pearson相关系数算法

#-*- coding: utf-8 -*- #计算两两指标间的相关系数矩阵 import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns inputfile = 'data3.csv' #输入的数据文件 data = pd.read_csv(inputfile) #读取数据 pearson=np.round(data.corr(method = 'pearson'), 2) #计算相关系数矩阵，保留两位小数 print(pearson) pearson.to_csv("data.csv") #热力图 colormap = plt.cm.viridis plt.figure(figsize=(30,30)) plt.title('Unit_price Correlation of Features', y=1.05, size=15) sns.heatmap(data.astype(float).corr(),linewidths=0.1,vmax=1.0, square=True, cmap=colormap, linecolor='white', annot=True) plt.show()