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I have a sales dataset with each store having a unique identifier. The dataset contains daily sales data for each store over a period of around two-years. I'm looking to build a time series forecasting model to predict future sales for each store.

I would appreciate guidance on the steps and best practices of how can i handle the date as an index?

My data looks like this, enter image description here

As you can see, I have converted the 'Date' column into an index column. However, I've encountered a situation where the same date, like '2015-07-31,' occurs in records for multiple stores. How can I effectively manage this scenario using pandas and Python while retaining date-time information as a feature variable?

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1 Answer 1

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In my opinion, you should be predicting the sales of each store separately and then each store will have a date only once in the dataset.

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