df['Age_scaled'] = scaler.fit_transform(df['Age'], age_scale_param)

[wenchengxucool]

ValueError: Expected 2D array, got 1D array instead:

[wenchengxucool]

Reshape your data either using array.reshape(-1, 1) ,if your data has a single feature or array.reshape(1, -1) if it contains a single sample.

[wenchengxucool]

import sklearn.preprocessing as preprocessing

'''
Reshape your data either using array.reshape(-1, 1)
if your data has a single feature or array.reshape(1, -1) if it contains a single sample.
'''
scaler = preprocessing.StandardScaler()
age_scale_param = scaler.fit(df['Age'].reshape(-1, 1))
df['Age_scaled'] = scaler.fit_transform(df['Age'].reshape(-1, 1), age_scale_param)
fare_scale_param = scaler.fit(df['Fare'].reshape(-1, 1))
df['Fare_scaled'] = scaler.fit_transform(df['Fare'].reshape(-1, 1), fare_scale_param)
df

[dwindy]

in current version
might try
.values.reshape(-1, 1)

[Sh-Zh-7]

Or you can try .to_frame()
The way pandas DataFrame object organizing its values is just like the column vectors.