What is the correct way to replace matplotlib tick labels with computed values?

We can use ax.loglog(x, y) and set_major_formatter() methods to replace matplotlib tick labels with computed values. This technique is particularly useful when working with logarithmic scales or when you need custom formatting for your axis labels.

Steps

• Set the figure size and adjust the padding between and around the subplots.

• Create a figure and a set of subplots.

• Make a plot with log scaling on both the X and Y axis.

• Set the formatter of the major ticker.

• To display the figure, use show() method.

Example 1: Using LogFormatterExponent

Here's how to replace tick labels with exponential notation −

import numpy as np
from matplotlib import pyplot as plt, ticker

plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

fig, ax = plt.subplots()

# Create logarithmic plot
x = np.logspace(0, 5)
y = x**2
ax.loglog(x, y)

# Format x-axis with exponential notation
ax.xaxis.set_major_formatter(ticker.LogFormatterExponent())

plt.title("Logarithmic Plot with Exponential Notation")
plt.show()

Example 2: Using Custom Formatter

You can also create a custom formatter for more control over tick labels −

import numpy as np
from matplotlib import pyplot as plt, ticker

fig, ax = plt.subplots(figsize=(8, 4))

# Sample data
x = np.linspace(0, 10, 100)
y = np.exp(x/5)

ax.semilogy(x, y)

# Custom formatter function
def custom_formatter(x, pos):
    return f'{x:.1f}s'

# Apply custom formatter to x-axis
ax.xaxis.set_major_formatter(ticker.FuncFormatter(custom_formatter))

plt.title("Semi-log Plot with Custom Tick Labels")
plt.xlabel("Time")
plt.ylabel("Value")
plt.show()

Example 3: Using FixedFormatter for Specific Labels

For completely custom labels at specific positions −

import numpy as np
from matplotlib import pyplot as plt, ticker

fig, ax = plt.subplots(figsize=(8, 4))

# Sample data
x = np.arange(5)
y = [10, 25, 40, 30, 15]

ax.bar(x, y)

# Set custom tick labels
custom_labels = ['Jan', 'Feb', 'Mar', 'Apr', 'May']
ax.xaxis.set_major_formatter(ticker.FixedFormatter(custom_labels))
ax.xaxis.set_major_locator(ticker.FixedLocator(x))

plt.title("Bar Chart with Custom Month Labels")
plt.ylabel("Sales")
plt.show()

Common Formatter Types

Conclusion

Use set_major_formatter() with appropriate formatter classes to customize tick labels. Choose LogFormatterExponent for logarithmic plots, FuncFormatter for custom functions, or FixedFormatter for specific text labels.