首页 > 解决方案 > Python:如何并排绘制多个 seaborn 热图?

问题描述

我有一个具有 20 多个功能的 Pandas 数据框。我想看看他们的相关矩阵。我使用如下代码创建热图,使用subset1,subset2等:

import seaborn as sns
cmap = sns.diverging_palette( 220 , 10 , as_cmap = True )
sb1 = sns.heatmap(
    subset1.corr(), 
    cmap = cmap,
    square=True, 
    cbar_kws={ 'shrink' : .9 }, 
    annot = True, 
    annot_kws = { 'fontsize' : 12 })

我希望能够并排显示上述代码生成的多个热图,如下所示:

display_side_by_side(sb1, sb2, sb3, . . .)

我不确定如何执行此操作,因为上面的第一个代码块不仅将结果保存到sb1,而且还绘制了热图。另外,不知道如何编写函数,display_side_by_side(). 我将以下内容用于 Pandas 数据框:

# create a helper function that takes pd.dataframes as input and outputs pretty, compact EDA results
from IPython.display import display_html
def display_side_by_side(*args):
    html_str = ''
    for df in args:
        html_str = html_str + df.to_html()
    display_html(html_str.replace('table','table style="display:inline"'),raw=True)

根据 Simas Joneliunas 下面的第一个答案,我提出了以下工作解决方案:

import matplotlib.pyplot as plt
import seaborn as sns

# Here we create a figure instance, and two subplots
fig = plt.figure(figsize = (20,20)) # width x height
ax1 = fig.add_subplot(3, 3, 1) # row, column, position
ax2 = fig.add_subplot(3, 3, 2)
ax3 = fig.add_subplot(3, 3, 3)
ax4 = fig.add_subplot(3, 3, 4)
ax5 = fig.add_subplot(3, 3, 5)

# We use ax parameter to tell seaborn which subplot to use for this plot
sns.heatmap(data=subset1.corr(), ax=ax1, cmap = cmap, square=True, cbar_kws={'shrink': .3}, annot=True, annot_kws={'fontsize': 12})
sns.heatmap(data=subset2.corr(), ax=ax2, cmap = cmap, square=True, cbar_kws={'shrink': .3}, annot=True, annot_kws={'fontsize': 12})
sns.heatmap(data=subset3.corr(), ax=ax3, cmap = cmap, square=True, cbar_kws={'shrink': .3}, annot=True, annot_kws={'fontsize': 12})
sns.heatmap(data=subset4.corr(), ax=ax4, cmap = cmap, square=True, cbar_kws={'shrink': .3}, annot=True, annot_kws={'fontsize': 12})
sns.heatmap(data=subset5.corr(), ax=ax5, cmap = cmap, square=True, cbar_kws={'shrink': .3}, annot=True, annot_kws={'fontsize': 12})

标签: pythonplotseaborn

解决方案


你应该看看 matplotlib.add_subplot:

# Here we create a figure instance, and two subplots
fig = plt.figure()
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212)

# We use ax parameter to tell seaborn which subplot to use for this plot
sns.pointplot(x="x", y="y", data=data, ax=ax1)

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