I am having an issue trying to get my date ticks rotated in matplotlib. A small sample program is below. If I try to rotate the ticks at the end, the ticks do not get rotated. If I try to rotate the ticks as shown under the comment 'crashes', then matplot lib crashes.
This only happens if the x-values are dates. If I replaces the variable dates with the variable t in the call to avail_plot, the xticks(rotation=70) call works just fine inside avail_plot.
Any ideas?
import numpy as np
import matplotlib.pyplot as plt
import datetime as dt
def avail_plot(ax, x, y, label, lcolor):
ax.plot(x,y,'b')
ax.set_ylabel(label, rotation='horizontal', color=lcolor)
ax.get_yaxis().set_ticks([])
#crashes
#plt.xticks(rotation=70)
ax2 = ax.twinx()
ax2.plot(x, [1 for a in y], 'b')
ax2.get_yaxis().set_ticks([])
ax2.set_ylabel('testing')
f, axs = plt.subplots(2, sharex=True, sharey=True)
t = np.arange(0.01, 5, 1)
s1 = np.exp(t)
start = dt.datetime.now()
dates=[]
for val in t:
next_val = start + dt.timedelta(0,val)
dates.append(next_val)
start = next_val
avail_plot(axs[0], dates, s1, 'testing', 'green')
avail_plot(axs[1], dates, s1, 'testing2', 'red')
plt.subplots_adjust(hspace=0, bottom=0.3)
plt.yticks([0.5,],("",""))
#doesn't crash, but does not rotate the xticks
#plt.xticks(rotation=70)
plt.show()
If you prefer a non-object-oriented approach, move plt.xticks(rotation=70) to right before the two avail_plot calls, eg
plt.xticks(rotation=70)
avail_plot(axs[0], dates, s1, 'testing', 'green')
avail_plot(axs[1], dates, s1, 'testing2', 'red')
This sets the rotation property before setting up the labels. Since you have two axes here, plt.xticks gets confused after you've made the two plots. At the point when plt.xticks doesn't do anything, plt.gca() does not give you the axes you want to modify, and so plt.xticks, which acts on the current axes, is not going to work.
For an object-oriented approach not using plt.xticks, you can use
plt.setp( axs[1].xaxis.get_majorticklabels(), rotation=70 )
after the two avail_plot calls. This sets the rotation on the correct axes specifically.
Solution works for matplotlib 2.1+
There exists an axes method tick_params that can change tick properties. It also exists as an axis method as set_tick_params
ax.tick_params(axis='x', rotation=45)
Or
ax.xaxis.set_tick_params(rotation=45)
As a side note, the current solution mixes the stateful interface (using pyplot) with the object-oriented interface by using the command plt.xticks(rotation=70). Since the code in the question uses the object-oriented approach, it's best to stick to that approach throughout. The solution does give a good explicit solution with plt.setp( axs[1].xaxis.get_majorticklabels(), rotation=70 )
An easy solution which avoids looping over the ticklabes is to just use
fig.autofmt_xdate()
This command automatically rotates the xaxis labels and adjusts their position. The default values are a rotation angle 30° and horizontal alignment "right". But they can be changed in the function call
fig.autofmt_xdate(bottom=0.2, rotation=30, ha='right')
The additional bottom argument is equivalent to setting plt.subplots_adjust(bottom=bottom), which allows to set the bottom axes padding to a larger value to host the rotated ticklabels.
So basically here you have all the settings you need to have a nice date axis in a single command.
A good example can be found on the matplotlib page.
Another way to applyhorizontalalignment and rotation to each tick label is doing a for loop over the tick labels you want to change:
import numpy as np
import matplotlib.pyplot as plt
import datetime as dt
now = dt.datetime.now()
hours = [now + dt.timedelta(minutes=x) for x in range(0,24*60,10)]
days = [now + dt.timedelta(days=x) for x in np.arange(0,30,1/4.)]
hours_value = np.random.random(len(hours))
days_value = np.random.random(len(days))
fig, axs = plt.subplots(2)
fig.subplots_adjust(hspace=0.75)
axs[0].plot(hours,hours_value)
axs[1].plot(days,days_value)
for label in axs[0].get_xmajorticklabels() + axs[1].get_xmajorticklabels():
label.set_rotation(30)
label.set_horizontalalignment("right")
And here is an example if you want to control the location of major and minor ticks:
import numpy as np
import matplotlib.pyplot as plt
import datetime as dt
fig, axs = plt.subplots(2)
fig.subplots_adjust(hspace=0.75)
now = dt.datetime.now()
hours = [now + dt.timedelta(minutes=x) for x in range(0,24*60,10)]
days = [now + dt.timedelta(days=x) for x in np.arange(0,30,1/4.)]
axs[0].plot(hours,np.random.random(len(hours)))
x_major_lct = mpl.dates.AutoDateLocator(minticks=2,maxticks=10, interval_multiples=True)
x_minor_lct = matplotlib.dates.HourLocator(byhour = range(0,25,1))
x_fmt = matplotlib.dates.AutoDateFormatter(x_major_lct)
axs[0].xaxis.set_major_locator(x_major_lct)
axs[0].xaxis.set_minor_locator(x_minor_lct)
axs[0].xaxis.set_major_formatter(x_fmt)
axs[0].set_xlabel("minor ticks set to every hour, major ticks start with 00:00")
axs[1].plot(days,np.random.random(len(days)))
x_major_lct = mpl.dates.AutoDateLocator(minticks=2,maxticks=10, interval_multiples=True)
x_minor_lct = matplotlib.dates.DayLocator(bymonthday = range(0,32,1))
x_fmt = matplotlib.dates.AutoDateFormatter(x_major_lct)
axs[1].xaxis.set_major_locator(x_major_lct)
axs[1].xaxis.set_minor_locator(x_minor_lct)
axs[1].xaxis.set_major_formatter(x_fmt)
axs[1].set_xlabel("minor ticks set to every day, major ticks show first day of month")
for label in axs[0].get_xmajorticklabels() + axs[1].get_xmajorticklabels():
label.set_rotation(30)
label.set_horizontalalignment("right")
Simply use
ax.set_xticklabels(label_list, rotation=45)
I am clearly late but there is an official example which uses
plt.setp(ax.get_xticklabels(), rotation=45, ha="right", rotation_mode="anchor")
to rotate the labels while keeping them correctly aligned with the ticks, which is both clean and easy.
Ref: https://matplotlib.org/stable/gallery/images_contours_and_fields/image_annotated_heatmap.html
Related
I can't figure out how to rotate the text on the X Axis. Its a time stamp, so as the number of samples increase, they get closer and closer until they overlap. I'd like to rotate the text 90 degrees so as the samples get closer together, they aren't overlapping.
Below is what I have, it works fine with the exception that I can't figure out how to rotate the X axis text.
import sys
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import datetime
font = {'family' : 'normal',
'weight' : 'bold',
'size' : 8}
matplotlib.rc('font', **font)
values = open('stats.csv', 'r').readlines()
time = [datetime.datetime.fromtimestamp(float(i.split(',')[0].strip())) for i in values[1:]]
delay = [float(i.split(',')[1].strip()) for i in values[1:]]
plt.plot(time, delay)
plt.grid(b='on')
plt.savefig('test.png')
This works for me:
plt.xticks(rotation=90)
Many "correct" answers here but I'll add one more since I think some details are left out of several. The OP asked for 90 degree rotation but I'll change to 45 degrees because when you use an angle that isn't zero or 90, you should change the horizontal alignment as well; otherwise your labels will be off-center and a bit misleading (and I'm guessing many people who come here want to rotate axes to something other than 90).
Easiest / Least Code
Option 1
plt.xticks(rotation=45, ha='right')
As mentioned previously, that may not be desirable if you'd rather take the Object Oriented approach.
Option 2
Another fast way (it's intended for date objects but seems to work on any label; doubt this is recommended though):
fig.autofmt_xdate(rotation=45)
fig you would usually get from:
fig = plt.gcf()
fig = plt.figure()
fig, ax = plt.subplots()
fig = ax.figure
Object-Oriented / Dealing directly with ax
Option 3a
If you have the list of labels:
labels = ['One', 'Two', 'Three']
ax.set_xticks([1, 2, 3])
ax.set_xticklabels(labels, rotation=45, ha='right')
In later versions of Matplotlib (3.5+), you can just use set_xticks alone:
ax.set_xticks([1, 2, 3], labels, rotation=45, ha='right')
Option 3b
If you want to get the list of labels from the current plot:
# Unfortunately you need to draw your figure first to assign the labels,
# otherwise get_xticklabels() will return empty strings.
plt.draw()
ax.set_xticks(ax.get_xticks())
ax.set_xticklabels(ax.get_xticklabels(), rotation=45, ha='right')
As above, in later versions of Matplotlib (3.5+), you can just use set_xticks alone:
ax.set_xticks(ax.get_xticks(), ax.get_xticklabels(), rotation=45, ha='right')
Option 4
Similar to above, but loop through manually instead.
for label in ax.get_xticklabels():
label.set_rotation(45)
label.set_ha('right')
Option 5
We still use pyplot (as plt) here but it's object-oriented because we're changing the property of a specific ax object.
plt.setp(ax.get_xticklabels(), rotation=45, ha='right')
Option 6
This option is simple, but AFAIK you can't set label horizontal align this way so another option might be better if your angle is not 90.
ax.tick_params(axis='x', labelrotation=45)
Edit:
There's discussion of this exact "bug" but a fix hasn't been released (as of 3.4.0):
https://github.com/matplotlib/matplotlib/issues/13774
Easy way
As described here, there is an existing method in the matplotlib.pyplot figure class that automatically rotates dates appropriately for you figure.
You can call it after you plot your data (i.e.ax.plot(dates,ydata) :
fig.autofmt_xdate()
If you need to format the labels further, checkout the above link.
Non-datetime objects
As per languitar's comment, the method I suggested for non-datetime xticks would not update correctly when zooming, etc. If it's not a datetime object used as your x-axis data, you should follow Tommy's answer:
for tick in ax.get_xticklabels():
tick.set_rotation(45)
Try pyplot.setp. I think you could do something like this:
x = range(len(time))
plt.xticks(x, time)
locs, labels = plt.xticks()
plt.setp(labels, rotation=90)
plt.plot(x, delay)
Appart from
plt.xticks(rotation=90)
this is also possible:
plt.xticks(rotation='vertical')
I came up with a similar example. Again, the rotation keyword is.. well, it's key.
from pylab import *
fig = figure()
ax = fig.add_subplot(111)
ax.bar( [0,1,2], [1,3,5] )
ax.set_xticks( [ 0.5, 1.5, 2.5 ] )
ax.set_xticklabels( ['tom','dick','harry'], rotation=45 ) ;
If you want to apply rotation on the axes object, the easiest way is using tick_params. For example.
ax.tick_params(axis='x', labelrotation=90)
Matplotlib documentation reference here.
This is useful when you have an array of axes as returned by plt.subplots, and it is more convenient than using set_xticks because in that case you need to also set the tick labels, and also more convenient that those that iterate over the ticks (for obvious reasons)
If using plt:
plt.xticks(rotation=90)
In case of using pandas or seaborn to plot, assuming ax as axes for the plot:
ax.set_xticklabels(ax.get_xticklabels(), rotation=90)
Another way of doing the above:
for tick in ax.get_xticklabels():
tick.set_rotation(45)
My answer is inspired by cjohnson318's answer, but I didn't want to supply a hardcoded list of labels; I wanted to rotate the existing labels:
for tick in ax.get_xticklabels():
tick.set_rotation(45)
The simplest solution is to use:
plt.xticks(rotation=XX)
but also
# Tweak spacing to prevent clipping of tick-labels
plt.subplots_adjust(bottom=X.XX)
e.g for dates I used rotation=45 and bottom=0.20 but you can do some test for your data
import pylab as pl
pl.xticks(rotation = 90)
To rotate the x-axis label to 90 degrees
for tick in ax.get_xticklabels():
tick.set_rotation(45)
It will depend on what are you plotting.
import matplotlib.pyplot as plt
x=['long_text_for_a_label_a',
'long_text_for_a_label_b',
'long_text_for_a_label_c']
y=[1,2,3]
myplot = plt.plot(x,y)
for item in myplot.axes.get_xticklabels():
item.set_rotation(90)
For pandas and seaborn that give you an Axes object:
df = pd.DataFrame(x,y)
#pandas
myplot = df.plot.bar()
#seaborn
myplotsns =sns.barplot(y='0', x=df.index, data=df)
# you can get xticklabels without .axes cause the object are already a
# isntance of it
for item in myplot.get_xticklabels():
item.set_rotation(90)
If you need to rotate labels you may need change the font size too, you can use font_scale=1.0 to do that.
I'm having with my xticks on my plot.
I have an hh:mm:ss format data on my x vector, but the xticks label are just eating up space on my x vector.
I'm trying to use only major xticks which would show the x vector label on 5 minutes basis.
but, the label not showing correctly.
right now this is the code that i wrote:
# -*- coding: utf-8 -*-
from os import listdir
from os.path import isfile, join
import pandas as pd
from Common import common as comm
from matplotlib.font_manager import FontProperties
import matplotlib.pyplot as plt
fp = FontProperties(fname="../templates/fonts/msgothic.ttc")
config = comm.configRead()
commonConf = comm.getCommonConfig(config)
peopleBhvConf = comm.getPeopleBhvConf(config)
files = [f for f in listdir(commonConf['resultFilePath']) if isfile(join(commonConf['resultFilePath'], f))]
waitTimeGraphInput = [s for s in files if peopleBhvConf['resultFileName'] in s]
waitTimeGraphFile = commonConf['inputFilePath'] + waitTimeGraphInput[0]
waitTimeGraph = pd.read_csv(waitTimeGraphFile)
# Create data
N = len(waitTimeGraph.index)
x = waitTimeGraph['ホール入時間']
y = waitTimeGraph['滞留時間(出-入sec)']
xTicks = pd.date_range(min(x), max(x), freq="5min")
fig, ax = plt.subplots()
ax.scatter(x, y)
ax.set_xticklabels(xTicks, rotation='vertical')
plt.axhline(y=100, xmin=min(x), xmax=max(x), linewidth=2, color = 'red')
plt.setp(ax.get_xticklabels(), visible=True, rotation=30, ha='right')
plt.savefig(commonConf['resultFilePath'] + '1人1人の待ち時間分布.png')
plt.show()
and this is the result:
as you can see, the labels are still being printed only on the front of my plotting.
I'm expecting it would being printed on my major xticks position only.
The problem
If I understand correctly what is going on, xTicks array is shorter than x, am I right? If so, this is the issue.
I don't see in your code where you set the tick position, but I guess you are showing all of them, one per each element of x. But since you set the tick labels manually with ax.set_xticklabels(xTicks, rotation='vertical'), matplotlib has no way to know at which ticks those labels should go, hence it fills the first available ticks, and if there are more ticks, they are left without labels.
If you were able to read the labes, you would see that the written dates do not correspond to the labelled positions on the axis.
How to fix it
The general rule, be sure when you set tick labels manually, that the array containing the label has the same length of the array of the ticks. Add empty strings for the ticks where you do not want to have a labels.
However, since you spoke of major ticks and minor ticks, I show you how to set them in your case, where you have dates on the x axis.
Drop the xTicks, is not needed. Don't set the tick labels manually, hence don't use ax.set_xticklabels().
Your code should be:
fig, ax = plt.subplots()
ax.scatter(x, y)
plt.axhline(y=100, xmin=min(x), xmax=max(x), linewidth=2, color = 'red')
ax.xaxis.set_major_locator(MinuteLocator(interval=5))
ax.xaxis.set_minor_locator(MinuteLocator(interval=1))
ax.xaxis.set_major_formatter(DateFormatter('%H:%M:%S'))
plt.setp(ax.get_xticklabels(), visible=True, rotation=30, ha='right')
plt.savefig(commonConf['resultFilePath'] + '1人1人の待ち時間分布.png')
Remember to import the locator and formatter:
from matplotlib.dates import MinuteLocator, DateFormatter
A brief explanation: MinuteLocator finds each minute interval in your x axis and place a tick. The parameter interval allows you to set a tick each N minutes. So in the above code a major tick is placed each 5 minutes, a minor tick each minute.
DateFormatter simply format the date accordingly to the string (here I choose the format hour, minute, second). Note that no formatter has been set for minor ticks, so by default matplotlib uses the null formatter (no labels for minor ticks).
Here the documentation on the dates module of matplotlib.
To give you an idea of the result, here is an image I created using the code above with random data (just look at the x axis).
I am attempting to align two sets of separate y-axis using python and matplotlib, and am running into behavior I don't understand. Here is my code so far:
import matplotlib.pyplot as mplot
import numpy as np
fig = mplot.figure()
ax1 = fig.add_subplot(111)
t = np.arange(1, 4, 1)
s1 = np.exp(t)
ax2 = ax1.twinx()
ax1.semilogx(t, s1)
ax2.set_yticks(2*ax1.get_yticks())
mplot.show()
This produces the expected result (from http://postimg.org/image/qowrjnnr5/):
however, changing the definition of t to
t = np.arrange(1, 3, 1)
produces the result (http://postimg.org/image/swanojt0b):
where you can see that the y axis ticks on the right side are off-shifted.
What am I missing in order to prevent this issue?
Thanks!
The two y axes do not have the same limits: in one case you fluke the same lower value in the automatic range calculation while in the other you don't. If you define one yaxis range in terms of the other, I think you achieve what you want:
lim1 = ax1.get_ylim()
lim2 = (lim1[0]*2, lim1[1] *2)
ax2.set_ylim(lim2)
(and if you don't explicitly set the ax2 yticks then ticks will still get rendered if you move beyond the original range in interactive mode).
I can't figure out how to rotate the text on the X Axis. Its a time stamp, so as the number of samples increase, they get closer and closer until they overlap. I'd like to rotate the text 90 degrees so as the samples get closer together, they aren't overlapping.
Below is what I have, it works fine with the exception that I can't figure out how to rotate the X axis text.
import sys
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import datetime
font = {'family' : 'normal',
'weight' : 'bold',
'size' : 8}
matplotlib.rc('font', **font)
values = open('stats.csv', 'r').readlines()
time = [datetime.datetime.fromtimestamp(float(i.split(',')[0].strip())) for i in values[1:]]
delay = [float(i.split(',')[1].strip()) for i in values[1:]]
plt.plot(time, delay)
plt.grid(b='on')
plt.savefig('test.png')
This works for me:
plt.xticks(rotation=90)
Many "correct" answers here but I'll add one more since I think some details are left out of several. The OP asked for 90 degree rotation but I'll change to 45 degrees because when you use an angle that isn't zero or 90, you should change the horizontal alignment as well; otherwise your labels will be off-center and a bit misleading (and I'm guessing many people who come here want to rotate axes to something other than 90).
Easiest / Least Code
Option 1
plt.xticks(rotation=45, ha='right')
As mentioned previously, that may not be desirable if you'd rather take the Object Oriented approach.
Option 2
Another fast way (it's intended for date objects but seems to work on any label; doubt this is recommended though):
fig.autofmt_xdate(rotation=45)
fig you would usually get from:
fig = plt.gcf()
fig = plt.figure()
fig, ax = plt.subplots()
fig = ax.figure
Object-Oriented / Dealing directly with ax
Option 3a
If you have the list of labels:
labels = ['One', 'Two', 'Three']
ax.set_xticks([1, 2, 3])
ax.set_xticklabels(labels, rotation=45, ha='right')
In later versions of Matplotlib (3.5+), you can just use set_xticks alone:
ax.set_xticks([1, 2, 3], labels, rotation=45, ha='right')
Option 3b
If you want to get the list of labels from the current plot:
# Unfortunately you need to draw your figure first to assign the labels,
# otherwise get_xticklabels() will return empty strings.
plt.draw()
ax.set_xticks(ax.get_xticks())
ax.set_xticklabels(ax.get_xticklabels(), rotation=45, ha='right')
As above, in later versions of Matplotlib (3.5+), you can just use set_xticks alone:
ax.set_xticks(ax.get_xticks(), ax.get_xticklabels(), rotation=45, ha='right')
Option 4
Similar to above, but loop through manually instead.
for label in ax.get_xticklabels():
label.set_rotation(45)
label.set_ha('right')
Option 5
We still use pyplot (as plt) here but it's object-oriented because we're changing the property of a specific ax object.
plt.setp(ax.get_xticklabels(), rotation=45, ha='right')
Option 6
This option is simple, but AFAIK you can't set label horizontal align this way so another option might be better if your angle is not 90.
ax.tick_params(axis='x', labelrotation=45)
Edit:
There's discussion of this exact "bug" but a fix hasn't been released (as of 3.4.0):
https://github.com/matplotlib/matplotlib/issues/13774
Easy way
As described here, there is an existing method in the matplotlib.pyplot figure class that automatically rotates dates appropriately for you figure.
You can call it after you plot your data (i.e.ax.plot(dates,ydata) :
fig.autofmt_xdate()
If you need to format the labels further, checkout the above link.
Non-datetime objects
As per languitar's comment, the method I suggested for non-datetime xticks would not update correctly when zooming, etc. If it's not a datetime object used as your x-axis data, you should follow Tommy's answer:
for tick in ax.get_xticklabels():
tick.set_rotation(45)
Try pyplot.setp. I think you could do something like this:
x = range(len(time))
plt.xticks(x, time)
locs, labels = plt.xticks()
plt.setp(labels, rotation=90)
plt.plot(x, delay)
Appart from
plt.xticks(rotation=90)
this is also possible:
plt.xticks(rotation='vertical')
I came up with a similar example. Again, the rotation keyword is.. well, it's key.
from pylab import *
fig = figure()
ax = fig.add_subplot(111)
ax.bar( [0,1,2], [1,3,5] )
ax.set_xticks( [ 0.5, 1.5, 2.5 ] )
ax.set_xticklabels( ['tom','dick','harry'], rotation=45 ) ;
If you want to apply rotation on the axes object, the easiest way is using tick_params. For example.
ax.tick_params(axis='x', labelrotation=90)
Matplotlib documentation reference here.
This is useful when you have an array of axes as returned by plt.subplots, and it is more convenient than using set_xticks because in that case you need to also set the tick labels, and also more convenient that those that iterate over the ticks (for obvious reasons)
If using plt:
plt.xticks(rotation=90)
In case of using pandas or seaborn to plot, assuming ax as axes for the plot:
ax.set_xticklabels(ax.get_xticklabels(), rotation=90)
Another way of doing the above:
for tick in ax.get_xticklabels():
tick.set_rotation(45)
My answer is inspired by cjohnson318's answer, but I didn't want to supply a hardcoded list of labels; I wanted to rotate the existing labels:
for tick in ax.get_xticklabels():
tick.set_rotation(45)
The simplest solution is to use:
plt.xticks(rotation=XX)
but also
# Tweak spacing to prevent clipping of tick-labels
plt.subplots_adjust(bottom=X.XX)
e.g for dates I used rotation=45 and bottom=0.20 but you can do some test for your data
import pylab as pl
pl.xticks(rotation = 90)
To rotate the x-axis label to 90 degrees
for tick in ax.get_xticklabels():
tick.set_rotation(45)
It will depend on what are you plotting.
import matplotlib.pyplot as plt
x=['long_text_for_a_label_a',
'long_text_for_a_label_b',
'long_text_for_a_label_c']
y=[1,2,3]
myplot = plt.plot(x,y)
for item in myplot.axes.get_xticklabels():
item.set_rotation(90)
For pandas and seaborn that give you an Axes object:
df = pd.DataFrame(x,y)
#pandas
myplot = df.plot.bar()
#seaborn
myplotsns =sns.barplot(y='0', x=df.index, data=df)
# you can get xticklabels without .axes cause the object are already a
# isntance of it
for item in myplot.get_xticklabels():
item.set_rotation(90)
If you need to rotate labels you may need change the font size too, you can use font_scale=1.0 to do that.
In a matplotlib figure, how can I make the font size for the tick labels using ax1.set_xticklabels() smaller?
Further, how can one rotate it from horizontal to vertical?
There is a simpler way actually. I just found:
import matplotlib.pyplot as plt
# We prepare the plot
fig, ax = plt.subplots()
# We change the fontsize of minor ticks label
ax.tick_params(axis='both', which='major', labelsize=10)
ax.tick_params(axis='both', which='minor', labelsize=8)
This only answers to the size of label part of your question though.
To specify both font size and rotation at the same time, try this:
plt.xticks(fontsize=14, rotation=90)
Please note that newer versions of MPL have a shortcut for this task. An example is shown in the other answer to this question: https://stackoverflow.com/a/11386056/42346
The code below is for illustrative purposes and may not necessarily be optimized.
import matplotlib.pyplot as plt
import numpy as np
def xticklabels_example():
fig = plt.figure()
x = np.arange(20)
y1 = np.cos(x)
y2 = (x**2)
y3 = (x**3)
yn = (y1,y2,y3)
COLORS = ('b','g','k')
for i,y in enumerate(yn):
ax = fig.add_subplot(len(yn),1,i+1)
ax.plot(x, y, ls='solid', color=COLORS[i])
if i != len(yn) - 1:
# all but last
ax.set_xticklabels( () )
else:
for tick in ax.xaxis.get_major_ticks():
tick.label.set_fontsize(14)
# specify integer or one of preset strings, e.g.
#tick.label.set_fontsize('x-small')
tick.label.set_rotation('vertical')
fig.suptitle('Matplotlib xticklabels Example')
plt.show()
if __name__ == '__main__':
xticklabels_example()
Alternatively, you can just do:
import matplotlib as mpl
label_size = 8
mpl.rcParams['xtick.labelsize'] = label_size
Another alternative
I have two plots side by side and would like to adjust tick labels separately.
The above solutions were close however they were not working out for me. I found my solution from this matplotlib page.
ax.xaxis.set_tick_params(labelsize=20)
This did the trick and was straight to the point. For my use case, it was the plot on the right that needed to be adjusted. For the plot on the left since I was creating new tick labels I was able to adjust the font in the same process as seting the labels.
ie
ax1.set_xticklabels(ax1_x, fontsize=15)
ax1.set_yticklabels(ax1_y, fontsize=15)
thus I used for the right plot,
ax2.xaxis.set_tick_params(labelsize=24)
ax2.yaxis.set_tick_params(labelsize=24)
A minor subtlety... I know... but I hope this helps someone :)
Bonus points if anyone knows how to adjust the font size of the order of magnitude label.
plt.tick_params(axis='both', which='minor', labelsize=12)
In current versions of Matplotlib, you can do axis.set_xticklabels(labels, fontsize='small').
The following worked for me:
ax2.xaxis.set_tick_params(labelsize=7)
ax2.yaxis.set_tick_params(labelsize=7)
The advantage of the above is you do not need to provide the array of labels and works with any data on the axes.
For smaller font, I use
ax1.set_xticklabels(xticklabels, fontsize=7)
and it works!
You can also change label display parameters like fontsize with a line like this:
zed = [tick.label.set_fontsize(14) for tick in ax.yaxis.get_major_ticks()]