Log normalization

Preprocessing for Machine Learning in Python

James Chapman

Curriculum Manager, DataCamp

What is log normalization?

Captures relative changes, the magnitude of change, and keeps everything positive

print(df)

   col1   col2
0  1.00    3.0
1  1.20   45.5
2  0.75   28.0
3  1.60  100.0

print(df.var())

col1       0.128958
col2    1691.729167
dtype: float64

import numpy as np
df["log_2"] = np.log(df["col2"])
print(df)

   col1   col2     log_2
0  1.00    3.0  1.098612
1  1.20   45.5  3.817712
2  0.75   28.0  3.332205
3  1.60  100.0  4.605170

print(df[["col1", "log_2"]].var())

col1     0.128958
log_2    2.262886
dtype: float64

Preprocessing for Machine Learning in Python