[sklearn][standardscaler] can I inverse the standardscaler for the model output?

Question

I have some data structured as below, trying to predict t from the features.

train_df

t: time to predict
f1: feature1
f2: feature2 
f3:......
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Answer 1

Yeah, and it's conveniently called inverse_transform.

The documentation provides examples of its use.

Answer 2

Here is sample code. You can replace here data with train_df['colunm_name']. Hope it helps.

from sklearn.preprocessing import StandardScaler
data = [[1,1], [2,3], [3,2], [1,1]]
scaler = StandardScaler()
scaler.fit(data)
scaled = scaler.transform(data)
print(scaled)

# for inverse transformation
inversed = scaler.inverse_transform(scaled)
print(inversed)