Additional feature scaling techniques in scikit-learn

Consider the HouseAge feature from the California housing dataset:

import pandas as pd
from sklearn.datasets import fetch_california_housing

data = fetch_california_housing(as_frame=True)
df = data.frame[['HouseAge']]

Perform the power transformation with the Box-Cox transform. Your answer should contain the parameters for the transformation of the selected feature (as a dictionary), along with it's minimum value, rounded up to the second decimal point, with each value on a new line, in the specified order.

The answer should have the following format:

{'copy': False, 'standardize': True}
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