plotly.py vs visx
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
A Python library for making interactive, browser-based charts and graphs.
Open source · MIT
A set of reusable React building blocks for drawing custom charts, built on d3 math.
The short answer
Choose plotly.py if you need…
- Python users who want hoverable, zoomable charts without writing JavaScript
- Data analysts working in Jupyter notebooks
- People building shareable HTML charts for reports
- Developers embedding charts in Dash dashboards
Choose visx if you need…
- React developers who want full control over how a chart looks and behaves
- Teams building their own reusable chart library on top of shared components
- Developers who already know d3 and want its math without its DOM update style
- Projects that want to keep bundle size small by importing only needed packages
Side-by-side
| plotly.py | visx | |
|---|---|---|
| Type | Library | Library |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 18.9k | 21.1k |
| Setup difficulty | Beginner | Intermediate |
| How you get it | Install with a package manager | Install with a package manager |
| Main language | Python | TypeScript |
| Last code update | 5 days ago | 5 months ago |
What each one is
plotly.py
plotly.py is a Python library for creating interactive charts that open in a web browser. It is built on top of plotly.js and lets you describe a chart in code, then view it in Jupyter notebooks, as standalone HTML files, or inside Dash applications. The README says plotly.js provides over 30 chart types, including 3D, statistical, map and financial charts.
visx
visx is a collection of low-level visualization components for React. It uses d3 for the calculations and math, while React handles updating the page, so developers can build charts without writing d3 selection code by hand. You install only the small packages you need, such as shapes or scales, and combine them into your own charts.
Best for
plotly.py
- Python users who want hoverable, zoomable charts without writing JavaScript
- Data analysts working in Jupyter notebooks
- People building shareable HTML charts for reports
- Developers embedding charts in Dash dashboards
visx
- React developers who want full control over how a chart looks and behaves
- Teams building their own reusable chart library on top of shared components
- Developers who already know d3 and want its math without its DOM update style
- Projects that want to keep bundle size small by importing only needed packages
Strengths
plotly.py
- Charts are interactive by default, so users can hover, zoom and inspect data
- Two APIs: a short high-level one (Plotly Express) and a detailed one (Graph Objects)
- Licensed under MIT with a large community and active maintenance
visx
- Components are low-level and unopinionated, so you control the final look
- Lets you use d3 math without managing d3 selections or enter/exit/update logic
- Modular packages mean you only include what you use
Not ideal for
plotly.py
- People who only need static images for print; the README points to a separate Kaleido package and a Chrome install for that, which adds setup
- Users who need a non-Python language; this project is Python-specific
- Projects needing a built-in dashboard server on its own, since the README links Dash as a separate product
visx
- People who want ready-made charts with no coding, since visx provides building blocks rather than finished charts
- Projects that need built-in animation, because the README says visx deliberately does not include animation and suggests using existing React animation libraries instead
- Projects not using React, since the components are built for React 18 or 19
Trade-offs
plotly.py
- Static image export needs an extra package and a Chrome or Chromium install
- Interactive charts depend on a browser, so they are less suited to fully offline or print-only workflows
- The README is truncated here, so detailed API coverage and version-specific changes were not verified
visx
- Because it is low-level, you write more code than with a turnkey charting library
- No built-in animation; you must add a React animation library yourself if you want it
- Requires React 18 or 19 for the current v4 release, so older React projects need migration (see the migration guide)
Getting started
plotly.py
Install plotly with pip
pip install plotlyInstall with Plotly Express support
pip install plotly[express]visx
Install the packages used in the README example
npm install --save @visx/mock-data @visx/group @visx/shape @visx/scaleFrequently asked questions
What is the difference between plotly.py and visx?
plotly.py: A Python library for making interactive, browser-based charts and graphs. visx: A set of reusable React building blocks for drawing custom charts, built on d3 math. plotly.py suits python users who want hoverable, zoomable charts without writing javascript, while visx suits react developers who want full control over how a chart looks and behaves.
Are plotly.py and visx free?
plotly.py: Free and open source. visx: Free and open source.
Which is easier to set up, plotly.py or visx?
plotly.py is easier to get started with (rated beginner); visx is rated intermediate and usually needs more setup.
Is plotly.py or visx more popular?
visx has more GitHub stars (21.1k) than plotly.py (18.9k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to plotly.py and visx?
Other options people compare them with include Plotly.js, deck.gl, G2, Recharts, nivo.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.