python - 从皮尔逊方法的相关系数中找到斜率

Question

import pandas as pd
import numpy as np



df = pd.read_csv("test.txt", 
              sep='\t', 
              names= ["ElementID","Load"])

df.insert(0, 'count', df.groupby('ElementID').cumcount())


df2 = df.pivot(index='count',columns='ElementID', values='Load')
df2_norm = df2.apply(lambda x: (x / x.abs().max())) 
allowableCorr = df2_norm.corr(method = 'pearson') 
    
slope = allowableCorr * (df2_norm.std().values / 
df2_norm.std().values[:, np.newaxis])

我有很多数据集，我使用 .corr 方法来获取 r^2 值。但是，上面的代码并不总是与斜率结果匹配。我正在使用 excel 来测试斜率值。我究竟做错了什么？

测试.txt

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883.334717 716865 143.003952
716865 -127.804535
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