Develop Reference

matplotlib last tick label still visible [duplicate]

I have a semilogx plot and I would like to remove the xticks. I tried:
plt.gca().set_xticks([])
plt.xticks([])
ax.set_xticks([])
The grid disappears (ok), but small ticks (at the place of the main ticks) remain. How to remove them?

The plt.tick_params method is very useful for stuff like this. This code turns off major and minor ticks and removes the labels from the x-axis.
Note that there is also ax.tick_params for matplotlib.axes.Axes objects.
from matplotlib import pyplot as plt
plt.plot(range(10))
plt.tick_params(
axis='x', # changes apply to the x-axis
which='both', # both major and minor ticks are affected
bottom=False, # ticks along the bottom edge are off
top=False, # ticks along the top edge are off
labelbottom=False) # labels along the bottom edge are off
plt.show()
plt.savefig('plot')
plt.clf()

Not exactly what the OP was asking for, but a simple way to disable all axes lines, ticks and labels is to simply call:
plt.axis('off')

Alternatively, you can pass an empty tick position and label as
# for matplotlib.pyplot
# ---------------------
plt.xticks([], [])
# for axis object
# ---------------
# from Anakhand May 5 at 13:08
# for major ticks
ax.set_xticks([])
# for minor ticks
ax.set_xticks([], minor=True)

Here is an alternative solution that I found on the matplotlib mailing list:
import matplotlib.pylab as plt
x = range(1000)
ax = plt.axes()
ax.semilogx(x, x)
ax.xaxis.set_ticks_position('none')

There is a better, and simpler, solution than the one given by John Vinyard. Use NullLocator:
import matplotlib.pyplot as plt
plt.plot(range(10))
plt.gca().xaxis.set_major_locator(plt.NullLocator())
plt.show()
plt.savefig('plot')

Try this to remove the labels (but not the ticks):
import matplotlib.pyplot as plt
plt.setp( ax.get_xticklabels(), visible=False)
example

This snippet might help in removing the xticks only.
from matplotlib import pyplot as plt
plt.xticks([])
This snippet might help in removing the xticks and yticks both.
from matplotlib import pyplot as plt
plt.xticks([]),plt.yticks([])

Those of you looking for a short command to switch off all ticks and labels should be fine with
plt.tick_params(top=False, bottom=False, left=False, right=False,
labelleft=False, labelbottom=False)
which allows type bool for respective parameters since version matplotlib>=2.1.1
For custom tick settings, the docs are helpful:
https://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.tick_params.html

# remove all the ticks (both axes), and tick labels on the Y axis
plt.tick_params(top='off', bottom='off', left='off', right='off', labelleft='off', labelbottom='on')

Modify the following rc parameters by adding the commands to the script:
plt.rcParams['xtick.bottom'] = False
plt.rcParams['xtick.labelbottom'] = False
A sample matplotlibrc file is depicted in this section of the matplotlib documentation, which lists many other parameters like changing figure size, color of figure, animation settings, etc.

A simple solution to this problem is to set the color of the xticks to White or to whatever the background color is. This will hide the text of the xticks but not the xticks itself.
import matplotlib.pyplot as plt
plt.plot()
plt.xticks(color='white')
plt.show()
Result

Removing ticks when using grid with imshow matplotlib

In this question, they answer how to correctly use grid with imshow with matplotlib. I am trying to do the same as they do, but I want to remove all ticks (x and y). When I try to do it, it also eliminates the grid and I just the image displayed without grid and ticks. My code is:
fig, ax = plt.subplots()
data = np.random.rand(20,20)
ax.imshow(data)
ax.set_xticks(np.arange(20))
ax.set_xticklabels(np.arange(20))
ax.set_xticks(np.arange(20)+0.5, minor=True)
ax.grid(which='minor',color='w',axis='x',linewidth=6)
ax.axes.xaxis.set_visible(False)
ax.axes.yaxis.set_visible(False)
plt.show()
Does anyone how to remove the ticks while keeping the grid (along the x axis in my case)?

Removing the axes (via set_visible(False)) will also remove the grid.
However, there's a workaround setting both spines and tick marks/labels to be invisible individually:
fig, ax = plt.subplots()
data = np.random.rand(20,20)
ax.imshow(data)
ax.set_xticks(np.arange(20))
ax.set_xticklabels(np.arange(20))
ax.set_xticks(np.arange(20)+0.5, minor=True)
ax.grid(which='minor',color='w',axis='x',linewidth=6)
# set axis spines (the box around the plot) to be invisible
plt.setp(ax.spines.values(), alpha = 0)
# set both tick marks and tick labels to size 0
ax.tick_params(which = 'both', size = 0, labelsize = 0)
plt.show()
Gives you output as:
Note, you might need to adjust xlim/ylim and grid parameters to fit your needs.

This is not perfect, but you can just set the tick label as an empty list.
ax.axes.get_xaxis().set_ticks([])
ax.axes.get_yaxis().set_ticks([])
Only the minor xticks, used in the grid, remain.

How to stop x labels from displaying after a certain value

I'm having the hardest time achieving the following:
I need to stop the x labels from showing after the vertical dashed line seen in the image:
Basically, I want to eliminate the 5 in this example.
I successfully stopped the ticks with the condition placed on "set_ticks", but the labels keep displaying.
My code:
ax2 = plt.subplot()
ax2.pcolormesh(xext, ye, Zext, cmap='hot')
ax2.set_xticks([a for a in xext if a<myval], minor=True)
ax2.axvline(myval, linestyle='--', color='white')
plt.show()
A solution like writing a list of [1,2,3,4] would not help me.
I need this to work for a large number of examples where all I know is the limit value, or myval from the code above.
(I am restating and narrowing down a question I posted before, now deleted.)

You only changed the minor ticks (the very short lines) on the x-axis. The major ticks also should be changed. ax.get_xticks() gives a list of the current ticks, which you can filter and apply again:
import matplotlib.pyplot as plt
import numpy as np
fig, ax2 = plt.subplots()
xext = np.arange(9.1, step=.1)
ye = np.arange(6)
zext = np.random.randn(len(ye) - 1, len(xext) - 1).cumsum(axis=1)
zext -= zext.mean(axis=1, keepdims=True)
ax2.pcolormesh(xext, ye, zext, cmap='hot')
myval = 6.28
ax2.set_xticks([a for a in xext if a < myval], minor=True)
xticks = ax2.get_xticks()
ax2.set_xticks([a for a in xticks if a < myval])
ax2.axvline(myval, linestyle='--', color='white')
plt.show()

x axis label disappearing in matplotlib and basic plotting in python

I am new to matplotlib, and I am finding it very confusing. I have spent quite a lot of time on the matplotlib tutorial website, but I still cannot really understand how to build a figure from scratch. To me, this means doing everything manually... not using the plt.plot() function, but always setting figure, axis handles.
Can anyone explain how to set up a figure from the ground up?
Right now, I have this code to generate a double y-axis plot. But my xlabels are disappearing and I dont' know why
fig, ax1 = plt.subplots()
ax1.plot(yearsTotal,timeseries_data1,'r-')
ax1.set_ylabel('Windspeed [m/s]')
ax1.tick_params('y',colors='r')
ax2 = ax1.twinx()
ax2.plot(yearsTotal,timeseries_data2,'b-')
ax2.set_xticks(np.arange(min(yearsTotal),max(yearsTotal)+1))
ax2.set_xticklabels(ax1.xaxis.get_majorticklabels(), rotation=90)
ax2.set_ylabel('Open water duration [days]')
ax2.tick_params('y',colors='b')
plt.title('My title')
fig.tight_layout()
plt.savefig('plots/my_figure.png',bbox_inches='tight')
plt.show()

Because you are using a twinx, it makes sense to operate only on the original axes (ax1).
Further, the ticklabels are not defined at the point where you call ax1.xaxis.get_majorticklabels().
If you want to set the ticks and ticklabels manually, you can use your own data to do so (although I wouldn't know why you'd prefer this over using the automatic labeling) by specifying a list or array
ticks = np.arange(min(yearsTotal),max(yearsTotal)+1)
ax1.set_xticks(ticks)
ax1.set_xticklabels(ticks)
Since the ticklabels are the same as the tickpositions here, you may also just do
ax1.set_xticks(np.arange(min(yearsTotal),max(yearsTotal)+1))
plt.setp(ax1.get_xticklabels(), rotation=70)
Complete example:
import matplotlib.pyplot as plt
import numpy as np; np.random.seed(1)
yearsTotal = np.arange(1977, 1999)
timeseries_data1 = np.cumsum(np.random.normal(size=len(yearsTotal)))+5
timeseries_data2 = np.cumsum(np.random.normal(size=len(yearsTotal)))+20
fig, ax1 = plt.subplots()
ax1.plot(yearsTotal,timeseries_data1,'r-')
ax1.set_ylabel('Windspeed [m/s]')
ax1.tick_params('y',colors='r')
ax1.set_xticks(np.arange(min(yearsTotal),max(yearsTotal)+1))
plt.setp(ax1.get_xticklabels(), rotation=70)
ax2 = ax1.twinx()
ax2.plot(yearsTotal,timeseries_data2,'b-')
ax2.set_ylabel('Open water duration [days]')
ax2.tick_params('y',colors='b')
plt.title('My title')
fig.tight_layout()
plt.show()

Based on your code, it is not disappear, it is set (overwrite) by these two functions:
ax2.set_xticks(np.arange(min(yearsTotal),max(yearsTotal)+1))
ax2.set_xticklabels(ax1.xaxis.get_majorticklabels(), rotation=90)
set_xticks() on the axes will set the locations and set_xticklabels() will set the xtick labels with list of strings labels.

Hiding axis text in matplotlib plots

I'm trying to plot a figure without tickmarks or numbers on either of the axes (I use axes in the traditional sense, not the matplotlib nomenclature!). An issue I have come across is where matplotlib adjusts the x(y)ticklabels by subtracting a value N, then adds N at the end of the axis.
This may be vague, but the following simplified example highlights the issue, with '6.18' being the offending value of N:
import matplotlib.pyplot as plt
import random
prefix = 6.18
rx = [prefix+(0.001*random.random()) for i in arange(100)]
ry = [prefix+(0.001*random.random()) for i in arange(100)]
plt.plot(rx,ry,'ko')
frame1 = plt.gca()
for xlabel_i in frame1.axes.get_xticklabels():
xlabel_i.set_visible(False)
xlabel_i.set_fontsize(0.0)
for xlabel_i in frame1.axes.get_yticklabels():
xlabel_i.set_fontsize(0.0)
xlabel_i.set_visible(False)
for tick in frame1.axes.get_xticklines():
tick.set_visible(False)
for tick in frame1.axes.get_yticklines():
tick.set_visible(False)
plt.show()
The three things I would like to know are:
How to turn off this behaviour in the first place (although in most cases it is useful, it is not always!) I have looked through matplotlib.axis.XAxis and cannot find anything appropriate
How can I make N disappear (i.e. X.set_visible(False))
Is there a better way to do the above anyway? My final plot would be 4x4 subplots in a figure, if that is relevant.

Instead of hiding each element, you can hide the whole axis:
frame1.axes.get_xaxis().set_visible(False)
frame1.axes.get_yaxis().set_visible(False)
Or, you can set the ticks to an empty list:
frame1.axes.get_xaxis().set_ticks([])
frame1.axes.get_yaxis().set_ticks([])
In this second option, you can still use plt.xlabel() and plt.ylabel() to add labels to the axes.

If you want to hide just the axis text keeping the grid lines:
frame1 = plt.gca()
frame1.axes.xaxis.set_ticklabels([])
frame1.axes.yaxis.set_ticklabels([])
Doing set_visible(False) or set_ticks([]) will also hide the grid lines.

If you are like me and don't always retrieve the axes, ax, when plotting the figure, then a simple solution would be to do
plt.xticks([])
plt.yticks([])

I've colour coded this figure to ease the process.
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
You can have full control over the figure using these commands, to complete the answer I've add also the control over the spines:
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
# X AXIS -BORDER
ax.spines['bottom'].set_visible(False)
# BLUE
ax.set_xticklabels([])
# RED
ax.set_xticks([])
# RED AND BLUE TOGETHER
ax.axes.get_xaxis().set_visible(False)
# Y AXIS -BORDER
ax.spines['left'].set_visible(False)
# YELLOW
ax.set_yticklabels([])
# GREEN
ax.set_yticks([])
# YELLOW AND GREEN TOGHETHER
ax.axes.get_yaxis().set_visible(False)

I was not actually able to render an image without borders or axis data based on any of the code snippets here (even the one accepted at the answer). After digging through some API documentation, I landed on this code to render my image
plt.axis('off')
plt.tick_params(axis='both', left=False, top=False, right=False, bottom=False, labelleft=False, labeltop=False, labelright=False, labelbottom=False)
plt.savefig('foo.png', dpi=100, bbox_inches='tight', pad_inches=0.0)
I used the tick_params call to basically shut down any extra information that might be rendered and I have a perfect graph in my output file.

Somewhat of an old thread but, this seems to be a faster method using the latest version of matplotlib:
set the major formatter for the x-axis
ax.xaxis.set_major_formatter(plt.NullFormatter())

One trick could be setting the color of tick labels as white to hide it!
plt.xticks(color='w')
plt.yticks(color='w')
or to be more generalized (#Armin Okić), you can set it as "None".

When using the object oriented API, the Axes object has two useful methods for removing the axis text, set_xticklabels() and set_xticks().
Say you create a plot using
fig, ax = plt.subplots(1)
ax.plot(x, y)
If you simply want to remove the tick labels, you could use
ax.set_xticklabels([])
or to remove the ticks completely, you could use
ax.set_xticks([])
These methods are useful for specifying exactly where you want the ticks and how you want them labeled. Passing an empty list results in no ticks, or no labels, respectively.

You could simply set xlabel to None, straight in your axis. Below an working example using seaborn
from matplotlib import pyplot as plt
import seaborn as sns
tips = sns.load_dataset("tips")
ax = sns.boxplot(x="day", y="total_bill", data=tips)
ax.set(xlabel=None)
plt.show()

Just do this in case you have subplots
fig, axs = plt.subplots(1, 2, figsize=(16, 8))
ax[0].set_yticklabels([]) # x-axis
ax[0].set_xticklabels([]) # y-axis