content: # -*- coding: utf-8 -*-
  """
  
  Vincent Scatter Examples
  
  """
  
  #Build a Line Chart from scratch
  
  from vincent import *
  import pandas as pd
  import pandas.io.data as web
  import datetime
  all_data = {}
  date_start = datetime.datetime(2010, 1, 1)
  date_end = datetime.datetime(2014, 1, 1)
  for ticker in ['AAPL', 'IBM', 'YHOO', 'MSFT']:
      all_data[ticker] = web.DataReader(ticker, 'yahoo', date_start, date_end)
  price = pd.DataFrame({tic: data['Adj Close']
                        for tic, data in all_data.items()})
  
  #Note that we're using timeseries, so x-scale type is "time". For non
  #timeseries data, use "linear"
  vis = Visualization(width=500, height=300)
  vis.scales['x'] = Scale(name='x', type='time', range='width',
                          domain=DataRef(data='table', field="data.idx"))
  vis.scales['y'] = Scale(name='y', range='height', type='linear', nice=True,
                          domain=DataRef(data='table', field="data.val"))
  vis.scales['color'] = Scale(name='color', type='ordinal',
                              domain=DataRef(data='table', field='data.col'),
                              range='category20')
  vis.axes.extend([Axis(type='x', scale='x'),
                   Axis(type='y', scale='y')])
  
  #Marks
  transform = MarkRef(data='table',
                      transform=[Transform(type='facet', keys=['data.col'])])
  enter_props = PropertySet(x=ValueRef(scale='x', field="data.idx"),
                            y=ValueRef(scale='y', field="data.val"),
                            fill=ValueRef(scale='color', field='data.col'),
                            size=ValueRef(value=10))
  mark = Mark(type='group', from_=transform,
              marks=[Mark(type='symbol',
              properties=MarkProperties(enter=enter_props))])
  vis.marks.append(mark)
  
  data = Data.from_pandas(price[['MSFT', 'AAPL']])
  
  #Using a Vincent Keyed List here
  vis.data['table'] = data
  vis.axis_titles(x='Date', y='Price')
  vis.legend(title='MSFT vs AAPL')
  vis.to_json('vega.json')
  
  #Convenience method
  
  vis = Scatter(price[['MSFT', 'AAPL']])
  vis.axis_titles(x='Date', y='Price')
  vis.legend(title='MSFT vs AAPL')
  vis.colors(brew='RdBu')
  vis.to_json('vega.json')
  