text_plain_output_1.png image_output_1.png
from sklearn.preprocessing import MinMaxScaler

from sklearn.preprocessing import MinMaxScaler

import pandas as pd

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

numerical = ['battery_power', 'clock_speed', 'fc', 'int_memory', 'm_dep', 'mobile_wt', 'n_cores', 'pc', 'px_height', 'px_width', 'ram', 'sc_h', 'sc_w', 'talk_time']
categorical = ['blue', 'dual_sim', 'four_g', 'three_g', 'touch_screen', 'wifi']

from sklearn.preprocessing import MinMaxScaler
scaler_test = MinMaxScaler()
test_num_scaled = scaler_test.fit_transform(test[numerical])
scaler_test.data_max_
scaler_test.data_min_