5 Best Ways to Remove Grid Lines from an Image in Python Matplotlib

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💡 Problem Formulation: In data visualization using Python’s Matplotlib library, grid lines can sometimes clutter an image, making it difficult to focus on the actual data. The problem at hand is the removal of these grid lines from plots to achieve cleaner graphics. Typically, we start with a plot that has grid lines visible and aim to produce an image where these lines are no longer present.

Method 1: Using ax.grid(False)

This method involves using the grid() function and passing False as an argument to turn off the grid lines in the axis object.

Here’s an example:

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.plot([0, 1], [0, 1])
ax.grid(False)
plt.show()

The output of this code snippet is a line chart without grid lines.

This code snippet first creates a figure and an axis object using subplots(). It then plots a simple line graph using ax.plot(). The ax.grid(False) is the key; it disables grid lines for that axis. Finally, plt.show() displays the plot.

Method 2: Using plt.grid(False)

In case you’re working with pyplot’s script-like interface, you can remove grid lines by calling plt.grid() and setting it to False.

Here’s an example:

import matplotlib.pyplot as plt

plt.plot([0, 1], [0, 1])
plt.grid(False)
plt.show()

The output is similar to Method 1, yielding a plot without grid lines.

This snippet works on the Matplotlib state-based interface, calling plt.plot() to create the graph and plt.grid(False) to hide grid lines. plt.show() is then used to display the resulting plot.

Method 3: Setting axis property in plt.style.use()

If you want to apply grid line removal globally to all plots within your script, you can use the plt.style.use() function with a custom style dictionary.

Here’s an example:

import matplotlib.pyplot as plt

plt.style.use({'axes.grid' : False})
plt.plot([0, 1], [0, 1])
plt.show()

As expected, this code results in a plot without any grid lines.

This method sets the axes.grid property to False using a style dictionary. This will apply the style to all plots in the script, making it unnecessary to disable grid lines individually.

Method 4: Use tick_params()

While not as straightforward, using tick_params() can also hide grid lines by setting grid visibility parameters for each axis.

Here’s an example:

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.plot([0, 1], [0, 1])
ax.tick_params(axis='both', which='both', length=0, gridOn=False) 
plt.show()

Once executed, you will see a plot with no grid lines.

This snippet utilizes ax.tick_params() to adjust the tick parameters. By setting gridOn to False, it hides the grid lines. The length=0 argument hides the tick marks as well.

Bonus One-Liner Method 5: Use axis('off')

To quickly turn off all axis lines, ticks, labels, and grid lines, axis('off') is a handy approach.

Here’s an example:

import matplotlib.pyplot as plt

plt.plot([0, 1], [0, 1])
plt.axis('off')
plt.show()

The output will be a clean plot free of any axis or grid lines.

This line of code is a one-stop-shop for those looking to clear all axis-related elements from a plot, including grid lines. It’s a sweeping change, so use it when a minimalistic plot is desired.

Summary/Discussion

  • Method 1: Using ax.grid(False). Strengths: Direct control over individual subplots. Weaknesses: Requires explicit handling of axes objects.
  • Method 2: Using plt.grid(False). Strengths: Simple usage with the pyplot interface. Weaknesses: Not well-suited for figures with multiple axes.
  • Method 3: Setting axis property in plt.style.use(). Strengths: Style consistency across all plots. Weaknesses: Less flexibility for individual plot customization.
  • Method 4: Use tick_params(). Strengths: Fine control over grid and tick parameters. Weaknesses: More complex syntax, can be overkill for simple tasks.
  • Method 5: Use axis('off'). Strengths: Fastest way to achieve a minimalist plot. Weaknesses: Remains unsuitable if you wish to keep labels or ticks.