text_plain_output_1.png
import pandas as pd

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

d_item_cat = pd.read_csv('/kaggle/input/competitive-data-science-predict-future-sales/item_categories.csv')

d_items = pd.read_csv('/kaggle/input/competitive-data-science-predict-future-sales/items.csv')

d_sam_sub = pd.read_csv('/kaggle/input/competitive-data-science-predict-future-sales/sample_submission.csv')

d_sal_tra = pd.read_csv('/kaggle/input/competitive-data-science-predict-future-sales/sales_train.csv')

d_shop = pd.read_csv('/kaggle/input/competitive-data-science-predict-future-sales/shops.csv')

d_test = pd.read_csv('/kaggle/input/competitive-data-science-predict-future-sales/test.csv')

dt_test = d_test.drop(labels='ID', axis=1)
dt_test

new_data = d_sal_tra.copy()
new_data

new_data = pd.merge(d_item_cat, d_items, how='inner', on='item_category_id')
new_data

new_data = pd.merge(new_data, d_sal_tra, how='inner', on='item_id')
new_data

new_data = pd.merge(new_data, d_shop, how='inner', on='shop_id')
new_data

dx = ['shop_id', 'item_id']
x = new_data[dx]
y = new_data['item_cnt_day']
(x, y)