For this case study, we have generated data through software as we cannot use real data of our clients
The dataset contains sales data for 12 months. It has 13 columns. The details of these columns are given below:
(1) Product: Product ID
(2) APR: Sales Amount for the month of April
(3) MAY: Sales Amount for the month of May
(4) JUN: Sales Amount for the month of June
(5) JUL: Sales Amount for the month of July
(6) AUG: Sales Amount for the month of August
(7) SEP: Sales Amount for the month of September
(8) OCT: Sales Amount for the month of October
(9) NOV: Sales Amount for the month of November
(10) DEC: Sales Amount for the month of December
(11) JAN: Sales Amount for the month of January
(12) FEB: Sales Amount for the month of February
(13) MAR: Sales Amount for the month of March
The sales data from April to March (for one year) is given as amount with Product ID. The data are given from April to March because in India financial year starts from April. In any case, we require data of last 12 months so that we can find products whose sales is high
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