Australian-Electricity-Demand

Australian Electricity Demand forecasting data, half-hourly data. From original source: ----- This dataset contains 5 time series representing the half hourly electricity demand of 5 states in Australia: Victoria, New South Wales, Queensland, Tasmania and South Australia. It was extracted from R tsibbledata package. ----- They claim that the original data comes from the R tsibbledata package, but I could not find the original data in the package or the original source. There are 5 columns: id_series: The id of the time series. date: The date of the time series in the format "%Y-%m-%d %H:%M:$S". time_step: The time step on the time series. covariate_0: Covariate values of the time series, tied to the 'id_series'. Not interested in forecasting, but can help with the forecasting task. value_0: The values of the time series, which will be used for the forecasting task. Preprocessing: 1 - Renamed columns 'series_name', 'series_value', 'state' to 'id_series', 'value_0', and 'covariate_0'. 2 - Exploded the 'value_0' column. 3 - Created 'time_step' column from the exploded data. 4 - Created 'date' column from 'starting_date' and 'time_step'. 5 - Casted 'date' to str, 'time_step' to int, 'value_0' to float, and defined 'id_series' and 'covariate_0' as 'category'.