# Aligning rotated xticklabels with their respective xticks

## Question:

Check the x axis of the figure below. How can I move the labels a bit to the left so that they align with their respective ticks?

I’m rotating the labels using:

``````ax.set_xticks(xlabels_positions)
ax.set_xticklabels(xlabels, rotation=45)
``````

But, as you can see, the rotation is centered on the middle of the text labels. Which makes it look like they are shifted to the right.

``````ax.set_xticklabels(xlabels, rotation=45, rotation_mode="anchor")
``````

… but it doesn’t do what I wished for. And `"anchor"` seems to be the only value allowed for the `rotation_mode` parameter.

You can set the horizontal alignment of ticklabels, see the example below. If you imagine a rectangular box around the rotated label, which side of the rectangle do you want to be aligned with the tickpoint?

Given your description, you want: ha=’right’

``````n=5

x = np.arange(n)
y = np.sin(np.linspace(-3,3,n))
xlabels = ['Ticklabel %i' % i for i in range(n)]

fig, axs = plt.subplots(1,3, figsize=(12,3))

ha = ['right', 'center', 'left']

for n, ax in enumerate(axs):
ax.plot(x,y, 'o-')
ax.set_title(ha[n])
ax.set_xticks(x)
ax.set_xticklabels(xlabels, rotation=40, ha=ha[n])
``````

Rotating the labels is certainly possible. Note though that doing so reduces the readability of the text. One alternative is to alternate label positions using a code like this:

``````import numpy as np
n=5

x = np.arange(n)
y = np.sin(np.linspace(-3,3,n))
xlabels = ['Long ticklabel %i' % i for i in range(n)]

fig, ax = plt.subplots()
ax.plot(x,y, 'o-')
ax.set_xticks(x)
labels = ax.set_xticklabels(xlabels)
for i, label in enumerate(labels):
label.set_y(label.get_position()[1] - (i % 2) * 0.075)
``````

For more background and alternatives, see this post on my blog

An easy, loop-free alternative is to use the `horizontalalignment` Text property as a keyword argument to `xticks`[1]. In the below, at the commented line, I’ve forced the `xticks` alignment to be “right”.

``````n=5
x = np.arange(n)
y = np.sin(np.linspace(-3,3,n))
xlabels = ['Long ticklabel %i' % i for i in range(n)]
fig, ax = plt.subplots()
ax.plot(x,y, 'o-')

plt.xticks(
[0,1,2,3,4],
["this label extends way past the figure's left boundary",
"bad motorfinger", "green", "in the age of octopus diplomacy", "x"],
rotation=45,
horizontalalignment="right")    # here
plt.show()
``````

(`yticks` already aligns the right edge with the tick by default, but for `xticks` the default appears to be “center”.)

[1] You find that described in the xticks documentation if you search for the phrase “Text properties”.

If you dont want to modify the xtick labels, you can just use:

`plt.xticks(rotation=45)`

`ha='right'` is not enough to visually align labels with ticks:

• For `rotation=45`, use both `ha='right'` and `rotation_mode='anchor'`
• For other angles, use a `ScaledTranslation()` instead

## `rotation_mode='anchor'`

If the rotation angle is roughly 45°, combine `ha='right'` with `rotation_mode='anchor'`:

``````ax.set_xticks(ticks)
ax.set_xticklabels(labels, rotation=45, ha='right', rotation_mode='anchor')
``````

Or in matplotlib 3.5.0+, set ticks and labels at once:

``````ax.set_xticks(ticks, labels, rotation=45, ha='right', rotation_mode='anchor')
``````

## `ScaledTranslation()`

If the rotation angle is more extreme (e.g., 70°) or you just want more fine-grained control, anchoring won’t work well. Instead, apply a linear transform:

``````ax.set_xticks(ticks)
ax.set_xticklabels(labels, rotation=70)

# create -5pt offset in x direction
from matplotlib.transforms import ScaledTranslation
dx, dy = -5, 0
offset = ScaledTranslation(dx / fig.dpi, dy / fig.dpi, fig.dpi_scale_trans)

# apply offset to all xticklabels
for label in ax.xaxis.get_majorticklabels():
label.set_transform(label.get_transform() + offset)
``````

I am clearly late but there is an official example which uses

``````plt.setp(ax.get_xticklabels(), rotation=45, ha="right", rotation_mode="anchor")
``````

to rotate the labels while keeping them correctly aligned with the ticks, which is both clean and easy.

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