data = pd.read_csv('train.csv')
data['date'] = pd.to_datetime(data['date'])
**# combine store and item column as time_series**
data['store'] = ['store_' + str(i) for i in data['store']]
data['item'] = ['item_' + str(i) for i in data['item']]
data['time_series'] = data[['store', 'item']].apply(lambda x: '_'.join(x), axis=1)
data.drop(['store', 'item'], axis=1, inplace=True)
**# extract features from date**
data['month'] = [i.month for i in data['date']]
data['year'] = [i.year for i in data['date']]
data['day_of_week'] = [i.dayofweek for i in data['date']]
data['day_of_year'] = [i.dayofyear for i in data['date']]