3 examples of 'pandas min max normalization' in Python

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82def normalize(df, excludes):
83 result = df.copy()
84 for feature_name in df.columns:
85 if feature_name in excludes:
86 continue
87 try:
88 max_value = df[feature_name].max()
89 min_value = df[feature_name].min()
90 if max_value == min_value:
91 min_value = 0
92 result[feature_name] = (df[feature_name] - min_value) / (max_value - min_value)
93 result[feature_name] = result[feature_name].apply(lambda x: round(abs(x), 4))
94 except:
95 LOGGER.error(f'Error normalizing feature: {feature_name}')
96 raise RuntimeError(f'Error normalizing feature: {feature_name}')
97 return result
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34def norm_minmax(X, min_=0, max_=1):
35 Xmin = X.min(axis=0)
36 Xmax = X.max(axis=0)
37 return (X - Xmin) / (Xmax - Xmin) * (max_ - min_) + min_
396def minmax_normalize(X, lower, upper):
397 return (X - lower) / (upper - lower)

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