new_contents: #!/usr/bin/env python
  
  #
  # parse multiple HDF5 files and print graph
  #
  
  import pandas as pd
  
  import matplotlib
  matplotlib.use('AGG')
  import matplotlib.pyplot as plt
  
  from pandas import ExcelWriter
  
  print('Import data from HDF5 files')
  store1 = pd.HDFStore("E:\\home\\2014\\07\\logfile_20140701.hdf5", mode='r')
  print(store1.root.series.tarom.Total_Charge_Current.data[0:10])
  store2 = pd.HDFStore("E:\\home\\2014\\07\\logfile_20140702.hdf5", mode='r')
  print(store2.root.series.tarom.Total_Charge_Current.data[0:10])
  store3 = pd.HDFStore("E:\\home\\2014\\07\\logfile_20140703.hdf5", mode='r')
  print(store3.root.series.tarom.Total_Charge_Current.data[0:10])
  store4 = pd.HDFStore("E:\\home\\2014\\07\\logfile_20140704.hdf5", mode='r')
  print(store4.root.series.tarom.Total_Charge_Current.data[0:10])
  
  # Example accessing HDF5 using MyRaspiHome framework
  # -------------------------------------------------------------
  # from data_accessor.data_accessor_hdf5 import DataAccessorHDF5
  # da = DataAccessorHDF5()
  # da.open("E:\\home\\2014\\07\\logfile_20140701.hdf5", 'r')
  # parameter = ('Total_Charge_Current',)
  # data = da.read('tarom', parameter)
  # print(data)
  # da.close()
  
  # convert to pandas dataframes
  s1 = pd.Series.from_array(store1.root.series.tarom.Total_Charge_Current.data)
  df1 = pd.DataFrame(s1)
  s2 = pd.Series.from_array(store2.root.series.tarom.Total_Charge_Current.data)
  df2 = pd.DataFrame(s2)
  s3 = pd.Series.from_array(store3.root.series.tarom.Total_Charge_Current.data)
  df3 = pd.DataFrame(s3)
  s4 = pd.Series.from_array(store4.root.series.tarom.Total_Charge_Current.data)
  df4 = pd.DataFrame(s3)
  
  print('Merge data')
  merged = pd.merge(df1, df2)
  
  print('Print graph')
  figure = plt.figure()
  #merged.plot(kind='area', stacked=False)
  df1.plot(kind='area', stacked=False)
  #df2.plot(kind='area', stacked=False)
  #df3.plot(kind='area', stacked=False)
  #df4.plot(kind='area', stacked=False)
  plt.grid(True)
  plt.savefig('test.png')
  plt.close(figure)
  
  print('To excel')
  with ExcelWriter('output.xlsx') as writer:
      df1.to_excel(writer, sheet_name='Dateframe_1')
      #df2.to_excel(writer, sheet_name='Dateframe_2')
      #df3.to_excel(writer, sheet_name='Dateframe_3')
      #df4.to_excel(writer, sheet_name='Dateframe_4')
      #merged.to_excel(writer, sheet_name='Merged')
      
  print('done')
  
subject: Add example script which demonstrates usage of pandas and matplotlib.