#!/usr/bin/env python
# coding: utf-8

# ### Creating a bullet graph using Bokeh
# 
# This is the notebook associated with the article at [Pbpython.com](http://pbpython.com/bokeh-bullet-waterfall.html)

# 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()


# 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])))


# 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")


# 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)


# 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)