Skip to main content

D3 Viewer for Matplotlib

Project description

This is an interactive D3js-based viewer which brings matplotlib graphics to the browser. Please visit [http://mpld3.github.io](http://mpld3.github.io) for documentation and examples.

You may also see the [blog post](http://jakevdp.github.io/blog/2013/12/19/a-d3-viewer-for-matplotlib/), or the [IPython notebook examples](http://nbviewer.ipython.org/github/jakevdp/mpld3/tree/master/notebooks/) available in the notebooks directory of this repository.

[![version status](https://img.shields.io/pypi/v/mpld3.svg)](https://pypi.python.org/pypi/mpld3) [![downloads](https://img.shields.io/pypi/dm/mpld3.svg)](https://pypi.python.org/pypi/mpld3) [![build status](https://travis-ci.org/jakevdp/mpld3.svg?branch=master)](https://travis-ci.org/jakevdp/mpld3)

About

mpld3 provides a custom stand-alone javascript library built on D3, which parses JSON representations of plots. The mpld3 python module provides a set of routines which parses matplotlib plots (using the [mplexporter](http://github.com/mpld3/mplexporter) framework) and outputs the JSON description readable by mpld3.js.

Installation

mpld3 is compatible with python 2.6-2.7 and 3.3-3.4. It requires [matplotlib](http://matplotlib.org) version 2.2.2 and [jinja2](http://jinja.pocoo.org/) version 2.7+.

Optionally, mpld3 can be used with [IPython](http://ipython.org) notebook, and requires IPython version 1.x or (preferably) version 2.0+.

This package is based on the [mplexporter](http://github.com/mpld3/mplexporter) framework for crawling and exporting matplotlib images. mplexporter is bundled with the source distribution via git submodule.

Within the git source directory, you can download the mplexporter dependency and copy it into the mpld3 source directory using the following command:

[~]$ python setup.py submodule

The submodule command is not necessary if you are installing from a distribution rather than from the git source.

Once the submodule command has been run, you can build the package locally using

[~]$ python setup.py build

or install the package to the standard Python path using:

[~]$ python setup.py install

Or, to install to another location, use

[~]$ python setup.py install –prefix=/path/to/location/

Then make sure your PYTHONPATH environment variable points to this location.

Trying it out

The package is pure python, and very light-weight. You can take a look at the notebooks in the examples directory, or run create_example.py, which will create a set of plots and launch a browser window showing interactive views of these plots.

For a more comprehensive set of examples, see the [IPython notebook examples](http://nbviewer.ipython.org/github/jakevdp/mpld3/tree/master/notebooks/) available in the notebooks directory.

Test Plots

To explore the comparison between D3 renderings and matplotlib renderings for various plot types, run the script visualize_tests.py. This will generate an HTML page with the D3 renderings beside corresponding matplotlib renderings.

Features

Many of the core features of matplotlib are already supported. And additionally there is some extra interactivity provided via the plugin framework. The following is a non-exhausive list of features that are yet to be supported:

  • tick specification & formatting

  • some legend features

  • blended transforms, such as those required by axvlines and axhlines

  • twin axes (i.e. multiple scales on one plot) tied together

If any of these look like something you’d like to tackle, feel free to submit a pull request!

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mpld3-0.5.0.tar.gz (1.0 MB view details)

Uploaded Source

File details

Details for the file mpld3-0.5.0.tar.gz.

File metadata

  • Download URL: mpld3-0.5.0.tar.gz
  • Upload date:
  • Size: 1.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: Python-urllib/3.7

File hashes

Hashes for mpld3-0.5.0.tar.gz
Algorithm Hash digest
SHA256 dccc708cc3c997c4478ab9fe4e973a75950683761e99b9e2b89cc96548ac0a57
MD5 d62d8276bb79c5d8744a2dc9ae3d128b
BLAKE2b-256 28003fc56f19ee9436ec5f98fbdfe22acb2e9cec0db0d08f6298e881a4912e58

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page