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import matplotlib.pyplot as plt
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

Create some data for bar chart plotting



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people = ('Tom', 'Dick', 'Harry', 'Slim', 'Jim')
performance = 3 + 10 * np.random.rand(len(people))

Static example



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y_pos = np.arange(len(people))
plt.barh(y_pos, performance, align='center', alpha=0.4)
plt.yticks(y_pos, people)
plt.xlabel('Performance')
plt.title('The static version')
plt.show()

Interactive example with bokeh



In [6]:

    
from bokeh.plotting import figure, output_notebook, show

# prepare some data
x = [1, 2, 3, 4, 5]
y = [6, 7, 2, 4, 5]

# output to static HTML file
output_notebook()

# create a new plot with a title and axis labels
p = figure(title="simple line example", x_axis_label='x', y_axis_label='y')

# add a line renderer with legend and line thickness
p.line(x, y, legend="Temp.", line_width=2)

# show the results
show(p)









    




    


    

    
        
        BokehJS successfully loaded.



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