Tick Locators & Formatters

Tick locators decide where the marks on an axis go, while tick formatters decide how each mark's value is written — together they give you complete control over axis labels.

Learn Tick Locators & Formatters in our free Matplotlib course — a beginner-friendly interactive lesson with worked examples, a practice exercise and a quick…

Part of the free Matplotlib course at LearnCodingFast — hands-on lessons with examples you run in your browser, plus practice exercises and a quick quiz.

In this lesson you'll set ticks by hand, place them with MaxNLocator and MultipleLocator , reformat numbers with FuncFormatter and PercentFormatter , rotate crowded labels, and add minor ticks.

The most direct approach: call ax.set_xticks() with the positions where ticks should sit, then ax.set_xticklabels() with the text for each. This is ideal when you plot against numeric positions but want friendly labels like month names underneath.

What you'll see: a five-point line of monthly sales rising overall, with the x-axis marked Jan through May instead of the raw numbers 0 to 4.

When the data range varies, hard-coding ticks is fragile. Locators place them by a rule instead. MultipleLocator(2) puts a tick at every multiple of 2, while MaxNLocator(5) picks at most five nicely rounded values. Both live in matplotlib.ticker and attach via ax.xaxis.set_major_locator() .

What you'll see: two sine waves. The top one has evenly stepped gridlike ticks every 2 units on x and 0.5 on y; the bottom one shows just a handful of clean, rounded x-ticks chosen automatically.

A formatter rewrites each tick's number. PercentFormatter(xmax=1.0) turns 0.25 into 25%. FuncFormatter runs your own function on every value — perfect for currency. StrMethodFormatter("{x:,.0f}") applies a format string with thousands separators. Attach any of them with ax.yaxis.set_major_formatter() .

What you'll see: two panels. The left bars have y-axis labels like $1,200 and $2,400; the right line has y-axis labels like 10% and 30% — the same numbers dressed up for their audience.

Replace each ___ to rotate the long day labels so they stop overlapping.

Hint: 45 degrees with ha="right" is the classic fix for crowded labels.

You set labels without matching positions. Call set_xticks(positions) first, then set_xticklabels(labels) with the same count.

Your formatter function must accept both value and position : lambda v, pos: ... , even if you ignore pos .

Import from the right module: from matplotlib.ticker import MultipleLocator, FuncFormatter, PercentFormatter .

Plot exponential growth with major ticks every 2 and minor ticks every 0.5, format the y-axis with thousands separators, and add a two-level grid.

Lesson complete — your axes now say exactly what you mean!

You set ticks by hand, placed them with MultipleLocator and MaxNLocator , reformatted numbers with FuncFormatter and PercentFormatter , rotated long labels, and added minor ticks.

🚀 Up next: Text, Math & LaTeX in Plots — annotate your charts with words and equations.

Practice quiz

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