old_contents: from __future__ import absolute_import, division, print_function
  import matplotlib.pyplot as plt
  import example_helpers
  import drms
  
  
  # Series name, timespan and wavelength
  series = 'aia.lev1_euv_12s'
  series_lev1 = 'aia.lev1'
  wavelen = 335
  #tsel = '2015-01-01T00:00:01Z/1h'
  #tsel = '2015-01-01T00:00:01Z/1d'
  #tsel = '2015-01-01T00:00:01Z/1d@60s'
  #tsel = '2015-01-01T00:00:01Z/7d@1h'
  #tsel = '2015-01-01T00:00:01Z/30d@6h'
  #tsel = '2015-01-01T00:00:01Z/100d@1d'
  tsel = '2014-01-01T00:00:01Z/365d@1d'
  
  # DRMS query string
  qstr = '%s[%s][%d]' % (series, tsel, wavelen)
  
  # Some keywords we are interested in; you can use c.keys(series) to get a
  # list of all available keywords of a series.
  keys = ['T_REC', 'T_OBS', 'DATAMIN', 'DATAMAX', 'DATAMEAN', 'DATARMS',
          'DATASKEW', 'DATAKURT', 'QUALITY']
  
  
  # Create DRMS client, uses JSOC baseurl by default, set debug=True to see the
  # DRMS query URLs.
  c = drms.Client(debug=False)
  
  # Get detailed information about the series. Some keywords from
  # aia.lev1_euv_12s are links to keywords in aia.lev1 and unfortunally some
  # entries (like note) are missing for linked keywords, so we are using the
  # entries from aia.lev1 in this case.
  print('Querying series info...')
  si = c.info(series)
  si_lev1 = c.info(series_lev1)
  for k in keys:
      linkinfo = si.keywords.loc[k].linkinfo
      if linkinfo is not None and linkinfo.startswith('lev1->'):
          note_str = si_lev1.keywords.loc[k].note
      else:
          note_str = si.keywords.loc[k].note
      print('%10s : %s' % (k, note_str))
  
  # Get keyword values for the selected timespan and wavelength
  print('Querying keyword data...\n -> %s' % qstr)
  res = c.query(qstr, key=keys)
  print(' -> %d lines retrieved.' % len(res))
  
  # Only use entries with QUALITY==0
  res = res[res.QUALITY == 0]
  print(' -> %d lines after QUALITY selection.' % len(res))
  
  # Convert T_REC strings to datetime and use it as index for the series
  res.index = drms.to_datetime(res.T_REC)
  
  # Create some simple plots
  plt.close('all')
  res[['DATAMEAN']].plot()
  res[['DATASKEW', 'DATARMS', 'DATAMEAN']].plot()
  res[['DATAMAX', 'DATAMIN', 'DATAMEAN']].plot()
  plt.show()
  
new_contents: from __future__ import absolute_import, division, print_function
  import matplotlib.pyplot as plt
  import example_helpers
  import drms
  
  
  # Series name, timespan and wavelength
  series = 'aia.lev1_euv_12s'
  series_lev1 = 'aia.lev1'
  wavelen = 335
  #tsel = '2015-01-01T00:00:01Z/1h'
  #tsel = '2015-01-01T00:00:01Z/1d'
  #tsel = '2015-01-01T00:00:01Z/1d@60s'
  #tsel = '2015-01-01T00:00:01Z/7d@1h'
  #tsel = '2015-01-01T00:00:01Z/30d@6h'
  #tsel = '2015-01-01T00:00:01Z/100d@1d'
  tsel = '2014-01-01T00:00:01Z/365d@1d'
  
  # DRMS query string
  qstr = '%s[%s][%d]' % (series, tsel, wavelen)
  
  # Some keywords we are interested in; you can use c.keys(series) to get a
  # list of all available keywords of a series.
  keys = ['T_REC', 'T_OBS', 'DATAMIN', 'DATAMAX', 'DATAMEAN', 'DATARMS',
          'DATASKEW', 'DATAKURT', 'QUALITY']
  
  
  # Create DRMS client, uses JSOC baseurl by default, set debug=True to see the
  # DRMS query URLs.
  c = drms.Client(debug=False)
  
  # Get detailed information about the series. Some keywords from
  # aia.lev1_euv_12s are links to keywords in aia.lev1 and unfortunally some
  # entries (like note) are missing for linked keywords, so we are using the
  # entries from aia.lev1 in this case.
  print('Querying series info...')
  si = c.info(series)
  si_lev1 = c.info(series_lev1)
  for k in keys:
      linkinfo = si.keywords.loc[k].linkinfo
      if linkinfo is not None and linkinfo.startswith('lev1->'):
          note_str = si_lev1.keywords.loc[k].note
      else:
          note_str = si.keywords.loc[k].note
      print('%10s : %s' % (k, note_str))
  
  # Get keyword values for the selected timespan and wavelength
  print('Querying keyword data...\n -> %s' % qstr)
  res = c.query(qstr, key=keys)
  print(' -> %d lines retrieved.' % len(res))
  
  # Only use entries with QUALITY==0
  res = res[res.QUALITY == 0]
  print(' -> %d lines after QUALITY selection.' % len(res))
  
  # Convert T_REC strings to datetime and use it as index for the series
  res.index = drms.to_datetime(res.T_REC)
  
  # Create some simple plots
  ax = res[['DATAMIN', 'DATAMAX', 'DATAMEAN', 'DATARMS', 'DATASKEW']].plot(
      figsize=(8, 10), subplots=True)
  ax[0].set_title(qstr, fontsize='medium')
  plt.tight_layout()
  plt.show()
  
subject: Use multiple panels in plot of the AIA example