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from sklearn.preprocessing import StandardScaler

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

train = pd.read_csv('/kaggle/input/mobile-price-classification/train.csv')
test = pd.read_csv('/kaggle/input/mobile-price-classification/test.csv')
train

test.drop(columns=['id'], inplace=True)
test

X_train = X_sample.iloc[:, :-1].values
y_train = X_sample.iloc[:, -1].values
X_test = y_sample.iloc[:, :-1].values
y_test = y_sample.iloc[:, -1].values

(X_train.shape, X_test.shape, y_train.shape, y_test.shape)

from sklearn.preprocessing import StandardScaler
sc = StandardScaler()
X_train = sc.fit_transform(X_train)
X_test = sc.transform(X_test)

data_test = sc.transform(test)
data_test