Below is my code for a line graph. I would like another x label under the current one (so I can show the days of the week).
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns;sns.set()
sns.set()
data = pd.read_csv("123.csv")
data['DAY']=["01","02","03","04","05","06","07","08","09","10","11","12","13","14","15","16","17","18","19","20","21","22","23","24","25","26","27","28","29","30","31"]
plt.figure(figsize=(15,8))
plt.plot('DAY','SWST',data=data,linewidth=2,color="k")
plt.plot('DAY','WMID',data=data,linewidth=2,color="m")
plt.xlabel('DAY', fontsize=20)
plt.ylabel('VOLUME', fontsize=20)
plt.legend()
EDIT: After following the documentation, I have 2 issues. The scale has changed from 31 to 16, and the days of the week do not line up with the day number.
data['DAY']=["01","02","03","04","05","06","07","08","09","10","11","12","13","14","15","16","17","18","19","20","21","22","23","24","25","26","27","28","29","30","31"]
tick_labels=['1','\n\nThu','2','\n\nFri','3','\n\nSat','4','\n\nSun','5','\n\nMon','6','\n\nTue','7','\n\nWed','8','\n\nThu','9','\n\nFri','10','\n\nSat','11','\n\nSun','12','\n\nMon','13','\n\nTue','14','\n\nWed','15','\n\nThu','16','\n\nFri','17','\n\nSat','18','\n\nSun','19','\n\nMon','20','\n\nTue','21','\n\nWed','22','\n\nThu','23','\n\nFri','24','\n\nSat','25','\n\nSun','26','\n\nMon','27','\n\nTue','28','\n\nWed','29','\n\nThu','30','\n\nFri','31','\n\nSat']
tick_locations = np.arange(31)
plt.figure(figsize=(15,8))
plt.xticks(tick_locations, tick_labels)
plt.plot('DAY','SWST',data=data,linewidth=2,color="k")
plt.plot('DAY','WMID',data=data,linewidth=2,color="m")
plt.xlabel('DAY', fontsize=20)
plt.ylabel('VOLUME', fontsize=20)
plt.legend()
plt.show()
The pyplot function you are looking for is plt.xticks(). This is essentially a combination of ax.set_xticks() and ax.set_xticklabels()
From the documentation:
Parameters:
ticks : array_like
A list of positions at which ticks should be placed. You can pass an
empty list to disable xticks.
labels:
array_like, optional A list of explicit labels to place at the given
locs.
You would want something like the below code. Note you should probably explicitly set the tick locations as well as the labels to avoid setting labels in the wrong positions:
tick_labels = ['1','\n\nThu','2',..., '31','\n\nSat')
plt.xticks(tick_locations, tick_labels)
Note that the object-orientated API (i.e. using ax.) allows for more customisable plots.
Update
After the edit, I see that the labels you want to go below are part of the same list. Therefore your label list actually has a length of 62. So you need to join every 2 elements of your list together:
tick_labels=['1','\n\nThu','2','\n\nFri','3','\n\nSat','4','\n\nSun','5','\n\nMon','6','\n\nTue','7','\n\nWed','8',
'\n\nThu','9','\n\nFri','10','\n\nSat','11','\n\nSun','12','\n\nMon','13','\n\nTue','14','\n\nWed','15',
'\n\nThu','16','\n\nFri','17','\n\nSat','18','\n\nSun','19','\n\nMon','20','\n\nTue','21','\n\nWed','22',
'\n\nThu','23','\n\nFri','24','\n\nSat','25','\n\nSun','26','\n\nMon','27','\n\nTue','28','\n\nWed','29',
'\n\nThu','30','\n\nFri','31','\n\nSat']
tick_locations = np.arange(31)
new_labels = [ ''.join(x) for x in zip(tick_labels[0::2], tick_labels[1::2]) ]
plt.figure(figsize=(15, 8))
plt.xticks(tick_locations, new_labels)
plt.show()
Never use ax.set_xticklabels without setting the locations of the ticks as well. This can be done via ax.set_xticks.
ax.set_xticks(...)
ax.set_xticklabels(...)
Of course you may do the same with pyplot
ax = plt.gca()
ax.set_xticks(...)
ax.set_xticklabels(...)
Related
I want to plot a bar graph with a variable amount of values along the x-axis. For the data, I have a set of labels which I want to show on the x-axis under the bars. I also want the x-axis limits to start at -1, since otherwise, only half of the first bar at index 0 would be visible. I've tried multiple alternatives for achieving that, none of them worked, because the xticklabels are always one or more off. And IF they work for a given set of data, with another set of data (with more or less bars) it does not work again. See minimum code example below
from matplotlib import pyplot as plt
from matplotlib import ticker
import numpy as np
randData = np.random.rand(100)
xValues = np.linspace(0, len(randData)-1, num=len(randData))
labels = []
for i in range(len(randData)):
labels.append('label' + str(i))
fig, ax = plt.subplots()
ax.bar(np.linspace(0, len(randData)-1, num=len(randData)), randData)
ax.xaxis.set_major_locator(ticker.MultipleLocator(1))
# Alternative 1
# Use an empty string for index -1, set labels, then set new xlim
labels.insert(0, '')
ax.set_xticklabels(labels, size='x-small', rotation=90)
plt.xlim(-1, len(randData))
# Alternative 2
# Use an empty string for index -1, set new xlim, then set labels
labels.insert(0, '')
plt.xlim(-1, len(randData))
ax.set_xticklabels(labels, size='x-small', rotation=90)
# Alternative 3
# Setting limits with ax.set_xlim
ax.set_xticklabels(labels, size='x-small', rotation=90)
ax.set_xlim([-1, len(randData)])
# Alternative 4
# Setting limits with plt.xlim
ax.set_xticklabels(labels, size='x-small', rotation=90)
plt.xlim(-1, len(randData))
plt.show()
None of the variants worked so far. One part of the problem is that the pyplot automatically sets its xlimits depending on the amount of bar graphs (sometimes it starts at -1, with more values it might sometimes start at -4).
One of the faulty results is shown below:
Any help would be appreciated.
P.S.: If I may, I'd like to add a little side question: How can I remove the Warning "UserWarning: FixedFormatter should only be used together with FixedLocator" when setting the xticklabels? Nothing from this answer worked for me.
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.
How do I prevent matplotlib from adding default axis labels to my subplot? The simple code below also labels the x and y axes for 0 to 1. This is messing up my plot when I add actual data (the new labels are added according to the data but the 0 to 1 labels are still present).
import matplotlib.pyplot as plt
fig, ax1 = plt.subplots()
ax1 = fig.add_subplot(111)
plt.show(block=True)
The above produces this figure:
So when I include actual data it looks like this, with just this additional line of code (final_wavelengths and final_stellar are numpy arrays of equal length):
ax1.plot(final_wavelengths, final_stellar, 'b', label='stellar')
How can I remove the unwanted default 0-1 labels?
I was pointed to similar issue. for me worked explicit assigning to right axes by using ax = fig.axes[0] (I had a list of 2 different axes and needed for work just the first one)
I am trying to customize the xticks and yticks for my scatterplot with the simple code below:
import numpy as np
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(1,1,1)
y_ticks = np.arange(10, 41, 10)
x_ticks = np.arange(1000, 5001, 1000)
ax.set_yticks(y_ticks)
ax.set_xticks(x_ticks)
ax.scatter(some_x, some_y)
plt.show()
If we comment out the line: ax.scatter(x, y), we get an empty plot with the correct result:
However if the code is run exactly as shown, we get this:
Finally, if we run the code with ax.set_yticks(yticks) and ax.set_xticks(xticks) commented out, we also get the correct result (just with the axes not in the ranges I desire them to be):
Note that I am using Python version 2.7. Additionally, some_x and some_y are omitted.
Any input on why the axes are changing in such an odd manner only after I try plotting a scatterplot would be appreciated.
EDIT:
If I run ax.scatter(x, y) before xticks and yticks are set, I get odd results that are slightly different than before:
Matplotlib axes will always adjust themselves to the content. This is a desirable feature, because it allows to always see the plotted data, no matter if it ranges from -10 to -9 or from 1000 to 10000.
Setting the xticks will only change the tick locations. So if you set the ticks to locations between -10 and -9, but then plot data from 1000 to 10000, you would simply not see any ticks, because they do not lie in the shown range.
If the automatically chosen limits are not what you are looking for, you need to set them manually, using ax.set_xlim() and ax.set_ylim().
Finally it should be clear that in order to have correct numbers appear on the axes, you need to actually use numbers. If some_x and some_y in ax.scatter(some_x, some_y) are strings, they will not obey to any reasonable limits, but simply be plotted one after the other.
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.