Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsCall fig.colorbar() once for each subplot, passing the plot object returned by that subplot’s plotting function as the mappable and the subplot itself as ax. For ordinary grids, layout="constrained" helps Matplotlib make room for the colorbars.
Add a separate colorbar to every subplot
Colorbars are attached to mappables—plot objects that map data values to colors. Keep the object returned by each plotting call, then pass it to fig.colorbar() with its parent axes:
import matplotlib.pyplot as plt
import numpy as np
fig, axs = plt.subplots(2, 2, layout="constrained")
data = np.arange(100).reshape(10, 10)
for i, ax in enumerate(axs.flat):
image = ax.imshow(data * (i + 1), cmap="viridis")
fig.colorbar(image, ax=ax, label=f"Panel {i + 1}")
plt.show()imshow() returns an image mappable. The same approach works with supported mappables from functions such as pcolormesh() and contour plotting: save the returned object and pass it to the colorbar call. The ax argument identifies the subplot associated with that colorbar; when Matplotlib creates a separate colorbar axes, it takes space from the specified parent axes.
Choose a per-subplot or shared colorbar
Use an individual colorbar when each panel needs its own scale. If the plots use a common normalization and their values are meant to be compared directly, a single colorbar for the group may be clearer and take less space. Matplotlib’s multiple-images example demonstrates sharing a normalization and adding one colorbar for a collection of axes.
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Control colorbar placement
Let Matplotlib place it
For standard subplot layouts, pass ax= and let Matplotlib create and position the colorbar. The colorbar placement guide recommends constrained layout for figures with attached colorbars; it automatically adjusts the layout to make room.
Provide a dedicated colorbar axes
For precise positioning, create a dedicated axes for the colorbar and pass it as cax=. When cax is supplied, it determines the colorbar’s size, so the shrink and aspect arguments are ignored. See the Figure.colorbar API for the available arguments.
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Use ImageGrid for a grid with one colorbar per axes
If you are building the grid with mpl_toolkits.axes_grid1.ImageGrid, set cbar_mode="each", then pair each image axes with its corresponding entry in grid.cbar_axes:
from mpl_toolkits.axes_grid1 import ImageGrid
import matplotlib.pyplot as plt
import numpy as np
fig = plt.figure(layout="constrained")
grid = ImageGrid(
fig, 111,
nrows_ncols=(2, 2),
cbar_mode="each",
cbar_location="right",
)
data = np.arange(100).reshape(10, 10)
for i, (ax, cbar_ax) in enumerate(zip(grid, grid.cbar_axes)):
image = ax.imshow(data * (i + 1), cmap="viridis")
fig.colorbar(image, cax=cbar_ax)
plt.show()ImageGrid provides dedicated colorbar axes when configured for each panel. For an ordinary plt.subplots() figure, repeated fig.colorbar(mappable, ax=ax) calls are usually simpler. See Matplotlib’s axes_grid1 examples for the grid helper’s documentation and usage.
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