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import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.linear_model import PassiveAggressiveRegressor
data = pd.read_csv("")
x = np.array(data.drop(["Sales"], 1))
y = np.array(data["Sales"])
xtrain, xtest, ytrain, ytest = train_test_split(x, y, test_size=0.2, random_state=42)
model = PassiveAggressiveRegressor(), ytrain)
ypred = model.predict(xtest)
data = pd.DataFrame(data={"Predicted Sales": ypred.flatten()})
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