plotly
An open-source interactive data visualization library for Python
Decision gist · record as of 2026-08-14
Yes. Plotly is a mature, well-maintained library (active development, 18738 GitHub stars, top 1000 PyPI packages) with permissive MIT licensing, low install friction, and no known vulnerabilities. It solves a clear problem—interactive visualization in Python—and is the standard choice for this use case. Install it unless you specifically need static-only plots or have strong performance constraints on very large datasets.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Installation is straightforward with low friction—a pure Python wheel with only two lightweight runtime dependencies (narwhals and packaging).
- The project is actively maintained with a recent release 36 days ago and strong community presence (18738 GitHub stars).
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use, modification, and distribution with minimal restrictions—a permissive choice that makes this safe for most projects without legal friction.
last release 2026-07-09 (36 days) · last repo commit 2026-08-07 · 18,738 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 74,220,387 downloads/mo, #452 on PyPI
Alternatives
Verify before relying
pip install plotly
import plotly.express as px
fig = px.bar(x=["a", "b", "c"], y=[1, 3, 2])
fig.show()- Whether static image export (PNG, SVG) requires additional system dependencies beyond the optional kaleido package
- Performance characteristics when rendering very large datasets or complex 3D visualizations
- Whether the narwhals dependency adds meaningful overhead or is used only in specific code paths
What it is and what it does
Plotly is a declarative charting library built on plotly.js that brings interactive, browser-based visualization to Python. It ships with over 30 chart types—including scientific, 3D, statistical, financial, and map-based charts—and renders output as HTML that works in Jupyter notebooks, standalone files, or integrated into Dash web applications. The library abstracts away JavaScript complexity, letting you build interactive plots with simple Python function calls.
The package has minimal runtime dependencies (only narwhals and packaging) and installs cleanly as a pure Python wheel. It supports Python 3.8 through 3.13 and is actively maintained. Optional features like static image export (PNG, SVG) require the separate kaleido package, and geographic visualizations can be extended with the plotly-geo package, but the core library works out of the box for most charting tasks.
Use it for
- Build interactive dashboards in Jupyter notebooks where users can hover, zoom, and pan through data without leaving the notebook
- Export standalone HTML files of plots for sharing with stakeholders or embedding in reports without requiring Python
- Create 3D scientific visualizations (scatter plots, surface plots, mesh plots) for research or technical documentation
- Integrate interactive charts into Dash web applications for production data exploration interfaces
- Generate financial charts (candlestick, OHLC) with interactive time-series controls for market analysis
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Plotly is a mature, well-maintained library (active development, 18738 GitHub stars, top 1000 PyPI packages) with permissive MIT licensing, low install friction, and no known vulnerabilities. It solves a clear problem—interactive visualization in Python—and is the standard choice for this use case. Install it unless you specifically need static-only plots or have strong performance constraints on very large datasets.
Install
plotly on PyPI
Before you install
Installation is straightforward with low friction—a pure Python wheel with only two lightweight runtime dependencies (narwhals and packaging). The project is actively maintained with a recent release 36 days ago and strong community presence (18738 GitHub stars).
License in practice
MIT license permits commercial and private use, modification, and distribution with minimal restrictions—a permissive choice that makes this safe for most projects without legal friction.
Quickstart
pip install plotly
import plotly.express as px
fig = px.bar(x=["a", "b", "c"], y=[1, 3, 2])
fig.show()Verify before relying
- Whether static image export (PNG, SVG) requires additional system dependencies beyond the optional kaleido package
- Performance characteristics when rendering very large datasets or complex 3D visualizations
- Whether the narwhals dependency adds meaningful overhead or is used only in specific code paths
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesnarwhalspackaging |
| Maintenance | Actively maintained 36 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 74,220,387 / month, #452 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Scientific/Engineering :: Visualization |
Evidence: plotly-6.9.0-py3-none-any.whl
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See also chart-studio · kaleido · plotly-express · plotly-resampler · sphinx-plotly-directive · ridgeplot · reflex-components-plotly · pyecharts · dash