特征锦囊：如何根据变量相关性画出热力图？

# 人体胸部加速度数据集,标签activity的数值为1-7
'''
1-在电脑前工作
2-站立、走路和上下楼梯
3-站立
4-走路
5-上下楼梯
6-与人边走边聊
7-站立着说话

'''
import pandas as pd
from sklearn.preprocessing import PolynomialFeatures

df = pd.read_csv('./data/activity_recognizer/1.csv', header=None)
df.columns = ['index','x','y','z','activity']

x = df[['x','y','z']]
y = df['activity']

# 多项式扩充数值变量
poly = PolynomialFeatures(degree=2, include_bias=False, interaction_only=False)

x_poly = poly.fit_transform(x)
pd.DataFrame(x_poly, columns=poly.get_feature_names()).head()

# 查看热力图(颜色越深代表相关性越强)
%matplotlib inline
import seaborn as sns

sns.heatmap(pd.DataFrame(x_poly, columns=poly.get_feature_names()).corr())