Additional feature scaling techniques in scikit-learn

Suppose you have the following 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[['AveRooms']]

Apply robust scaling on the AveRooms feature, do not center the data before the transformation (controlled by the with_centering parameter). The resulting feature should have a variance of 1 after the transformation (which could be controlled with theunit_variance parameter). Your answer should contain two values: the feature mean and the median after the transformation, rounded up to the third decimal point, separated by a space.