I have a dataset of almost 10,000 shops, 'dates' and 'sales amounts' as their features almost 2 years of data. I want to forecast each shop, the sales amount for 30 next days. I want to perform this on a CPU (laptop), no cloud, and no GPU.

I can do this if there are 10 to 20 shops, but I am not getting how to do this for 10,000 shops.

Current situation: I have aggregated all the shop's data and predicted the next 30 days using ARIMA. But not getting any idea how to do it at each shop level.

Please help.

Thank you.

I have a dataset of almost 10,000 shops, 'dates', 'shop ID' and 'sales amounts' as their features almost 2 years of data. I want to forecast each shop, the sales amount for 30 next days. I want to perform this on a CPU (laptop), no cloud, and no GPU. I can do this if there are 10 to 20 shops, but I am not getting how to do this for 10,000 shops.

I am adding an example dataset here.

The above fig shows shop ID, date and sale amount columns. Now for each shop ID there are almost 2 years of data. And there are such 10,000 shops.

Current situation: I have aggregated all the shop's data over date and predicted the next 30 days using ARIMA. But not getting any idea how to do it at each shop level.

Please help.

Thank you.