![]() See the announcement at for more background. In March, we released a tech preview of Plotly Express: a wrapper for plotly.py that provides a simple syntax for creating complex charts. Because this distinction is now much clearer, we are retiring the “online”/“offline” terminology. The only way to interact with Chart Studio services is to install the chart-studio distribution package and call functions from the top-level chart_studio module. They contain no logic for interacting with external Chart Studio services. Using our legacy terminology, both the plotly distribution package and the top-level plotly module are “offline” only. See the version 4 migration guide for guidance on porting “online” code to use the new chart-studio package. Instead, it is included in a new optional chart-studio distribution package. Second, this chart_studio module is no longer included in the plotly distribution package. ) to a new top-level chart_studio module (e.g. This duality has been a common source of confusion for several years, and so in version 4 we are making some important changes to help clear this up.įirst, all functionality for interacting with Chart Studio has been moved from the top-level plotly module (e.g. In “online” mode, figures were uploaded to the Chart Studio cloud (or on-premise) service, whereas in “offline” mode figures were rendered locally. ![]() Prior versions of plotly.py contained functionality for creating figures in both “online” and “offline” modes. “offline” only ( chart-studio package split) jupyterlab-plotly extension and JupyterLab 1.0 support.Reduced package size ( plotly-geo package split).New renderers framework (or plotly.py everywhere).“offline” only ( chart-studio package split).Here are some of the highlights that will be discussed in more detail below: For installation instructions, see the Getting Started page. This is a major release that includes many features and changes that we’re really excited about. I’m happy to announce the availability of the first release candidate of plotly.py version 4. See the official announcement post at plotly.py 4.0.0rc1 Update: Version 4.0.0 final has been released. We also encourage you to join the Plotly Community Forum if you want help with anything related to plotly.Update: version 4.9 has been released since this was posted. Once you've installed, you can use our documentation in three main ways: Note: This package is optional, and if it is not installed it is not possible for figures to be uploaded to the Chart Studio cloud service. Plotly may be installed using pip:$ pip install plotly=5.14.1 We also encourage you to join the Plotly Community Forum if you want help with anything related to plotly. You can check out our exhaustive reference guides: the Python API reference or the Figure Referenceįor information on using Python to build web applications containing plotly figures, see the Dash User Guide.If you prefer to learn about the fundamentals of the library first, you can read about the structure of figures, how to create and update figures, how to display figures, how to theme figures with templates, how to export figures to various formats and about Plotly Express, the high-level API for doing all of the above.You jump right in to examples of how to make basic charts, statistical charts, scientific charts, financial charts, maps, and 3-dimensional charts.This Getting Started guide explains how to install plotly and related optional pages. exporting notebooks to PDF with high-quality vector images). QtConsole, Spyder, P圜harm) and static document publishing (e.g. Thanks to deep integration with our Kaleido image export utility, plotly also provides great support for non-web contexts including desktop editors (e.g. The plotly Python library is sometimes referred to as "plotly.py" to differentiate it from the JavaScript library. The plotly Python library is an interactive, open-source plotting library that supports over 40 unique chart types covering a wide range of statistical, financial, geographic, scientific, and 3-dimensional use-cases.īuilt on top of the Plotly JavaScript library ( plotly.js), plotly enables Python users to create beautiful interactive web-based visualizations that can be displayed in Jupyter notebooks, saved to standalone HTML files, or served as part of pure Python-built web applications using Dash.
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