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Hide tick label values but keep axis labels

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How do I hide tick labels?

By using the method xticks() and yticks() you can disable the ticks and tick labels from both the x-axis and y-axis. In the above example, we use plt. xticks([]) method to invisible both the ticks and labels on the x-axis and set the ticks empty.

How do I get rid of Xlabel in matplotlib?

To hide or remove X-axis labels, use set(xlabel=None). To display the figure, use show() method.


If you use the matplotlib object-oriented approach, this is a simple task using ax.set_xticklabels() and ax.set_yticklabels(). Here we can just set them to an empty list to remove any labels:

import matplotlib.pyplot as plt

# Create Figure and Axes instances
fig,ax = plt.subplots(1)

# Make your plot, set your axes labels
ax.plot(sim_1['t'],sim_1['V'],'k')
ax.set_ylabel('V')
ax.set_xlabel('t')

# Turn off tick labels
ax.set_yticklabels([])
ax.set_xticklabels([])

plt.show()

If you also want to remove the tick marks as well as the labels, you can use ax.set_xticks() and ax.set_yticks() and set those to an empty list as well:

ax.set_xticks([])
ax.set_yticks([])

Without a subplots, you can universally remove the ticks like this:

plt.xticks([])
plt.yticks([])

This works great. Just paste this before plt.show():

plt.gca().axes.get_yaxis().set_visible(False)

Boom.


to remove tickmarks entirely use:

ax.set_yticks([])
ax.set_xticks([])

otherwise ax.set_yticklabels([]) and ax.set_xticklabels([]) will keep tickmarks.


plt.gca().axes.yaxis.set_ticklabels([])

enter image description here


Not sure this is the best way, but you can certainly replace the tick labels like this:

import matplotlib.pyplot as plt
x = range(10)
y = range(10)
plt.plot(x,y)
plt.xticks(x," ")
plt.show()

In Python 3.4 this generates a simple line plot with no tick labels on the x-axis. A simple example is here: http://matplotlib.org/examples/ticks_and_spines/ticklabels_demo_rotation.html

This related question also has some better suggestions: Hiding axis text in matplotlib plots

I'm new to python. Your mileage may vary in earlier versions. Maybe others can help?


This also works.

fig, ax = plt.subplots()
ax.yaxis.set_major_locator(plt.NullLocator())
ax.xaxis.set_major_formatter(plt.NullFormatter())

see this book for nice tips for customizing ticks https://jakevdp.github.io/PythonDataScienceHandbook/04.10-customizing-ticks.html