express as px

fig = px.scatter(df, x="col_x", y="col_y", color="category")
fig.show()

Graph Objects Pattern

import plotly.graph_objects as go

fig = go.Figure()
fig.add_trace(go.Scatter(x=x_data, y=y_data, mode="markers"))
fig.update_layout(title="My Plot")
fig.show()

Common px Functions

Common go Trace Types

Saving Plots

# Interactive HTML
fig.write_html("plot.html")

# Static image export (PNG/SVG/PDF) is NOT available in DAAF — kaleido is not
# installed due to its heavy Chromium dependency. Use plotnine for static figures.
# For interactive output, use HTML:
# fig.write_image("plot.png")  # Would require: pip install kaleido + Chromium

Topic Index

Citation

When this library is used as a primary analytical tool, include in the report's Software & Tools references:

Plotly Technologies Inc. Plotly: Interactive graphing library [Computer software]. https://plotly.com/

Cite when: Plotly is the primary visualization library producing interactive figures included in the report or notebook. Do not cite when: Only used for quick exploratory plots not included in deliverables.