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Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Repair Windows errors before they cause bigger problemsFix Now →To set theta ticks on a Matplotlib polar plot, call ax.set_thetagrids(angles, labels=...) on the polar axes. The angles argument is in degrees, even though the polar axis stores its native angle values in radians. The pyplot equivalent, plt.thetagrids(...), acts on the current polar plot. Those two calls cover fixed positions and custom names. For labels that must stay correct as the user pans or zooms, you need to configure the axis locator and formatter instead, and the sections below explain when each approach applies.
Set fixed theta positions and labels
A polar axes is created with projection="polar". Its angular axis is the theta axis, and set_thetagrids controls both where the angular gridlines fall and what text appears at each one. The method returns the gridline objects and the text label objects it created, so you can restyle them afterwards if needed.
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Object-oriented form: ax.set_thetagrids()
Pass a sequence of angles in degrees and, optionally, a sequence of labels of the same length:
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fig, ax = plt.subplots(subplot_kw={"projection": "polar"})
ax.set_thetagrids([0, 45, 90, 135, 180], labels=["N", "NE", "E", "SE", "S"])
plt.show()Each label is attached to the angle at the same index. If you omit labels, or pass None, Matplotlib uses its default theta formatter and shows the angles as degrees.
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Pyplot form: plt.thetagrids()
The pyplot function accepts the same positions and labels and applies them to the current polar axes. The Matplotlib example gallery uses this form to place four compass-style labels:
plt.thetagrids(range(45, 360, 90), ("NE", "NW", "SW", "SE"))Use the object-oriented form when a figure contains several axes or when you hold a reference to the axes. The pyplot form is convenient in short scripts where the current axes is the one you want.
Default labels: the theta formatter and locator
When you do not supply labels, Matplotlib’s ThetaFormatter takes the native radian value of each tick, converts it to degrees, and appends a degree symbol. The Matplotlib API reference for matplotlib.projections.polar describes it this way: “Used to format the theta tick labels. Converts the native unit of radians into degrees and adds a degree symbol.”
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Tick positions come from ThetaLocator. In most views it delegates to its base locator. When the view spans the full circle, it switches to the familiar 45-degree positions. That is why a default full polar plot shows eight evenly spaced labels without any configuration.
Custom label text and format strings
There are two ways to change how labels look without supplying every label by hand.
Format strings with fmt
The fmt argument of set_thetagrids is passed to a FormatStrFormatter. The API reference notes that the value the format string receives is the angle in radians, not degrees. A format such as "%.2f" therefore prints a radian value. If you want degrees, the format string alone is not enough; use a function, as described next.
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Function-based labels with FuncFormatter
When label text depends on logic, pass a formatter to the theta axis. A FuncFormatter receives the tick value in radians and the tick position, and returns a string:
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from matplotlib import ticker
ax.xaxis.set_major_formatter(
ticker.FuncFormatter(lambda x, pos: f"{round(math.degrees(x))}°")
)The theta axis is the xaxis of a polar axes, while the radial axis is the yaxis. The locator decides where ticks go; the formatter decides what they say. Keep those two jobs separate when you design a label scheme.
Why styling disappears after you zoom or pan
The main pitfall is that set_thetagrids changes the properties of the tick instances that exist at the moment you call it. The API reference warns that later operations can create, delete or modify tick instances. Interactive panning and zooming are among those operations, so text you styled through set_thetagrids may not survive a view change.
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If the labels must stay correct as the view changes, move the configuration to the axis level:
- Set the positions with a fixed locator on the theta axis, using radians, for example
ax.xaxis.set_major_locator(ticker.FixedLocator(np.radians([0, 90, 180, 270])))after importing NumPy asnp. - Set the text with a formatter on the same axis, either
ticker.FixedFormatterwith a list of names matching the locator, or theFuncFormattershown above. - Apply any styling, such as font size or colour, through the tick label settings after the locator and formatter are in place, and check the result after interacting with the plot.
Fixed positions and labels are simple and quick to write. Axis-level locators and formatters are the better choice when the plot will be panned, zoomed or redrawn in an interactive session.
Orientation and angular range are separate settings
Tick placement does not change where zero sits or which way angles increase. Those are controlled by separate methods, and each one has its own units. The table below summarises the calls covered by the Matplotlib polar reference.
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| Goal | Call | Units and notes |
|---|---|---|
| Place angular gridlines and labels | ax.set_thetagrids(angles, labels=...) |
Angles in degrees; affects current ticks only |
| Same, via pyplot | plt.thetagrids(angles, labels) |
Angles in degrees; applies to the current polar axes |
| Change the label format string | set_thetagrids(..., fmt=...) |
Format receives radians |
| Set zero location | ax.set_theta_zero_location(loc, offset=...) |
Offset is always applied counterclockwise, whatever the direction setting |
| Set clockwise or counterclockwise increase | ax.set_theta_direction(...) |
Controls the direction in which angles increase |
| Restrict visible angular range | ax.set_thetalim(...) |
Positional arguments are radians; keyword arguments thetamin= and thetamax= are degrees |
The Matplotlib polar demo restricts the visible range with set_thetamin(0) and set_thetamax(225), which is a useful pattern when a plot covers only a sector of the circle.
Choosing an approach
| Situation | Recommended approach |
|---|---|
| Static figure with a few named directions | set_thetagrids with labels |
| Quick script using the current axes | plt.thetagrids |
| Labels need logic, such as converting radians to degrees with a custom suffix | FuncFormatter on the theta axis |
| Interactive plot where users pan or zoom | Axis-level fixed or function locator and formatter, then verify after interaction |
| Changing where zero sits or the direction of increase | set_theta_zero_location and set_theta_direction, separate from tick calls |
Sources used for the signatures and behaviour above are the Matplotlib stable documentation: the PolarAxes page (version 3.11.1), the pyplot thetagrids page (version 3.11.0), and the ticker and polar demo pages (version 3.11.2). Behaviour can differ in other releases, so check the page for your installed version when a detail matters. The examples here illustrate the calls; they have not been run as part of this article.
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