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

Each Answer to this Q is separated by one/two green lines.

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

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

You can also set figure size by passing dictionary to rc parameter with key 'figure.figsize' in seaborn set method:

import seaborn as sns

sns.set(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

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)

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.

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)

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')

enter image description here

This can be done using:

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

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)

This shall also work.

from matplotlib import pyplot as plt
import seaborn as sns    

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

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).

  • 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.
  • 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)

enter image description here

  • With p.fig.set_dpi(100)

enter image description here

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

enter image description here

  • With dpi=100

enter image description here

# 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()

An 18x18 plot of my graph

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

Some tried out ways:

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


The answers/resolutions are collected from stackoverflow, are licensed under cc by-sa 2.5 , cc by-sa 3.0 and cc by-sa 4.0 .

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