..seealso::

:ref:`interactive_figures`.

..note::

If you only need to use the classic notebook (i.e. ``notebook<7``),

you can use:

..sourcecode::ipython

%matplotlib notebook

Standalone scripts and interactive use

`.pyplot.subplots`

Creates a new `.Figure` and fills it with a grid of `~.axes.Axes`

`.pyplot` has a notion of "The Current Figure" which can be accessed

through `.pyplot.gcf` and a notion of "The Current Axes" accessed

through `.pyplot.gca`. Almost all of the functions in `.pyplot` pass

through the current `.Figure` / `~.axes.Axes` (or create one) as

appropriate.

`.pyplot.gcf`

Get the current `.Figure`. If there is current no figure on the pyplot figure

stack, a new figure is created

`.pyplot.gca`

Get the current `~.axes.Axes`. If there is current no Axes on the Figure,

a new one is created

Almost all of the functions in `.pyplot` pass through the current `.Figure` / `~.axes.Axes`

(or create one) as appropriate.

Matplotlib keeps a reference to all of the open figures

created via `pyplot.figure` or `pyplot.subplots` so that the figures will not be garbage

..seealso::

For more discussion of Matplotlib's event system and integrated event loops:

-:ref:`interactive_figures_and_eventloops`

-:ref:`event-handling`

..warning::

Using `.Figure.show` it is possible to display a figure on

Using `.Figure.show`, it is possible to display a figure on

the screen without starting the event loop and without being in

interactive mode. This may work (depending on the GUI toolkit) but

will likely result in a non-responsive figure.

..image::../../../_static/toolbar.png

All figure windows come with a navigation toolbar, which can be used

to navigate through the data set. Here is a description of each of

the buttons at the bottom of the toolbar

to navigate through the data set.

..image::../../../../lib/matplotlib/mpl-data/images/home_large.png

..image::../../../../lib/matplotlib/mpl-data/images/forward_large.png

The ``Home``, ``Forward`` and ``Back`` buttons

These areakin to a web browser's home, forward and back controls.

These aresimilar to a web browser's home, forward and back controls.

``Forward`` and ``Back`` are used to navigate back and forth between

previously defined views. They have no meaning unless you have already

navigated somewhere else using the pan and zoom buttons. This is analogous

to trying to click ``Back`` on your web browser before visiting a

new page or ``Forward`` before you have gone back to a page --

nothing happens. ``Home`` always takes you to the

first, default view of your data. Again, all of these buttons should

feel very familiar to any user of a web browser.

nothing happens. ``Home`` takes you to the

first, default view of your data.

..image::../../../../lib/matplotlib/mpl-data/images/move_large.png

The ``Pan/Zoom`` button

This button has two modes: pan and zoom. Click thetoolbar button

This button has two modes: pan and zoom. Click the``Pan/Zoom`` button

to activate panning and zooming, then put your mouse somewhere

over an axes. Press the left mouse button and hold it to pan the

figure, dragging it to a new position. When you release it, the

the right mouse button to zoom, dragging it to a new position.

The x axis will be zoomed in proportionately to the rightward

movement and zoomed out proportionately to the leftward movement.

The same is true for the y axis and up/down motions. The point under your

mouse when you begin the zoom remains stationary, allowing you to

The same is true for the y axis and up/down motions (up zooms in, down zooms out).

The point under yourmouse when you begin the zoom remains stationary, allowing you to

zoom in or out around that point as much as you wish. You can use the

modifier keys 'x', 'y' or 'CONTROL' to constrain the zoom to the x

axis, the y axis, or aspect ratio preserve, respectively.

..image::../../../../lib/matplotlib/mpl-data/images/zoom_to_rect_large.png

The ``Zoom-to-rectangle`` button

Click this toolbar button to activate this mode. Put your mouse somewhere

over an axes and press a mouse button. Define a rectangular region by

The ``Zoom-to-Rectangle`` button

Put your mouse somewhere over an axes and press a mouse button. Define a rectangular region by

dragging the mouse while holding the button to a new location. When using

the left mouse button, the axes view limits will be zoomed to the defined

region. When using the right mouse button, the axes view limits will be

..image::../../../../lib/matplotlib/mpl-data/images/subplots_large.png

The ``Subplot-configuration`` button

Use thistool to configure the appearance of the subplot:

you can stretch or compress the left, right, top, or bottom

Use thisbutton to configure the appearance of the subplot.

You can stretch or compress the left, right, top, or bottom

side of the subplot, or the space between the rows or

space between the columns.

>>>plt.ion()

>>>

however this does not ensure that the event hook is properly installed

However, this does not ensure that the event hook is properly installed

and your figures may not be responsive. Please consult the

documentation of your GUI toolkit for details.

Jupyter Notebooks / JupyterLab

..note::

To get the interactive functionality described here, you must be

using an interactive backend. The default backend in notebooks,

the inline backend, is not. `~ipykernel.pylab.backend_inline`

renders the figure once and inserts a static image into the

notebook when the cell is executed. Because the images are static, they

cannot be panned / zoomed, take user input, or be updated from other

cells.

To get interactive figures in the 'classic' notebook or Jupyter lab,

use the `ipympl<https://matplotlib.org/ipympl>`__ backend

(must be installed separately) which uses the **ipywidget** framework.

to select and enable it.

If you only need to use the classic notebook, you can use

If you only need to use the classic notebook (i.e. ``notebook<7``), you can use

..sourcecode::ipython

which uses the `.backend_nbagg` backend provided by Matplotlib;

however, nbagg does not work in Jupyter Lab.

..note::

To get the interactive functionality described here, you must be

using an interactive backend. The default backend in notebooks,

the inline backend, is not. `~ipykernel.pylab.backend_inline`

renders the figure once and inserts a static image into the

notebook when the cell is executed. Because the images are static, they

cannot be panned / zoomed, take user input, or be updated from other

cells.

GUIs + Jupyter