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.. _toolkits-index:
.. toctree::
:hidden:
axes_grid/index.rst
mplot3d/index.rst
.. _toolkits:
########
Toolkits
########
Toolkits are collections of application-specific functions that extend matplotlib.
.. _toolkits-mapping:
Mapping Toolkits
****************
.. _toolkit_basemap:
Basemap
=======
(*Not distributed with matplotlib*)
Plots data on map projections, with continental and political
boundaries, see `basemap <http://matplotlib.org/basemap>`_
docs.
.. image:: /_static/basemap_contour1.png
:height: 400px
Cartopy
=======
(*Not distributed with matplotlib*)
An alternative mapping library written for matplotlib ``v1.2`` and beyond.
`Cartopy <http://scitools.org.uk/cartopy/docs/latest>`_ builds on top of
matplotlib to provide object oriented map projection definitions and close
integration with Shapely for powerful yet easy-to-use vector data processing
tools. An example plot from the
`Cartopy gallery <http://scitools.org.uk/cartopy/docs/latest/gallery.html>`_:
.. image:: /_static/cartopy_hurricane_katrina_01_00.png
:height: 400px
.. _toolkits-shipped:
General Toolkits
****************
.. _toolkit_mplot3d:
mplot3d
=======
.. toctree::
:maxdepth: 2
mplot3d/index
:ref:`mpl_toolkits.mplot3d <toolkit_mplot3d-index>` provides some basic 3D plotting (scatter, surf,
line, mesh) tools. Not the fastest or feature complete 3D library out
there, but ships with matplotlib and thus may be a lighter weight
solution for some use cases.
.. plot:: mpl_examples/mplot3d/contourf3d_demo2.py
.. _toolkit_axes_grid:
AxesGrid
========
.. toctree::
:maxdepth: 2
axes_grid/index
The matplotlib :ref:`AxesGrid <toolkit_axesgrid-index>` toolkit is a collection of helper classes to
ease displaying multiple images in matplotlib. The AxesGrid toolkit is
distributed with matplotlib source.
.. image:: /_static/demo_axes_grid.png
.. _toolkit_mplcursors:
mplcursors
==========
`mplcursors <https://mplcursors.readthedocs.io>`_ provides interactive
data cursors for matplotlib.
.. _toolkit_mpldatacursor:
MplDataCursor
=============
(*Not distributed with matplotlib*)
`MplDataCursor <https://github.com/joferkington/mpldatacursor>`_ is a
toolkit written by Joe Kington to provide interactive "data cursors"
(clickable annotation boxes) for matplotlib.
.. _toolkit_gtk:
GTK Tools
=========
mpl_toolkits.gtktools provides some utilities for working with GTK.
This toolkit ships with matplotlib, but requires `pygtk
<http://www.pygtk.org/>`_.
.. _toolkit_excel:
Excel Tools
===========
mpl_toolkits.exceltools provides some utilities for working with
Excel. This toolkit ships with matplotlib, but requires
`xlwt <https://pypi.python.org/pypi/xlwt>`_
.. _toolkit_natgrid:
Natgrid
=======
(*Not distributed with matplotlib*)
mpl_toolkits.natgrid is an interface to natgrid C library for gridding
irregularly spaced data. This requires a separate installation of the
`natgrid toolkit <https://github.com/matplotlib/natgrid>`__.
.. _toolkit_matplotlibvenn:
Matplotlib-Venn
===============
(*Not distributed with matplotlib*)
`Matplotlib-Venn <https://github.com/konstantint/matplotlib-venn>`_ provides a set of functions for plotting 2- and 3-set area-weighted (or unweighted) Venn diagrams.
mplstereonet
===============
(*Not distributed with matplotlib*)
`mplstereonet <https://github.com/joferkington/mplstereonet>`_ provides stereonets for plotting and analyzing orientation data in Matplotlib.
.. _hl_plotting:
High-Level Plotting
*******************
Several projects have started to provide a higher-level interface to
matplotlib. These are independent projects.
.. _toolkit_seaborn:
seaborn
=======
(*Not distributed with matplotlib*)
`seaborn <https://seaborn.github.io/>`_ is a high level interface for drawing
statistical graphics with matplotlib. It aims to make visualization a central
part of exploring and understanding complex datasets.
.. image:: /_static/seaborn.png
:height: 157px
.. _toolkit_holoviews:
holoviews
=========
(*Not distributed with matplotlib*)
`holoviews <http://holoviews.org>`_ makes it easier to visualize data
interactively, especially in a `Jupyter notebook
<http://jupyter.org>`_, by providing a set of declarative
plotting objects that store your data and associated metadata. Your
data is then immediately visualizable alongside or overlaid with other
data, either statically or with automatically provided widgets for
parameter exploration.
.. image:: /_static/holoviews.png
:height: 354px
.. _toolkit_ggplot:
ggplot
======
(*Not distributed with matplotlib*)
`ggplot <https://github.com/yhat/ggplot>`_ is a port of the R ggplot2
to python based on matplotlib.
.. image:: /_static/ggplot.png
:height: 195px
.. _toolkit_prettyplotlib:
prettyplotlib
=============
(*Not distributed with matplotlib*)
`prettyplotlib <https://olgabot.github.io/prettyplotlib>`_ is an extension
to matplotlib which changes many of the defaults to make plots some
consider more attractive.
iTerm2 terminal backend
=======================
(*Not distributed with matplotlib*)
`matplotlib_iterm2 <https://github.com/oselivanov/matplotlib_iterm2>`_ is an
external matplotlib backend uses iTerm2 nightly build inline image display
feature.
.. image:: /_static/matplotlib_iterm2_demo.png
|
