In [1]:

    

from bokeh.io import show, output_notebook
from bokeh.palettes import PuBu4
from bokeh.plotting import figure
from bokeh.models import Label


    

In [2]:

    

output_notebook()


    

    






    

        
        Loading BokehJS ...
    






    

In [3]:

    

# Load in the data
data= [("John Smith", 105, 120),
       ("Jane Jones", 99, 110),
       ("Fred Flintstone", 109, 125),
       ("Barney Rubble", 135, 123),
       ("Mr T", 45, 105)]

limits = [0, 20, 60, 100, 160]
labels = ["Poor", "OK", "Good", "Excellent"]
cats = [x[0] for x in data]


    

In [4]:

    

# Create the base figure
p=figure(title="Sales Rep Performance", plot_height=350, plot_width=800, y_range=cats)
p.x_range.range_padding = 0
p.grid.grid_line_color = None
p.xaxis[0].ticker.num_minor_ticks = 0


    

In [5]:

    

# Here's the format of the data we need
print(list(zip(limits[:-1], limits[1:], PuBu4[::-1])))


    

    




[(0, 20, '#f1eef6'), (20, 60, '#bdc9e1'), (60, 100, '#74a9cf'), (100, 160, '#0570b0')]

In [6]:

    

for left, right, color in zip(limits[:-1], limits[1:], PuBu4[::-1]):
    p.hbar(y=cats, left=left, right=right, height=0.8, color=color)


    

In [7]:

    

show(p)


    

In [8]:

    

# Now add the black bars for the actual performance
perf = [x[1] for x in data]
p.hbar(y=cats, left=0, right=perf, height=0.3, color="black")


    

    
Out[8]:




GlyphRenderer(
id = 'b74dd2be-5247-49c2-8f91-74b8b95b65c3', …)
data_source = ColumnDataSource(id='16e81a84-0e42-40bc-b65c-052d37b77e4a', ...),
glyph = HBar(id='b9dc72ae-b295-4fd6-add7-d805fa6e381a', ...),
hover_glyph = None,
js_event_callbacks = {},
js_property_callbacks = {},
level = 'glyph',
muted = False,
muted_glyph = None,
name = None,
nonselection_glyph = HBar(id='0e6796bb-e53e-48aa-bd0f-594b9a3f83df', ...),
selection_glyph = None,
subscribed_events = [],
tags = [],
view = CDSView(id='e241765e-3b5a-4be2-af7e-984e7aa9a21e', ...),
visible = True,
x_range_name = 'default',
y_range_name = 'default')

In [9]:

    

show(p)


    

In [10]:

    

# Add the segment for the target
comp = [x[2]for x in data]
p.segment(x0=comp, y0=[(x, -0.5) for x in cats], x1=comp, 
          y1=[(x, 0.5) for x in cats], color="white", line_width=2)


    

    
Out[10]:




GlyphRenderer(
id = '4abe5572-1d9d-4d00-8328-3e14208c2059', …)
data_source = ColumnDataSource(id='f0578c05-a4cf-448c-b4fc-ac09307fcb88', ...),
glyph = Segment(id='1c2c5e6e-5a1f-4244-b1f2-6a19f83c8189', ...),
hover_glyph = None,
js_event_callbacks = {},
js_property_callbacks = {},
level = 'glyph',
muted = False,
muted_glyph = None,
name = None,
nonselection_glyph = Segment(id='0b0f764c-720a-496c-b1ff-e0516ae5d22e', ...),
selection_glyph = None,
subscribed_events = [],
tags = [],
view = CDSView(id='7acc21a1-79b4-442f-ab3c-18c288dc190c', ...),
visible = True,
x_range_name = 'default',
y_range_name = 'default')

In [11]:

    

show(p)


    

In [12]:

    

# Add the labels
for start, label in zip(limits[:-1], labels):
    p.add_layout(Label(x=start, y=0, text=label, text_font_size="10pt",
                       text_color='black', y_offset=5, x_offset=15))


    

In [13]:

    

show(p)