Develop Reference

How to scale graphs in seaborn scatterplot [duplicate]

How do I create a plot where the scales of x-axis and y-axis are the same?
This equal ratio should be maintained even if I change the window size. Currently, my graph scales together with the window size.
I tried:
plt.xlim(-3, 3)
plt.ylim(-3, 3)
plt.axis('equal')

Use Axes.set_aspect in the following manner:
from matplotlib import pyplot as plt
plt.plot(range(5))
plt.xlim(-3, 3)
plt.ylim(-3, 3)
ax = plt.gca()
ax.set_aspect('equal', adjustable='box')
plt.draw()

plt.axis('scaled')
works well for me.

See the documentation on plt.axis(). This:
plt.axis('equal')
doesn't work because it changes the limits of the axis to make circles appear circular. What you want is:
plt.axis('square')
This creates a square plot with equal axes.

Try something like:
import pylab as p
p.plot(x,y)
p.axis('equal')
p.show()

you can stretch the plot to square using this :
fig = plt.figure(figsize=(1, 1))

Python matplotlib: Rotate x-axis labels of a Bar-Chart [duplicate]

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.

python matplotlib: how to move the scale to the other side of the axis?

I have this weird thing with the scale of the axis showing out of the figure like:
And what I want to have:
How can I move the scale to the other side of the axis?
x=range(len(ticks))
plt.plot(x,phase1,'r^-',label='$\Delta \phi(U1,I1)$')
plt.plot(x,phase2,'go-',label='$\Delta \phi(U2,I2)$')
plt.plot(x,phase3,'b*-',label='$\Delta \phi(U3,I3)$')
plt.xticks(x,ticks,rotation=45)
plt.xlabel('Messung')
plt.ylabel('$\Delta \phi [^\circ]$')
plt.legend()
plt.show()

The tick_params of your axis can be used to control axes label and ticks location. Set direction to in so that they point into the graph.
And here is a great example if you want different y-axis ranges and colours too.
from matplotlib import pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
ax.tick_params(direction='in', length=6, width=2, colors='r', right=True, labelright='on')
plt.show()

You can use plt.tick_params() to adjust the behaviour of the ticks, documentation can be found here.
For your example you want the ticks to appear inside the figure. Therefore add
plt.tick_params(direction="in")
to your code. Example:
x=range(len(ticks))
plt.plot(x,phase1,'r^-',label='$\Delta \phi(U1,I1)$')
plt.plot(x,phase2,'go-',label='$\Delta \phi(U2,I2)$')
plt.plot(x,phase3,'b*-',label='$\Delta \phi(U3,I3)$')
plt.xticks(x,ticks,rotation=45)
plt.xlabel('Messung')
plt.ylabel('$\Delta \phi [^\circ]$')
plt.legend()
plt.tick_params(direction="in") # Set ticks inside the figure
plt.show()
You can get the ticks to appear on the top and right side of the figure too as shown in your second screenshot by adding:
plt.tick_params(direction="in",top="on",right="on")
If you wanted to make all figures in your Python script have this behaviour then you can add the following at the top of your script (this might be of interest):
import matplotlib
matplotlib.rcParams['xtick.direction'] = "in"
matplotlib.rcParams['ytick.direction'] = "in"
This will save you having to call plt.tick_params() for each figure, which is helpful if you generate lots of figures.

How to prevent overlapping x-axis labels in sns.countplot

For the plot
sns.countplot(x="HostRamSize",data=df)
I got the following graph with x-axis label mixing together, how do I avoid this? Should I change the size of the graph to solve this problem?

Having a Series ds like this
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np; np.random.seed(136)
l = "1234567890123"
categories = [ l[i:i+5]+" - "+l[i+1:i+6] for i in range(6)]
x = np.random.choice(categories, size=1000,
p=np.diff(np.array([0,0.7,2.8,6.5,8.5,9.3,10])/10.))
ds = pd.Series({"Column" : x})
there are several options to make the axis labels more readable.
Change figure size
plt.figure(figsize=(8,4)) # this creates a figure 8 inch wide, 4 inch high
sns.countplot(x="Column", data=ds)
plt.show()
Rotate the ticklabels
ax = sns.countplot(x="Column", data=ds)
ax.set_xticklabels(ax.get_xticklabels(), rotation=40, ha="right")
plt.tight_layout()
plt.show()
Decrease Fontsize
ax = sns.countplot(x="Column", data=ds)
ax.set_xticklabels(ax.get_xticklabels(), fontsize=7)
plt.tight_layout()
plt.show()
Of course any combination of those would work equally well.
Setting rcParams
The figure size and the xlabel fontsize can be set globally using rcParams
plt.rcParams["figure.figsize"] = (8, 4)
plt.rcParams["xtick.labelsize"] = 7
This might be useful to put on top of a juypter notebook such that those settings apply for any figure generated within. Unfortunately rotating the xticklabels is not possible using rcParams.
I guess it's worth noting that the same strategies would naturally also apply for seaborn barplot, matplotlib bar plot or pandas.bar.

You can rotate the x_labels and increase their font size using the xticks methods of pandas.pyplot.
For Example:
import matplotlib.pyplot as plt
plt.figure(figsize=(10,5))
chart = sns.countplot(x="HostRamSize",data=df)
plt.xticks(
rotation=45,
horizontalalignment='right',
fontweight='light',
fontsize='x-large'
)
For more such modifications you can refer this link:
Drawing from Data

If you just want to make sure xticks labels are not squeezed together, you can set a proper fig size and try fig.autofmt_xdate().
This function will automatically align and rotate the labels.

plt.figure(figsize=(15,10)) #adjust the size of plot
ax=sns.countplot(x=df['Location'],data=df,hue='label',palette='mako')
ax.set_xticklabels(ax.get_xticklabels(), rotation=40, ha="right") #it will rotate text on x axis
plt.tight_layout()
plt.show()
you can try this code & change size & rotation according to your need.

I don't know whether it is an option for you but maybe turning the graphic could be a solution (instead of plotting on x=, do it on y=), such that:
sns.countplot(y="HostRamSize",data=df)

Matplotlib delete plot stribes

I have the following issue displayed in the image below:
For an improved clarity I want do delete the stripes on the x axis or put them below the x axis. (Also it would be nice If you know a solution to the problem of overlapping numbers)

Assuming you have defined your plot and axes as below:
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
If you want to remove the x axis tick marks you can do:
ax.tick_params(axis='x', top='off', bottom='off')
If you want to change the direction of the tick marks you can do:
ax.tick_params(axis='x', direction='out')
If you want to change the x axis labels then use:
set_xticklabels()
You have to pass a list of labels to use, although I'm not sure why your labels aren't evenly spaced. The documentation at the link below should help:
matplotlib.axes documentation