Plotly’s Python browser-based graphing library makes interactive, publication-quality graphs and scientific visualizations online.
Built on top of plotly.js, plotly.py is a high-level, declarative charting library. plotly.js ships with over 30 chart types, including scientific charts, 3D graphs, statistical charts, SVG maps, financial charts, and more.
Plotly graphs can be viewed in Jupyter notebooks, standalone HTML files, or hosted online on plot.ly.
Key Features
- Works in online or offline mode, as well as Jupyter notebooks.
- Create dashboards using the online creator or programmatically with Plotly’s python API. Dashboards can contain plots, text and webpage images. Dashboards can be public, private or secret independent of the plots inside them.
- Embed plotly graphs with an iframe in HTML. This includes IPython notebooks, WordPress sites, dashboards, blogs, and more.
- Upload data to Plotly from Python with the Plotly Grid API.
- Convert supported matplotlib figures.
- Built-in animation capability which is easy to use.
- 3D plotting capability.
- Not only a Python library. It’s also an R library, it’s a Julia library etc.
- Geographical visualization.
- Multi-language support.
Plotly is an online collaborative data analysis and graphing tool. The Python API allows you to access all of Plotly’s functionality from Python. Plotly figures are shared, tracked, and edited all online and the data is always accessible from the graph. Plotly provides a web-service for hosting graphs.
Website: plot.ly/python
Support: Documentation, GitHub Code Repository
Developer: Plotly, Inc
License: MIT License

Plotly is written in Python. Learn Python with our recommended free books and free tutorials.
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|---|---|
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| Bokeh | Elegant, concise construction of versatile graphics |
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| Vega-Altair | Declarative Visualization in Python |
| plotnine | Grammar of graphics for Python |
| PyQtGraph | Python graphics and GUI library built on PyQt4 / PySide and numpy |
| bqplot | Interactive Plotting Framework for the Jupyter Notebook |
| Vaex | Fast visualization of big data |
| PyVista | 3D plotting and mesh analysis |
| folium | Visualize data in a Leaflet map |
| HoloViews | Make Data Analysis and Visualization Seamless |
| Datashader | Generates aggregate arrays and representations of them as images |
| yt | Multi-code Toolkit for Analyzing and Visualizing Volumetric Data |
| Glumpy | Intuitive interface between NumPy and modern OpenGL |
| GeoViews | Explore and visualize geographical, meteorological, and oceanographic datasets |
| Pygal | Dynamic SVG charting library |
| Glue | Multi-dimensional linked-data exploration |
Read our verdict in the software roundup.
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