# 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()

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')

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, ...)

你需要提前创建matplotlib Figure和Axes对象，指定图形的大小:

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)

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