have a shared axis that has units, calling `~matplotlib.axis.Axis.set_units` will update each axis with the new units. squeeze : bool, default: True - If True, extra dimensions are squeezed out from the returned array of `~matplotlib.axes.Axes`: - if only one subplot is constructed (nrows=ncols=1), the resulting single Axes object is returned as a scalar. - for Nx1 or 1xM subplots, the returned object is a 1D numpy object array of Axes objects. - for NxM, subplots with N>1 and M>1 are returned as a 2D array. - 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. width_ratios : array-like of length *ncols*, optional Defines the relative widths of the columns. Each column gets a relative width of ``width_ratios[i] / sum(width_ratios)``. If not given, all columns will have the same width. Equivalent to ``gridspec_kw={'width_ratios': [...]}``. height_ratios : array-like of length *nrows*, optional Defines the relative heights of the rows. Each row gets a relative height of ``height_ratios[i] / sum(height_ratios)``. If not given, all rows will have the same height. Convenience for ``gridspec_kw={'height_ratios': [...]}``. subplot_kw : dict, optional Dict with keywords passed to the `~matplotlib.figure.Figure.add_subplot` call used to create each subplot. gridspec_kw : dict, optional Dict with keywords passed to the `~matplotlib.gridspec.GridSpec` constructor used to create the grid the subplots are placed on. **fig_kw All additional keyword arguments are passed to the `.pyplot.figure` call. Returns ------- fig : `.Figure` ax : `~.axes.Axes` or array of Axes *ax* can be either a single `~.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. Typical idioms for handling the return value are:: # using the variable ax for single a Axes fig, ax = plt.subplots() # using the variable axs for multiple Axes fig, axs = plt.subplots(2, 2) # using tuple unpacking for multiple Axes fig, (ax1, ax2) = plt.subplots(1, 2) fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2) The names ``ax`` and pluralized ``axs`` are preferred over ``axes`` because for the latter it's not clear if it refers to a single `~.axes.Axes` instance or a collection of these. See Also -------- .pyplot.figure .pyplot.subplot .pyplot.axes .Figure.subplots .Figure.add_subplot Examples -------- :: # First create some toy data: x = np.linspace(0, 2*np.pi, 400) y = np.sin(x**2) # Create just a figure and only one subplot fig, ax = plt.subplots() ax.plot(x, y) ax.set_title('Simple plot') # Create two subplots and unpack 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) # Create four polar axes and access them through the returned array fig, axs = plt.subplots(2, 2, subplot_kw=dict(projection="polar")) axs[0, 0].plot(x, y) axs[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) # Create figure number 10 with a single subplot # and clears it if it already exists. fig, ax = plt.subplots(num=10, clear=True) ) r‰