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# importing required libraries
import pandas as pd
from sklearn.compose import ColumnTransformer
from sklearn.impute import SimpleImputer
import category_encoders as ce
from sklearn.preprocessing import StandardScaler
from sklearn.ensemble import RandomForestRegressor
from sklearn.pipeline import Pipeline
# read the training data set
data = pd.read_csv('dataset/train_kOBLwZA.csv')
# top rows of the data
data.head()
# seperate the independent and target variables
train_x = data.drop(columns=['Item_Outlet_Sales'])
train_y = data['Item_Outlet_Sales']
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