transform a pandas column with natural logarithm in python

To transform a column in pandas with the natural logarithm (base e), you can use the numpy library in combination with the .apply() method provided by pandas.

First, let's assume you have a pandas DataFrame called df with a column named column_name that you want to transform. Here's an example code snippet that demonstrates how to apply the natural logarithm transformation:

main.py
import pandas as pd
import numpy as np

# Create a sample DataFrame
data = {'column_name': [1, 2, 3, 4, 5]}
df = pd.DataFrame(data)

# Apply the natural logarithm transformation
df['transformed_column'] = np.log(df['column_name'])

# Print the DataFrame
print(df)
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This code will create a new column called transformed_column in df which contains the natural logarithm values of the column_name column.

Note that we use the np.log() function from NumPy to apply the natural logarithm transformation.