old_contents: __author__ = 'saeedamen'  # Saeed Amen
  
  #
  # Copyright 2016 Cuemacro
  #
  # Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the
  # License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an
  # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  #
  # See the License for the specific language governing permissions and limitations under the License.
  #
  
  from chartpy import Chart, Style
  
  # choose run_example = 0 for everything
  # run_example = 1 - plot volatility surface
  run_example = 0
  
  if run_example == 1 or run_example == 0:
      import pandas
  
      # get sample volatility surface for GBP/USD
      df = pandas.read_csv('volsurface.csv')
  
      # set the style of the plot
      style = Style(title="GBP/USD vol surface", source="chartpy", color='Blues')
      style.file_output = 'volsurface.png'
  
      # Chart object is initialised with the dataframe and our chart style
      chart = Chart(df=df, chart_type='surface', style=style)
  
      # chart.plot(engine='matplotlib')   TODO matplotlib implementation
      # chart.plot(engine='bokeh')        TODO bokeh surface implementation
      chart.plot(engine='plotly')
new_contents: __author__ = 'saeedamen'  # Saeed Amen
  
  #
  # Copyright 2016 Cuemacro
  #
  # Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the
  # License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an
  # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  #
  # See the License for the specific language governing permissions and limitations under the License.
  #
  
  from chartpy import Chart, Style
  
  # choose run_example = 0 for everything
  # run_example = 1 - plot volatility surface
  run_example = 0
  
  if run_example == 1 or run_example == 0:
      import pandas
  
      # get sample volatility surface for GBP/USD (and make sure columns are in reasonable order)
      df = pandas.read_csv('volsurface.csv', index_col='Exp')
      df = df[['10D Put GBP', '25D Put GBP', 'ATM', '25D Call GBP', '10D Call GBP']]
  
      # set the style of the plot
      style = Style(title="GBP/USD vol surface", source="chartpy", color='Blues')
      style.file_output = 'volsurface.png'
  
      # Chart object is initialised with the dataframe and our chart style
      chart = Chart(df=df, chart_type='surface', style=style)
  
      chart.plot(engine='matplotlib')
      # chart.plot(engine='bokeh')        # TODO bokeh surface implementation
      chart.plot(engine='plotly')
subject: Change orders of GBP columns