5 Best Ways to Hide Tick Labels in Python but Keep the Ticks in Place

Rate this post

πŸ’‘ Problem Formulation: When visualizing data in Python, especially with libraries like Matplotlib or Seaborn, it’s sometimes necessary to hide the tick labels of a plot to achieve a cleaner or more minimalist design or to prepare figures for a publication where labels may be superfluous. This article discusses how to achieve this while keeping the tick marks themselves visible, which can aid in understanding the scale or spacing of the data points.

Method 1: Using Matplotlib Tick Parameters

Matplotlib’s Axes object has a method tick_params() which is versatile for controlling appearance properties of ticks, labels, and gridlines. To simply hide the tick labels while leaving the ticks in place, set the labelsize to 0 or adjust the visibility attribute. This method is clear and effective for both the x and y axes separately or together.

Here’s an example:

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.plot(range(10))
ax.tick_params(axis='both', which='both', labelsize=0)

plt.show()

In this code, the tick labels disappear, but the ticks remain on the plot.

This snippet creates a simple line plot using Matplotlib and then uses the tick_params() method to set the labelsize to 0. This effectively hides the labels making them invisible while keeping the tick marks visible on both axes of the plot.

Method 2: Set Empty Strings as Labels

Another method involves directly setting the tick labels to empty strings. By accessing the tick label objects, users can iterate over them and replace the text with an empty string. This method is straightforward and allows for individual tick label control.

Here’s an example:

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.plot(range(10))
ax.set_xticklabels(['' for _ in ax.get_xticks()])
ax.set_yticklabels(['' for _ in ax.get_yticks()])

plt.show()

In this code, the plot displays no tick labels, but the tick marks are visible.

The code snippet uses set_xticklabels() and set_yticklabels() methods to replace all x and y tick labels with empty strings. As a result, the tick labels are not shown on the plot, but the tick marks themselves are kept in place.

Method 3: Tweaking the Axes Formatter

The ticker module in Matplotlib provides functionality to customize tick handling. The NullFormatter is a placeholder formatter that leaves the label strings empty. Applying this to the axes will remove the labels while retaining the ticks.

Here’s an example:

import matplotlib.pyplot as plt
import matplotlib.ticker as ticker

fig, ax = plt.subplots()
ax.plot(range(10))
ax.xaxis.set_major_formatter(ticker.NullFormatter())
ax.yaxis.set_major_formatter(ticker.NullFormatter())

plt.show()

This method will show a plot with visible ticks but without labels.

By setting the axis formatters to an instance of NullFormatter, the tick labels are hidden. It’s a very clean approach since it doesn’t involve working with label properties directly.

Method 4: Customizing through the rcParams

In Matplotlib, rcParams allow for global style parameter settings. Disabling the axis label setting here will affect all plots by default. While powerful, this method is broad and less suited for one-off adjustments.

Here’s an example:

import matplotlib.pyplot as plt

plt.rcParams['xtick.labelsize'] = 0
plt.rcParams['ytick.labelsize'] = 0

fig, ax = plt.subplots()
ax.plot(range(10))

plt.show()

The plot generated will show ticks but no labels for all subsequent plots unless these parameters are reset.

This example modifies the rcParams dict to set the tick label sizes to 0, which will apply these settings globally unless changed back. This method helps when many plots require the same kind of tick label modification.

Bonus One-Liner Method 5: Using List Comprehension

For a quick and dirty one-liner, we can use list comprehension along with the setp() method from Pyplot to directly apply an attribute change to all tick labels.

Here’s an example:

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.plot(range(10))
plt.setp(ax.get_xticklabels() + ax.get_yticklabels(), visible=False)

plt.show()

The produced output shows a graph with the ticks present but no labels.

This one-liner uses the Pyplot setp() function to set the visibility of all x and y tick labels to False, hiding them efficiently while keeping the tick marks.

Summary/Discussion

  • Method 1: Tick Parameters. Allows axis-specific control. Requires minimum code changes.
  • Method 2: Empty String Labels. Flexible and allows individual label edits. Can be a bit verbose for simple tasks.
  • Method 3: Axes Formatter. Clean and uses built-in formatters. Not as intuitive for beginners.
  • Method 4: rcParams Customization. Changes apply globally and provide consistency. May be too broad for specific adjustments.
  • Bonus Method 5: One-Liner List Comprehension. Quick for on-the-fly usage. Can be cryptic and less readable for complex cases.