Seaborn lmplot 标注相关性

Question

如何在lmplot中注释文本？ 我想显示“petal_length”与 iris 数据集中其他特征之间的相关性，所以我用lmplot绘制了回归图。

import seaborn as sns
import pandas as pd

df = sns.load_dataset('iris')
melt = pd.melt(df, id_vars=['species','petal_length'], value_vars=['sepal_length','sepal_width', 'petal_width'])
sns.lmplot(data=melt, x='value', y='petal_length', col='variable', sharey=False, sharex=False)

但是，我不知道如何注释相关值。 我可以用一个regplot做到这一点，就像这样：

from scipy.stats import spearmanr

r, pvalue = spearmanr(df['sepal_length'], df['petal_length'])
sns.regplot(data=df, x='sepal_length', y='petal_length', label=f'Spearman = {r:.2f}')
plt.legend()

lmplot返回一个 FacetGrid，所以我必须在每个轴上注释文本。 如何注释FacetGrid上的值列表？

spearman = []
for feature in ['sepal_length','sepal_width', 'petal_width']:
    r, pvalue = spearmanr(df['petal_length'], df[feature])
    spearman.append(r)
print(spearman)

[0.8818981264349859，-0.30963508601557777，0.9376668235763412]

Answer 1

您可以遍历轴，计算 r 值并将其添加到图例中：

import seaborn as sns
import pandas as pd
from scipy.stats import spearmanr
from matplotlib import pyplot as plt

df = sns.load_dataset('iris')
melt = pd.melt(df, id_vars=['species', 'petal_length'], value_vars=['sepal_length', 'sepal_width', 'petal_width'])
g = sns.lmplot(data=melt, x='value', y='petal_length', col='variable', sharey=False, sharex=False)

for ax, feature in zip(g.axes.flat, g.col_names):
    r, pvalue = spearmanr(df['petal_length'], df[feature])
    ax.collections[0].set_label(f'Spearman = {r:.2f}')
    ax.legend()
plt.tight_layout()
plt.show()

PS：除了创建图例，您还可以更新标题，例如。

ax.set_title(ax.get_title() + f', r={r:.2f}')