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import pandas as pd

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

import seaborn as sns

data = pd.read_csv('/kaggle/input/car-price-prediction/car_price.csv')

data.shape

data.sample()

data[data.duplicated()]

data.nunique()

features = data.copy()

features.drop(columns=['fueltype', 'aspiration', 'doornumber', 'drivewheel', 'enginelocation', 'symboling'], inplace=True)
features.columns

corr = features.select_dtypes('number').drop(columns=['price']).corr()

features.drop(columns=['wheelbase', 'enginesize', 'boreratio', 'highwaympg'], inplace=True)
features.columns

corr = features.select_dtypes('number').drop(columns=['price']).corr()

features.info()