Tick Labels¶

Customize how tick labels appear on your axes.

set_xticklabels and set_yticklabels¶

Set custom text for tick labels:

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-2*np.pi, 2*np.pi, 100)
y = np.sin(x)

fig, ax = plt.subplots(figsize=(12, 3))
ax.plot(x, y)

ax.set_xticks((-2*np.pi, -np.pi, 0, np.pi, 2*np.pi))
ax.set_yticks((-1, 0, 1))
ax.set_xticklabels(("-2$\\pi$", "-$\\pi$", "0", "$\\pi$", "2$\\pi$"))
ax.set_yticklabels(("-1", "0", "1"))

ax.spines["top"].set_visible(False)
ax.spines["right"].set_visible(False)
ax.spines["bottom"].set_position("zero")
ax.spines["left"].set_position("zero")

plt.show()

Getting Current Labels¶

print(ax.get_xticklabels())
print(ax.get_yticklabels())

Returns a list of Text objects.

Rotating Labels¶

Rotate labels to prevent overlap:

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

# Generate time series data
np.random.seed(0)
error = np.random.normal(size=(400,))
index = pd.date_range(start='2019-09-01', end='2020-01-01', freq='D')

mu = 50
data = [mu + 0.4*error[t-1] + 0.3*error[t-2] + error[t] 
        for t in range(2, len(index)+2)]
s = pd.Series(data, index)

fig, ax = plt.subplots(figsize=(12, 3))
ax.plot(s)
ax.axhline(mu, linestyle='--', color='grey')

# Rotate and align labels
for label in ax.get_xticklabels():
    label.set_horizontalalignment("right")
    label.set_rotation(45)

plt.show()

Text Object Properties¶

Each tick label is a Text object with many properties:

for label in ax.get_xticklabels():
    print(type(label))  # <class 'matplotlib.text.Text'>

Common Text methods:

set_rotation(angle): Rotate the text
set_horizontalalignment(align): 'left', 'center', 'right'
set_verticalalignment(align): 'top', 'center', 'bottom', 'baseline'
set_fontsize(size): Set font size
set_color(color): Set text color
set_bbox(dict): Add background box

Adding Background to Labels¶

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-10, 10, 500)
y = np.sin(x) / x

fig, ax = plt.subplots(figsize=(8, 4))
ax.plot(x, y, linewidth=2)

# Move spines to origin
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.spines['bottom'].set_position(('data', 0))
ax.spines['left'].set_position(('data', 0))

ax.set_xticks([-10, -5, 5, 10])
ax.set_yticks([0.5, 1])

# Add white background to labels
for label in ax.get_xticklabels() + ax.get_yticklabels():
    label.set_bbox({'facecolor': 'white', 'edgecolor': 'white'})

plt.show()

Using tick_params for Styling¶

Bulk styling of tick labels:

ax.tick_params(
    axis='x',
    labelsize=12,
    labelrotation=45,
    labelcolor='blue'
)

ax.tick_params(
    axis='y', 
    labelsize=10,
    labelcolor='green'
)

Categorical Labels¶

For bar charts or categorical data:

import matplotlib.pyplot as plt

categories = ['Mon', 'Tue', 'Wed', 'Thu', 'Fri']
values = [10, 25, 15, 30, 20]

fig, ax = plt.subplots()
ax.bar(range(len(categories)), values)
ax.set_xticks(range(len(categories)))
ax.set_xticklabels(categories)
plt.show()

Hiding Tick Labels¶

Keep ticks but hide labels:

ax.tick_params(labelbottom=False)  # Hide x-axis labels
ax.tick_params(labelleft=False)    # Hide y-axis labels

Or set empty labels:

ax.set_xticklabels([])

Key Takeaways¶

set_xticklabels() and set_yticklabels() set custom label text
Each label is a Text object with full formatting control
Use set_rotation() and set_horizontalalignment() for angled labels
set_bbox() adds a background to labels
tick_params() provides bulk styling options