I have been reading up a bit on LSTM's and their use for time series and its been interesting but difficult at the same time. One thing I have had difficulties with understanding is the approach to adding additional features to what is already a list of time series features. Assuming you have your dataset up like this:
Now lets say you know you have a feature that does affect the output but its not necessarily a time series feature, lets say its the weather outside. Is this something you can just add and the LSTM will be able to distinguish what is the time series aspect and what isnt?