LaTeXĭcc.Graph supports rendering LaTeX on titles, labels, and annotations. Partial bundles are smaller than the full Plotly.js bundles that come with the Graph component and Plotly.py and can therefore improve your app’s loading time. * use a Plotly-distributed Plotly.js partial bundle or a custom-built Plotly.js bundle which only includes the subset of Plotly.js features that your Dash app uses. We strive to make Plotly.js releases completely backwards-compatible, so you shouldn’t have to do this very often. * take advantage of more desirable behavior of a version of Plotly.js that is less recent than the one that is included in the currently installed version of Dash, Plotly.py, or Dash Design Kit. * take advantage of new features in a version of Plotly.js that is more recent than the one that is included in the currently installed version of Dash, Plotly.py, or Dash Design Kit. In all versions of Dash you can also override the Plotly.js version by placing a Plotly.js bundle in the assets directory. See the Plotly.py releases page for more details on which version of Plotly.js was included with each release. If you want to use a different version of Plotly.js in Dash 2.13 or later, you can use a different version of Plotly.py. Each version of Dash prior to 2.13 included its own version of Plotly.js. In Dash 2.13 and later, the dcc.Graph component uses the version of the Plotly.js library in the Plotly.py version you have installed. The dcc.Graph component leverages the Plotly.js library to render The fig object is passed directly into the figure property of dcc.Graph:Ĭontrolling the Plotly.js Version Used by dcc.Graph To see all of these rendering environments, see.If you are using the interface outside of Dash, then calling fig.show() will always display the graph (either in your browser or inline directly in your environment). In development, you can create figures by running Dash apps or in other environments like Jupyter, your console, and more.Plotly supports 40-50 different chart types. If you can’t generate the graph easily with px, then learn the graph_objects structure by reading 1 and understanding the structure of the figure via.Once you understand it, view all of the properties by visiting the “Figure Reference” page at. Read through 1 to understand the low-level figure interface and how to modify the properties of a generated figure. Once you understand its structure, you can see all of the arguments in the “API Reference” page documented here: Įvery aspect of a chart is configurable. Understand where it fits in by reading 1. Plotly Express is the recommended high-level interface. For example “Histograms in Python” is documented at Familiarize yourself with the structure of these pages. Every chart type has a set of examples at a unique URL.To get started with plotly, learn how its documentation is organized: dcc.Graph(figure=fig) with fig a plotly figure. The Plotly Graphing Library, known as the package plotly, generates “figures”.The dcc.Graph component can be used to render any plotly-powered data visualization, passed as the figure argument.
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