这也会起作用。

from matplotlib import pyplot as plt
import seaborn as sns    

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

您可以将上下文设置为poster或手动设置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')

对于我的图(一个sns因子图)，建议的答案并不能很好地工作。

因此我使用

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

就在与seaborn的情节之后(所以不需要传递一个斧头给seaborn或改变rc设置)。

一些尝试过的方法:

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

这可以使用:

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

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

导入和数据

import seaborn as sns
import matplotlib.pyplot as plt

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

sns.displot

图形级图的大小可以通过高度和/或纵横参数进行调整 此外，图的dpi可以通过访问fig对象并使用.set_dpi()来设置。

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

没有p.fig.set_dpi (100)

与p.fig.set_dpi (100)

sns.histplot

轴级图的大小可以通过figsize和/或dpi进行调整

# 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)

没有dpi = 100

dpi = 100