Quick Start Guide¶
The mpld3 package is extremely easy to use: you can simply take any script generating a matplotlib plot, run it through one of mpld3’s convenience routines, and embed the result in a web page.
The current release of mpld3 can be installed with pip:
pip install mpld3
Then you can make an interactive plot like so:
import matplotlib.pyplot as plt, mpld3 plt.plot([3,1,4,1,5], 'ks-', mec='w', mew=5, ms=20) mpld3.show()
Next, we’ll give a quick overview of the basic mpld3 functions you should know about.
These are the general functions used to convert matplotlib graphics into HTML and D3js. See some examples of these being used in the Example Gallery.
- This function is mpld3’s equivalent of matplotlib’s
plt.showfunction. It will convert the current figure to HTML using
fig_to_d3(), start a local webserver which serves this HTML, and (if the operating system allows it) automatically open this page in the web browser.
IPython Notebook Functions¶
These are functions which enable the use of mpld3 within the IPython notebook. See some examples of these being used in the Notebook Examples.
- This function displays a single mpld3 figure inline within the IPython
notebook. It is useful if you want to use the standard static figure
display hook through the notebook, but override it in a few cases.
If you want every matplotlib figure to be displayed via mpld3, use
enable_notebook()function, described below.
- This function will adjust the IPython notebook display properties so that
mpld3 will be used to display every figure, without having to call
%matplotlib inlinemode within the notebook: see the IPython documentation for details.
- This function undoes the changes made by
enable_notebook(), so that the normal matplotlib backend is used instead.
Saving Figures to File¶
Figures can be saved to file either in a stand-alone HTML format, or in a JSON format. mpld3 supplies the following convenience routines for this purpose:
The mpld3 plugin framework allows nearly endless possibilities for adding interactive behavior to matplotlib plots rendered in d3. The package includes several built-in plugins, which add zooming, panning, and other interactive behaviors to plots. Several examples of these plugins can be seen in the Example Gallery. For some examples of built-in plugins, see Linked Brushing Example, Scatter Plot With Tooltips and HTML tooltip plugin. For some examples of defining custom plugin behavior, see Visualizing Random Walks and Defining a Custom Plugin. More information on using and creating plugins can be found in the Plugins documentation.