Hide tick label values but keep axis labels

Question

I have this image:

plt.plot(sim_1['t'],sim_1['V'],'k')
plt.ylabel('V')
plt.xlabel('t')
plt.show()

I want to hide the numbers; if I use:

plt.axis('off')

...I get this image:

It also hide the labels, V and t. How can I keep the labels while hiding the values?

Answer 1

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([])

Answer 2

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

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

Answer 3

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

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

Answer 4

to remove tickmarks entirely use:

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

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

Answer 5

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?

Answer 6

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

Answer 7

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

Answer 8

With this is enough:

plt.xticks(color='w')