I have a dataset with sales numbers for around 100 related products. Every day, the number of sales of each product is recorded along with other relevant information (what day of the week is it, is it a public holiday, what is the weather like etc. etc.).
So essentially this is a time series with daily entries, and I am thinking of pushing this through an LSTM.
My question is, how do I deal with the fact that I have multiple observations at every point in time?
Day Product Wheather NumberSold 1 Jan Meat Sunny 15 1 Jan Apples Sunny 211 1 Jan Fries Sunny 5 ... 1 Jan Carrots Cloudy 75 2 Jan Meat Cloudy 10 2 Jan Apples Cloudy 220 ... ...
Do I have to divide my dataset up by product so as to have only one entry per day to feed into the LSTM? Or is there a way to deal with all of the 1 Jan observations as a sort of batch that is remembered?