我有一个20+功能的熊猫数据框。我想看看它们的相关矩阵。我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 })
我希望能够显示由上述代码生成的多个热图,并排显示如下:
display_side_by_side(sb1, sb2, sb3, . . .)
我不知道该怎么做,因为上面的第一个代码块不仅将结果保存到sb1
,还绘制了热图。另外,不知道如何编写函数display_side_by_side()
。我正在使用以下熊猫数据帧:
# 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)
基于以下Simas Joneliunas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})
目前没有回答
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