

In [ ]:

    
import numpy as np
import pandas as pd

from bqplot import *
from datetime import datetime as dt

from bqplot.traits import *



In [ ]:

    
price_data = pd.DataFrame(np.cumsum(np.random.randn(150, 2).dot([[0.5, 0.8], [0.8, 1.0]]), axis=0) + 100,
                          columns=['Security 1', 'Security 2'],
                          index=pd.date_range(start='01-01-2007', periods=150))

numpy array of np.datetime objects



In [ ]:

    
x_data = price_data.index.values
x_data[:5]



In [ ]:

    
dt_x = DateScale()
sc_y = LinearScale()

line = Lines(x=x_data, y=price_data['Security 1'].values, scales={'x': dt_x, 'y': sc_y})
ax_x = Axis(scale=dt_x)
ax_y = Axis(scale=sc_y, orientation='vertical')

Figure(marks=[line], axes=[ax_x, ax_y])

List of python datetimes



In [ ]:

    
import datetime
ref_date = dt.datetime(2010, 1, 1)
num_items = range(250)

x_data = [ref_date + datetime.timedelta(x) for x in num_items]
x_data[:5]



In [ ]:

    
dt_x = DateScale()
sc_y = LinearScale()

date_x = convert_to_date(x_data)
line = Lines(x=date_x, y=price_data['Security 1'].values, scales={'x': dt_x, 'y': sc_y})
ax_x = Axis(scale=dt_x)
ax_y = Axis(scale=sc_y, orientation='vertical')

Figure(marks=[line], axes=[ax_x, ax_y])

Array of python datetimes



In [ ]:

    
x_data = np.array(x_data)
x_data[:5]



In [ ]:

    
dt_x = DateScale()
sc_y = LinearScale()

date_x = convert_to_date(x_data)
line = Lines(x=date_x, y=price_data['Security 1'].values, scales={'x': dt_x, 'y': sc_y})
ax_x = Axis(scale=dt_x)
ax_y = Axis(scale=sc_y, orientation='vertical')

Figure(marks=[line], axes=[ax_x, ax_y])

Array of dates converted to string



In [ ]:

    
date_format = '%m-%d-%Y'
x_data = price_data.index.values
x_data[:5]



In [ ]:

    
dt_x = DateScale()
sc_y = LinearScale()

date_x = convert_to_date(x_data)
line = Lines(x=date_x, y=price_data['Security 1'].values, scales={'x': dt_x, 'y': sc_y})
ax_x = Axis(scale=dt_x)
ax_y = Axis(scale=sc_y, orientation='vertical')

Figure(marks=[line], axes=[ax_x, ax_y])

List of dates converted to string



In [ ]:

    
x_data = x_data.tolist()
x_data[:5]



In [ ]:

    
dt_x = DateScale()
sc_y = LinearScale()

line = Lines(x=x_data, y=price_data['Security 1'].values, scales={'x': dt_x, 'y': sc_y})
ax_x = Axis(scale=dt_x)
ax_y = Axis(scale=sc_y, orientation='vertical')

Figure(marks=[line], axes=[ax_x, ax_y])

Multi-dimensional x and y



In [ ]:

    
date_format = '%m-%d-%Y'
x_data = price_data.index.values

data_2 = price_data.iloc[30: ,]
x_data_2 = data_2.index.values



In [ ]:

    
final_y = pd.concat([price_data['Security 1'], data_2['Security 2']], axis=1).values.T



In [ ]:

    
dt_x = DateScale()
sc_y = LinearScale()

line = Lines(x=x_data, y=final_y, scales={'x': dt_x, 'y': sc_y}, labels=['spx', 'sp2'], 
             display_legend=True, colors=['hotpink', 'orange'])

ax_x = Axis(scale=dt_x)
ax_y = Axis(scale=sc_y, orientation='vertical')

Figure(marks=[line], axes=[ax_x, ax_y])



In [ ]:



In [ ]:



In [ ]: