predict future value in every one hour using (t+60 minutes) LSTM neural network in python
One option is to :


Break data into constant-frequency observations (E.g.: Assume that g,p,c,out are same for all time periods between two observations). With this, you will get samples every N minutes. 
Training data will then be a set of [Last M observations till T, Observation for T + 60]


This Train and test data can be fed into a network.