How to Prevent Overlapping or Cut-off Labels in Matplotlib?

Dealing with Overlapping or Cut-off Labels in Matplotlib

In matplotlib, accommodating labeling elements appropriately can be crucial for producing informative visualizations. However, oversized labels or intricate expressions may extend beyond the designated plot area, leading to obscured text. To address this issue, we delve into adjusting padding to provide ample space for these labels.

Adjusting Padding

One solution is to manually adjust the padding using the subplots_adjust() function. This function grants control over the spacing surrounding axes, including top, bottom, left, and right margins. By increasing the bottom margin, we can create more vertical space for the x-axis label.

import matplotlib.pyplot as plt

plt.gcf().subplots_adjust(bottom=0.15)

Alternatively, matplotlib provides the tight_layout() function to automatically adjust padding. This function optimizes the layout of all axes in a figure to accommodate labels.

plt.tight_layout()

Example with Subplots

In the revised MRE, subplots are utilized. Despite having large x and y labels, the labels are adequately adjusted using subplots_adjust().

Conclusion

Adjusting padding or utilizing tight_layout() is an effective means of ensuring label readability. These methods provide control over the surrounding space, enabling optimal utilization of the plot area. By carefully adjusting the padding, we can prevent label cutoff and enhance the overall aesthetics of our visualizations.

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