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I have the dataset consisting of energy demand per each of the user profiles, sampled on every half an hour during different days (for example Weekday in Summer or Saturday in Winter). What I would like to do is to extend this for each day of a year using existing data with some randomness here and there.

What methods do you recommend for time series extrapolation?

The dataset I'm working on is here: https://data.ukedc.rl.ac.uk/browse/edc/efficiency/residential/LoadProfile/data

Andjela
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You may use imputeTS or pandas interpolate for filling missing values in betweens the days (i.e., imputation/interpolation) and forecast for filling future values (forecast/extrapolation).

Reveille
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