Future values means, if you are predicting for time 1300 hrs you can not use >1300hrs information because you won't be having that at inference time. for example shift(-1)

Does this mean we have to take separate data for each timestamp (like data <1300 hrs for predicting values on 1300 hrs and so on) and predict according to that? In that case, how can it be possible? because there are 63 unique() time stamps in the time column. Do we have to take separate data for all of them and train on 63 different models, predict, and then combine the rows? Please guide me as I am a beginner in data science and machine learning