new_contents: import tsam.timeseriesaggregation as tsam
  import pandas as pd
  
  raw = pd.read_csv('testdata.csv', index_col=0)
  
  aggregation = tsam.TimeSeriesAggregation(raw, noTypicalPeriods = 8,
                                           hoursPerPeriod = 24,
                                           clusterMethod = 'hierarchical')
  df = aggregation.createTypicalPeriods()
  weights = aggregation.clusterPeriodNoOccur
  aggregation.clusterOrder
  
  timesteps = [i for i in range(0, len(df.index.get_level_values('TimeStep')))]
  
  print(aggregation.clusterCenterIndices)
  
  # get all index for every hour that in day of the clusterCenterIndices
  days = [d for d in raw.index.dayofyear
          if d in aggregation.clusterCenterIndices]
  
  # select the dates based on this
  dates = raw.iloc[days].index
  
  # TODO: Check index start (1 in dataframe, 0 in numpy -> should fit, otherwise
  # days are offset one day
  
subject: Add script example