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matplotlib.pyplot.subplots

matplotlib.pyplot.subplots(nrows=1, ncols=1, sharex=False, sharey=False, squeeze=True, subplot_kw=None, gridspec_kw=None, **fig_kw)

Create a figure and a set of subplots

This utility wrapper makes it convenient to create common layouts of subplots, including the enclosing figure object, in a single call.

Parameters:

nrows, ncols : int, optional, default: 1

Number of rows/columns of the subplot grid.

sharex, sharey : bool or {‘none’, ‘all’, ‘row’, ‘col’}, default: False

Controls sharing of properties among x (sharex) or y (sharey) axes:

  • True or ‘all’: x- or y-axis will be shared among all subplots.
  • False or ‘none’: each subplot x- or y-axis will be independent.
  • ‘row’: each subplot row will share an x- or y-axis.
  • ‘col’: each subplot column will share an x- or y-axis.

When subplots have a shared x-axis along a column, only the x tick labels of the bottom subplot are visible. Similarly, when subplots have a shared y-axis along a row, only the y tick labels of the first column subplot are visible.

squeeze : bool, optional, default: True

  • If True, extra dimensions are squeezed out from the returned Axes object:

    • if only one subplot is constructed (nrows=ncols=1), the resulting single Axes object is returned as a scalar.
    • for Nx1 or 1xN subplots, the returned object is a 1D numpy object array of Axes objects are returned as numpy 1D arrays.
    • for NxM, subplots with N>1 and M>1 are returned as a 2D arrays.
  • If False, no squeezing at all is done: the returned Axes object is always a 2D array containing Axes instances, even if it ends up being 1x1.

subplot_kw : dict, optional

Dict with keywords passed to the add_subplot() call used to create each subplot.

gridspec_kw : dict, optional

Dict with keywords passed to the GridSpec constructor used to create the grid the subplots are placed on.

**fig_kw :

All additional keyword arguments are passed to the figure() call.

Returns:

fig : matplotlib.figure.Figure object

ax : Axes object or array of Axes objects.

ax can be either a single matplotlib.axes.Axes object or an array of Axes objects if more than one subplot was created. The dimensions of the resulting array can be controlled with the squeeze keyword, see above.

See also

figure, subplot

Examples

First create some toy data:

>>> x = np.linspace(0, 2*np.pi, 400)
>>> y = np.sin(x**2)

Creates just a figure and only one subplot

>>> fig, ax = plt.subplots()
>>> ax.plot(x, y)
>>> ax.set_title('Simple plot')

Creates two subplots and unpacks the output array immediately

>>> f, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
>>> ax1.plot(x, y)
>>> ax1.set_title('Sharing Y axis')
>>> ax2.scatter(x, y)

Creates four polar axes, and accesses them through the returned array

>>> fig, axes = plt.subplots(2, 2, subplot_kw=dict(polar=True))
>>> axes[0, 0].plot(x, y)
>>> axes[1, 1].scatter(x, y)

Share a X axis with each column of subplots

>>> plt.subplots(2, 2, sharex='col')

Share a Y axis with each row of subplots

>>> plt.subplots(2, 2, sharey='row')

Share both X and Y axes with all subplots

>>> plt.subplots(2, 2, sharex='all', sharey='all')

Note that this is the same as

>>> plt.subplots(2, 2, sharex=True, sharey=True)

Examples using matplotlib.pyplot.subplots

../../_images/sphx_glr_mri_demo_thumb.png

MRI