How to change the figure size of a seaborn axes or figure level plot

Question

How do I change the size of my image so it's suitable for printing?

For example, I'd like to use an A4 paper, whose dimensions are 11.7 inches by 8.27 inches in landscape orientation.

Answer 1

You need to create the matplotlib Figure and Axes objects ahead of time, specifying how big the figure is:

from matplotlib import pyplot
import seaborn

import mylib

a4_dims = (11.7, 8.27)
df = mylib.load_data()
fig, ax = pyplot.subplots(figsize=a4_dims)
seaborn.violinplot(ax=ax, data=df, **violin_options)

Answer 2

Change Axes-level plot size

Seaborn has plotter functions that return Axes objects. The size of those plots can be changed globally using the set() or set_theme() functions (as given in niraj's answer).

import seaborn as sns
df = sns.load_dataset("tips")

sns.set_theme(rc={'figure.figsize': (8.27, 11.7)})
ax = sns.regplot(df, x='total_bill', y='tip')

The size of these plots can also be changed by changing the size of the underlying matplotlib figure that contains this Axes using set_size_inches(). Note that dmainz's answer's answer does a similar thing but it works by setting the width and height separately; this method sets them both in one function call. This is especially useful if your seaborn plot is created somewhere else and you want to change its size to whatever you want in inches.

ax = sns.regplot(df, x='total_bill', y='tip')     # the default figsize is 6.4"x4.8"
ax.figure.set_size_inches(8.27, 11.7)             # now it becomes 8.27"x11.7"

If your seaborn plot is generated by the function that doesn't return a value, then you can still change it by accessing the current figure object using plt.gcf(). For example:

import matplotlib.pyplot as plt

sns.regplot(df, x='total_bill', y='tip')
plt.gcf().set_size_inches(8.27, 11.7)

Note that set() or set_theme() changes the figure size globally which may not be desirable if you only want to set a specific size of a single figure and use the default settings for others. In that case, you can use a context manager to change the figsize of a single figure.

with plt.rc_context(rc={'figure.figsize': (8.27, 11.7)}):
    sns.regplot(df, x='total_bill', y='tip')

Change figure / FacetGrid size

Similar to above where the underlying matplotlib figure size was changed, the same can be done for FacetGrid objects as well. A demo goes as follows:

g = sns.lmplot(data=df, x='total_bill', y='tip')  # the default figsize is 5"x5"
g.fig.set_size_inches(8.27, 11.7)                 # now it becomes 8.27"x11.7"

Note that if your seaborn figure is generated by the function that doesn't return a value, then you can still change it by accessing the current figure object using plt.gcf():

sns.lmplot(data=df, x='total_bill', y='tip')
plt.gcf().set_size_inches(8.27, 11.7)

Answer 3

# Sets the figure size temporarily but has to be set again the next plot
plt.figure(figsize=(18,18))

sns.barplot(x=housing.ocean_proximity, y=housing.median_house_value)
plt.show()

Answer 4

The top answers by Paul H and J. Li do not work for all types of seaborn figures. For the FacetGrid type (for instance sns.lmplot()), use the size and aspect parameter.

Size changes both the height and width, maintaining the aspect ratio.

Aspect only changes the width, keeping the height constant.

You can always get your desired size by playing with these two parameters.

Credit: https://stackoverflow.com/a/28765059/3901029

Answer 5

Some tried out ways:

import seaborn as sns
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=[15,7])
sns.boxplot(x="feature1", y="feature2",data=df, ax=ax) # where df would be your dataframe

or

import seaborn as sns
import matplotlib.pyplot as plt
plt.figure(figsize=[15,7])
sns.boxplot(x="feature1", y="feature2",data=df) # where df would be your dataframe

Answer 6

first import matplotlib and use it to set the size of the figure

from matplotlib import pyplot as plt
import seaborn as sns

plt.figure(figsize=(15,8))
ax = sns.barplot(x="Word", y="Frequency", data=boxdata)

Answer 7

Note that if you are trying to pass to a "figure level" method in seaborn (for example lmplot, catplot / factorplot, jointplot) you can and should specify this within the arguments using height and aspect.

sns.catplot(data=df, x='xvar', y='yvar', 
    hue='hue_bar', height=8.27, aspect=11.7/8.27)

See https://github.com/mwaskom/seaborn/issues/488 and Plotting with seaborn using the matplotlib object-oriented interface for more details on the fact that figure level methods do not obey axes specifications.

Answer 8

You can also set figure size by passing dictionary to rc parameter with key 'figure.figsize' in seaborn set_theme method (which replaces the set method, deprecated in v0.11.0 (September 2020))

import seaborn as sns

sns.set_theme(rc={'figure.figsize':(11.7,8.27)})

Other alternative may be to use figure.figsize of rcParams to set figure size as below:

from matplotlib import rcParams

# figure size in inches
rcParams['figure.figsize'] = 11.7,8.27

More details can be found in matplotlib documentation

Answer 9

For my plot (a sns factorplot) the proposed answer didn't works fine.

Thus I use

plt.gcf().set_size_inches(11.7, 8.27)

Just after the plot with seaborn (so no need to pass an ax to seaborn or to change the rc settings).

Answer 10

This shall also work.

from matplotlib import pyplot as plt
import seaborn as sns    

plt.figure(figsize=(15,16))
sns.countplot(data=yourdata, ...)

Answer 11

• See How to change the image size for seaborn.objects for a solution with the new seaborn.objects interface from seaborn v0.12, which is not the same as seaborn axes-level or figure-level plots.
• Adjusting the size of the plot depends if the plot is a figure-level plot like seaborn.displot, or an axes-level plot like seaborn.histplot. This answer applies to any figure or axes level plots.
  • See the the seaborn API reference
• seaborn is a high-level API for matplotlib, so seaborn works with matplotlib methods
• Tested in python 3.8.12, matplotlib 3.4.3, seaborn 0.11.2

Imports and Data

import seaborn as sns
import matplotlib.pyplot as plt

# load data
df = sns.load_dataset('penguins')

sns.displot

• The size of a figure-level plot can be adjusted with the height and/or aspect parameters
• Additionally, the dpi of the figure can be set by accessing the fig object and using .set_dpi()

p = sns.displot(data=df, x='flipper_length_mm', stat='density', height=4, aspect=1.5)
p.fig.set_dpi(100)

• Without p.fig.set_dpi(100)

• With p.fig.set_dpi(100)

sns.histplot

• The size of an axes-level plot can be adjusted with figsize and/or dpi

# create figure and axes
fig, ax = plt.subplots(figsize=(6, 5), dpi=100)

# plot to the existing fig, by using ax=ax
p = sns.histplot(data=df, x='flipper_length_mm', stat='density', ax=ax)

• Without dpi=100

• With dpi=100

Answer 12

You can set the context to be poster or manually set fig_size.

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt

np.random.seed(0)
n, p = 40, 8
d = np.random.normal(0, 2, (n, p))
d += np.log(np.arange(1, p + 1)) * -5 + 10


# plot
sns.set_style('ticks')
fig, ax = plt.subplots()
# the size of A4 paper
fig.set_size_inches(11.7, 8.27)
sns.violinplot(data=d, inner="points", ax=ax)    
sns.despine()

fig.savefig('example.png')

Answer 13

In addition to elz answer regarding "figure level" methods that return multi-plot grid objects it is possible to set the figure height and width explicitly (that is without using aspect ratio) using the following approach:

import seaborn as sns 

g = sns.catplot(data=df, x='xvar', y='yvar', hue='hue_bar')
g.fig.set_figwidth(8.27)
g.fig.set_figheight(11.7)

Answer 14

This can be done using:

plt.figure(figsize=(15,8))
sns.kdeplot(data,shade=True)