How to show specific intervals of tick labels while maintaining the ticks

Question

I'm currently trying to plot a figure with a lot of ticks. It has ticks for each value from 0 to 50 resulting in packed tick labels that are merged making the plot quite messy. I made the ticks using

fig, ax = plt.subplots()
ax.set_xticks(np.arange(0,50))
ax.set_yticks(np.arange(0,50))

and hidden the tick labels using

ax.set_xticklabels([])
ax.set_yticklabels([])

However, the problem is that this hides all the tick labels, whereas I want some of the labels to remain so that I can track easily using the labels.

I've tried doing

ax.set_xticklabels(np.arange(0,50,5))

but this only resulted in labeling the first 10 ticks with inappropriate labels (which were range(0,50) with the interval of 5)

I'm hoping to figure out a way to show tick 'labels' with a interval of 5 (or any specific interval) while maintaining all the actual ticks (so that I can use them for grids).

@Julien that would only result the change in ticks which I don't want, where, what I do want are the changes in only the labels — Cody Chung, May 09 '18 at 05:30

score 3 · Accepted Answer · edited Jun 20 '20 at 09:12

Matplotlib gives you full control over the ticks and labels using locators and formatters. This is often preferable above setting the ticks and labels to some fixed values via set_xticks and set_xticklabels.
Two options to label only some of the ticks:

Using only major ticks

You may use a FuncFormatter to set the label either to the tick's value or to an empty string "" depending on some condition.

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker

fig, ax = plt.subplots()
ax.plot([0,49],[1,8])

ax.xaxis.set_major_locator(mticker.MultipleLocator())

def func(x, pos):
    if not x%5:
        return "{:g}".format(x)
    else:
        return ""
ax.xaxis.set_major_formatter(mticker.FuncFormatter(func))

plt.show()

Using minor ticks

One may use the major ticks to get labeled and the minor ticks to stay unlabeled. Optionally one may make the minor ticks as large as the major ticks.

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker

fig, ax = plt.subplots()
ax.plot([0,49],[1,8])

ax.xaxis.set_major_locator(mticker.MultipleLocator(5))
ax.xaxis.set_minor_locator(mticker.MultipleLocator(1))
ax.xaxis.set_minor_formatter(mticker.NullFormatter())

# optionally make the minorticks as large as the major ticks
#ax.tick_params(axis="x", which="both", length=4)

plt.show()

score 1 · Answer 2 · answered May 09 '18 at 02:27

What about creating your own trick:

import matplotlib.pyplot as plt
import numpy as np

names = ['aaa','aaa','aaa','aaa','aaa','aaa','aaa','aaa','aaa','aaa',
         'aaa','aaa','aaa','aaa','aaa','aaa','aaa','aaa','aaa','aaa',
         'aaa','aaa','aaa','aaa','aaa','aaa','aaa','aaa','aaa','aaa',
         'aaa','aaa','aaa','aaa','aaa','aaa','aaa','aaa','aaa','aaa',
         'aaa','aaa','aaa','aaa','aaa','aaa','aaa','aaa','aaa','aaa']
fig, ax = plt.subplots()
ax.set_xticks(np.arange(0,50))
ax.set_yticks(np.arange(0,50,5))
new_names=[]
for n,i in enumerate(names):
    if n%5==0:
        new_names.append(i)

    else:
        new_names.append('')

ax.set_xticklabels(new_names)
plt.show()

In summary, you create a new list containing only an element every 5, and the rest, are empty ''

I only applied for the x axis, but same idea could be done for y axis

just an idea...

Thanks! just what I wanted :) Although it would have been even better if they actually supported such features — Cody Chung, May 09 '18 at 07:01

How to show specific intervals of tick labels while maintaining the ticks

2 Answers2

Using only major ticks

Using minor ticks

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