Matplotlib ~.axes.Axes are the gateway to creating your data visualizations. Once an Axes is placed on a figure there are many methods that can be used to add data to the Axes. An Axes typically has a pair of ~.axis.Axis Artists that define the data coordinate system, and include methods to add annotations like x- and y-labels, titles, and legends.
.. plot::
import matplotlib.pyplot as plt
import numpy as np
fig, axs = plt.subplots(ncols=2, nrows=2, figsize=(3.5, 2.5),
layout="constrained")
# for each Axes, add an artist, in this case a nice label in the middle...
for row in range(2):
for col in range(2):
axs[row, col].annotate(f'axs[{row}, {col}]', (0.5, 0.5),
transform=axs[row, col].transAxes,
ha='center', va='center', fontsize=18,
color='darkgrey')
fig.suptitle('plt.subplots()')
.. toctree::
:maxdepth: 2
axes_intro
.. toctree::
:maxdepth: 1
arranging_axes
colorbar_placement
autoscale
.. toctree::
:maxdepth: 2
:includehidden:
axes_scales
axes_ticks
axes_units
Legends <legend_guide>
Subplot mosaic <mosaic>
.. toctree::
:maxdepth: 1
:includehidden:
Constrained layout guide <constrainedlayout_guide>
Tight layout guide (mildly discouraged) <tight_layout_guide>