For time series data, you don't want to shuffle, because now you are predicting the past based on the future. I think the best way is to choose a minimum times

For time series data, you don't want to shuffle, because now you are predicting the past based on the future. I think the best way is to choose a minimum timespan you want to be able to predict on, train on that and predict on the future, then retrain, including that future and predict on the next future. If your time series allow it (e.g. contains a bunch of independent target groups) you can train/test on a subset and leave a another subset for validation