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8 cze 2023 · A way get around the issue is to set the two simultaneously. If you have matplotlib>=3.5, then you can pass the labels to set_xticks (or set_yticks for the y-axis) as the second argument. ax.set_xticks(new_ticks) ax.set_xticklabels(new_labels) # <--- error.
One of the most straightforward methods for changing the tick frequency on x or y axis in matplotlib is by using the set_xticks () and set_yticks () functions. These functions allow you to explicitly define the positions where you want tick marks to appear.
If you are directly working with matplotlib's pyplot (plt) and if you are more familiar with the new-style format string, you can try this: from matplotlib.ticker import StrMethodFormatter. plt.gca().yaxis.set_major_formatter(StrMethodFormatter('{x:,.0f}')) # No decimal places.
Set the options for yaxis. The y-axis is the vertical line you see in axis charts.
yticklabels(labels) sets the y-axis tick labels for the current axes. Specify labels as a string array or a cell array of character vectors; for example, {'January','February','March'} .
Customizing the tick values and labels along an axis can help highlight particular aspects of your data. These examples show some common customizations, such as modifying the tick value placement, changing the tick label text and formatting, and rotating the tick labels.
The x and y Axis on each Axes have default tick "locators" and "formatters" that depend on the scale being used (see Axis scales). It is possible to customize the ticks and tick labels with either high-level methods like set_xticks or set the locators and formatters directly on the axis.
