Python 中的机器学习特征工程
Robert O'Callaghan
Director of Data Science, Ordergroove
q_cutoff = df['col_name'].quantile(0.95) mask = df['col_name'] < q_cutoff trimmed_df = df[mask]
mean = df['col_name'].mean() std = df['col_name'].std() cut_off = std * 3 lower, upper = mean - cut_off, mean + cut_off new_df = df[(df['col_name'] < upper) & (df['col_name'] > lower)]
mean = df['col_name'].mean() std = df['col_name'].std()
cut_off = std * 3 lower, upper = mean - cut_off, mean + cut_off
new_df = df[(df['col_name'] < upper) & (df['col_name'] > lower)]
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