请注意，如果您试图传递给seaborn中的“图形级”方法(例如lmplot, catplot / factorplot, jointplot)，您可以并且应该在参数中使用height和aspect指定此方法。

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

请参阅https://github.com/mwaskom/seaborn/issues/488和使用matplotlib面向对象接口使用seaborn进行绘图，以获得关于图形级方法不遵守轴规范的更多详细信息。

首先导入matplotlib并使用它来设置图形的大小

from matplotlib import pyplot as plt
import seaborn as sns

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

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)

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

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

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, ...)