def skew_correction(df, numerical_features):
# Skew correction
skewed_feats = df[numerical_features].apply(lambda x: skew(x.dropna())) # compute skewness
skewed_feats = skewed_feats[skewed_feats > 0.75]
skewed_feats = skewed_feats.index
df.loc[:, tuple(skewed_feats)] = np.log1p(np.asarray(df[skewed_feats], dtype=float))
two_sigma_financial_modelling.py 文件源码
python
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