# python - set_xticks - matplotlib xticks

## How to move a tick's label in matplotlib? (3)

I would like to move some ticks' labels horizontally along the x-axis, without moving the corresponding ticks.

More specifically, when rotating labels with `plt.setp`

, the centers of the labels' text stay aligned with the ticks. I would like to shift those labels to the right, so that the near ends of the labels get aligned instead as suggested on the image below.

I am aware of this post and this one, however the answers are interesting kludges rather than strict answers to the question.

my code:

```
import matplotlib.pyplot as plt
import numpy as np
import datetime
# my fake data
dates = np.array([datetime.datetime(2000,1,1) + datetime.timedelta(days=i) for i in range(365*5)])
data = np.sin(np.arange(365*5)/365.0*2*np.pi - 0.25*np.pi) + np.random.rand(365*5) /3
# creates fig with 2 subplots
fig = plt.figure(figsize=(10.0, 6.0))
ax = plt.subplot2grid((2,1), (0, 0))
ax2 = plt.subplot2grid((2,1), (1, 0))
## plot dates
ax2.plot_date( dates, data )
# rotates labels
plt.setp( ax2.xaxis.get_majorticklabels(), rotation=-45 )
# try to shift labels to the right
ax2.xaxis.get_majorticklabels()[2].set_y(-.1)
ax2.xaxis.get_majorticklabels()[2].set_x(10**99)
plt.show()
```

Strangely enough, `set_y`

behaves as expected, but even if I set `x`

to a fantasillion, the labels would not move by one iota.
(The use of `plot_date`

may introduce additional confusion, but the same actually happens with `plot`

.)

Another way of doing a horizontal alignment:

```
plt.xticks(ha='left')
```

First of all, let's use a mcve to show the problem.

```
import numpy as np
import datetime
import matplotlib.pyplot as plt
plt.rcParams["date.autoformatter.month"] = "%b %Y"
# my fake data
dates = np.array([datetime.datetime(2000,1,1) + datetime.timedelta(days=i) for i in range(365)])
data = np.sin(np.arange(365)/365.0*2*np.pi - 0.25*np.pi) + np.random.rand(365) /3
# creates fig with 2 subplots
fig, ax = plt.subplots(figsize=(6,2))
## plot dates
ax.plot_date( dates, data )
# rotates labels
plt.setp( ax.xaxis.get_majorticklabels(), rotation=-45 )
plt.tight_layout()
plt.show()
```

Now as other anwers pointed out already, you may use horizontal alignment of the text.

```
# rotates labels and aligns them horizontally to left
plt.setp( ax.xaxis.get_majorticklabels(), rotation=-45, ha="left" )
```

You may use the `rotation_mode`

argument to let the rotation happen about the top left point of the text, giving a slightly nicer result in this case.

```
# rotates labels and aligns them horizontally to left
plt.setp( ax.xaxis.get_majorticklabels(), rotation=-45, ha="left", rotation_mode="anchor")
```

In case those options are not fine grained enough, i.e. you want to position the labels more accurately, e.g. shifting it to the side by some points, you may use a transform. The following would offset the label by 5 points in horizontal direction, using a `matplotlib.transforms.ScaledTranslation`

.

```
import matplotlib.transforms
plt.setp( ax.xaxis.get_majorticklabels(), rotation=-45)
# Create offset transform by 5 points in x direction
dx = 5/72.; dy = 0/72.
offset = matplotlib.transforms.ScaledTranslation(dx, dy, fig.dpi_scale_trans)
# apply offset transform to all x ticklabels.
for label in ax.xaxis.get_majorticklabels():
label.set_transform(label.get_transform() + offset)
```

The advantage of this, compared to e.g. the solution provided by @explorerDude is that the offset is independent on the data in the graph, such that it is generally applicable to any plot and would look the same for a given fontsize.

Instead of

```
ax2.xaxis.get_majorticklabels()[2].set_y(-.1)
ax2.xaxis.get_majorticklabels()[2].set_x(10**99)
```

use the `set_horizontalalignment()`

for each tick on the axis:

```
for tick in ax2.xaxis.get_majorticklabels():
tick.set_horizontalalignment("left")
```

resulting in: