

In [1]:

    
import numpy as np
import pandas as pd

import bqplot.pyplot as plt



In [2]:

    
np.random.seed(10)
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))
y_data = np.cumsum(np.random.randn(100))

Label positioned in data co-ordinates



In [3]:

    
fig = plt.figure(title='Basic Label Example')
test_line = plt.plot(np.arange(10), y_data[:10])
test_label = plt.label(['Test', 'Label', 'for', 'the', 'Data'], 
                       x=np.arange(5), y=y_data[:5], 
                       default_size=26, font_weight='bolder',
                       colors=['orange', 'red'], update_on_move=True)
fig

Setting the label attribute enable_move to True makes the label draggable



In [4]:

    
# now the labels can be moved by dragging them!
test_label.enable_move = True

Label positioned in terms of Figure co-ordinates



In [5]:

    
fig = plt.figure()

test_line = plt.plot(np.arange(10), y_data)
test_label = plt.label(['Test Label'], default_size=26, font_weight='bolder', colors=['orange'])
test_label.x = [0.5]
test_label.y = [0.2]
fig



In [6]:

    
# Rotating the label
test_label.rotate_angle = 30

Label positioned at a Date value



In [7]:

    
fig = plt.figure()
lines = plt.plot(price_data.index, price_data['Security 1'])
label = plt.label(['Pi-Day'], x=[np.datetime64('2007-03-14')], colors=['orange'])
label.y = [.5]
fig



In [8]:

    
# Setting an offset in pixels
label.x_offset = 100