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# This didn't improve the model. Might be because the data had 
# one hot vector and numerical columns all together.
from sklearn.preprocessing import StandardScaler
std = StandardScaler()
std.fit(df)
df = pd.DataFrame(std.transform(df), columns=x_df.columns)