Matplotlib tick_params(): Customize Ticks and Tick Labels

tick_params() changes how ticks, tick labels and gridlines look in Matplotlib: their direction, length, width, colour, label size, rotation and which sides of the plot show them. Call it on an axes, ax.tick_params(...), or use plt.tick_params(...) for the current axes. It changes existing and future ticks, so you do not need to recreate them. This guide explains every important Matplotlib tick_params parameter with real plots, plus colorbars, zorder, seaborn and two mistakes that silently do nothing.

Tested with Python 3.12.5, Matplotlib 3.11.2 and seaborn 0.13.2; the plots are real Matplotlib windows. The full parameter list is in the Axes.tick_params documentation.

Basic tick_params example

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 10, 100)
fig, ax = plt.subplots(figsize=(7, 4))
ax.plot(x, np.sin(x))

ax.tick_params(axis="both", direction="in", length=8, width=1.5,
               colors="darkblue", labelsize=12, pad=8)
ax.set_title("tick_params: direction, length, width, colors, labelsize")
plt.tight_layout()
plt.show()

tick_params parameters

Parameter	Values	What it does
axis	“x”, “y”, “both” (default)	Which axis to change
which	“major” (default), “minor”, “both”	Major ticks, minor ticks or both
direction	“out”, “in”, “inout”	Ticks point out of, into, or across the axes
length, width	points	Tick size and line thickness
color	colour	Colour of the tick marks only
labelcolor	colour	Colour of the tick labels only
colors	colour	Colour of both tick marks and labels
labelsize	points or “small”, “large”…	Font size of the tick labels
labelrotation	degrees	Rotate the tick labels
pad	points	Distance between tick and label
bottom, top, left, right	True / False	Show or hide the tick marks on each side
labelbottom, labeltop, labelleft, labelright	True / False	Show or hide the tick labels on each side
grid_color, grid_alpha, grid_linewidth, grid_linestyle	grid line properties	Style the gridlines at the ticks

direction: out, in and inout

The default is "out". "in" is common in scientific plots and "inout" crosses the axis line:

import matplotlib.pyplot as plt

fig, axes = plt.subplots(1, 3, figsize=(9, 3))
for ax, direction in zip(axes, ["out", "in", "inout"]):
    ax.plot([0, 1, 2, 3], [1, 3, 2, 4])
    ax.tick_params(direction=direction, length=8, width=1.2)
    ax.set_title(f'direction="{direction}"')
plt.tight_layout()
plt.show()

Major and minor ticks, and label colours

Use which= to style major and minor ticks separately, and axis= to change only one axis. color changes the tick marks, labelcolor the labels, and colors both:

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 10, 200)
fig, ax = plt.subplots(figsize=(7, 4))
ax.plot(x, np.exp(x / 4))
ax.minorticks_on()                                            # add minor ticks

ax.tick_params(which="major", length=10, width=1.5, color="black", labelsize=11)
ax.tick_params(which="minor", length=4, width=0.8, color="gray")
ax.tick_params(axis="y", labelcolor="tab:red")                # only the y tick labels
plt.tight_layout()
plt.show()

Rotate tick labels and show ticks on all sides

import matplotlib.pyplot as plt

months = ["January", "February", "March", "April", "May", "June"]
fig, ax = plt.subplots(figsize=(7, 4.2))
ax.bar(months, [12, 15, 11, 18, 21, 19], color="tab:olive")

ax.tick_params(axis="x", labelrotation=45)                    # rotate the x tick labels
ax.tick_params(top=True, right=True, direction="in")          # ticks on all four sides
ax.tick_params(labelright=True)                               # y labels on the right as well
plt.tight_layout()
plt.show()

For alignment options when rotating, see rotate tick labels in Matplotlib; to hide ticks or labels instead, see remove tick labels in Matplotlib.

plt.tick_params vs ax.tick_params

They accept exactly the same arguments. plt.tick_params() changes the current axes (the last one created or selected); ax.tick_params() changes the axes you call it on. With several subplots, use the axes version so you know which plot changes; to style all subplots, loop over them: for ax in axes.flat: ax.tick_params(labelsize=8).

Colorbar ticks: cbar.ax.tick_params

A colorbar has its own axes, so style it through cbar.ax:

import matplotlib.pyplot as plt
import numpy as np

data = np.random.default_rng(2).normal(size=(15, 15)).cumsum(axis=1)
fig, ax = plt.subplots(figsize=(6.5, 5))
im = ax.imshow(data, cmap="magma")
cbar = fig.colorbar(im, ax=ax)

ax.tick_params(labelsize=9, length=0)                          # the image axes
cbar.ax.tick_params(labelsize=11, direction="in", length=6, colors="tab:blue")   # the colorbar
plt.show()

Check the current settings, and why bottom=’off’ does not work

Matplotlib 3.7 added get_tick_params() to read what you set. Older tutorials use bottom='off', which was the Matplotlib 1.x syntax; today the string 'off' is simply a truthy value, so the ticks stay visible without any error:

import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.plot([1, 2, 3])
ax.tick_params(axis="x", direction="out", length=6, labelsize=9)
print("x tick settings:", ax.xaxis.get_tick_params(which="major"))    # Matplotlib 3.7+

# old Matplotlib 1.x style: the string "off" is truthy, so the ticks stay visible
ax.tick_params(axis="x", bottom="off")
fig.canvas.draw()
print("bottom='off' -> tick drawn:", bool(ax.xaxis.get_major_ticks()[0].tick1line.get_visible()))

ax.tick_params(axis="x", bottom=False)                                # correct: a boolean
fig.canvas.draw()
print("bottom=False -> tick drawn:", bool(ax.xaxis.get_major_ticks()[0].tick1line.get_visible()))

Output:

x tick settings: {'length': 6, 'direction': 'out', 'bottom': True, 'top': False, 'labelbottom': True, 'labeltop': False, 'gridOn': False, 'labelsize': 9}
bottom='off' -> tick drawn: True
bottom=False -> tick drawn: False

tick_params zorder: draw ticks above the data

tick_params() accepts a zorder argument, but in practice the ticks are drawn together with their axis, so what decides whether ticks appear above or below your data is the axis order. Use ax.set_axisbelow(False) to put ticks and gridlines on top (or True to put them behind everything):

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 10, 60)
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(9, 3.6))
for ax in (ax1, ax2):
    ax.plot(x, 3 + np.sin(x), color="tab:blue")
    ax.axhline(0.35, color="gold", linewidth=22)             # a thick band along the bottom edge
    ax.set_ylim(0, 5)
    ax.tick_params(direction="in", length=14, width=2.5, color="red")

ax1.set_title("default: the band hides the x ticks")
ax2.set_axisbelow(False)                                      # draw ticks (and grid) above the data
ax2.set_title("ax.set_axisbelow(False)")
plt.tight_layout()
plt.show()