StandardScaler

from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split

df=df.drop(columns=['date'])
y=df.pop('Press_mm_hg')
X_train, X_test, y_train, y_test = train_test_split(df, y, test_size=0.33, random_state=42)

standard_scaler=StandardScaler()
standard_scaler.fit(X_train)

X_train[X_train.columns]=standard_scaler.transform(X_train)
X_test[X_train.columns]=standard_scaler.transform(X_test)
X_train