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To place the legend outside the plot area, use loc and bbox_to_anchor keywords of legend(). For example, the following code will place the legend to the right of the plot area: legend(loc="upper left", bbox_to_anchor=(1,1)) For more info, see the legend guide
18 gru 2016 · pyplot.show () displays the correct plot with a legend outside it. But when I save it as a file with fig.savefig (), the legend is truncated. Some googling shows me workarounds such as adding bbox_extra_artists= [leg.legendPatch] or bbox_extra_artists= [leg] to savefig (), but neither worked.
26 lis 2022 · To solve this problem we need to place the legend outside the plot. The syntax to set the legend outside is as given below: matplotlib.pyplot.legend (bbox_to_anchor= (x,y)) Example 1: Matplotlib set legend upper-left outside the plot. Python3. import matplotlib.pyplot as plt. import numpy as np. x = np.linspace(0, 10, 100)
6 cze 2023 · You can increase the readability of legend labels by using a semi-transparent legend background. This can be achieved by setting the framealpha parameter in legend(). For example, ax.legend(framealpha=0.5) sets the legend background to be semi-transparent.
22 wrz 2023 · Positioning the legend outside the plot in Matplotlib is fairly easy to do. We simply need to use the bbox_to_anchor and loc parameters of the legend() function. Here's how to do it: import matplotlib.pyplot as plt # Create a simple line plot plt.plot([1, 2, 3, 4], [1, 4, 9, 16], label= 'Sample Data') # Add a legend outside the plot plt.legend ...
ucl = ['upper', 'center', 'lower'] lcr = ['left', 'center', 'right'] fig, ax = plt. subplots (figsize = (6, 4), layout = 'constrained', facecolor = '0.7') ax. plot ([1, 2], [1, 2], label = 'TEST') # Place a legend to the right of this smaller subplot. for loc in ['outside upper left', 'outside upper center', 'outside upper right', 'outside ...
Sometimes you don't want a legend that is explicitly tied to data that you have plotted. For example, say you have plotted 10 lines, but don't want a legend item to show up for each one. If you simply plot the lines and call ax.legend() , you will get the following:
