Notebook for Building a bullet chart in python. Full article posted in http://pbpython.com/bullet-graph.html
In [1]:
import matplotlib.pyplot as plt
import seaborn as sns
from matplotlib.ticker import FuncFormatter
In [2]:
%matplotlib inline
Show examples of using seaborn's palette functionality
In [3]:
sns.palplot(sns.light_palette("green", 5))
In [4]:
sns.palplot(sns.light_palette("red", 5))
In [5]:
sns.palplot(sns.light_palette("purple",8, reverse=True))
Set up the data that we want to plot
In [6]:
limits = [80, 100, 150]
data_to_plot = ("Example 1", 105, 120)
palette = sns.color_palette("Blues_r", len(limits))
Try the first version of building a stacked bar chart
In [7]:
fig, ax = plt.subplots()
ax.set_aspect('equal')
ax.set_yticks([1])
ax.set_yticklabels([data_to_plot[0]])
prev_limit = 0
for idx, lim in enumerate(limits):
ax.barh([1], lim-prev_limit, left=prev_limit, height=15, color=palette[idx])
prev_limit = lim
Expand on the version to add the value we are measuring
In [8]:
fig, ax = plt.subplots()
ax.set_aspect('equal')
ax.set_yticks([1])
ax.set_yticklabels([data_to_plot[0]])
prev_limit = 0
for idx, lim in enumerate(limits):
ax.barh([1], lim-prev_limit, left=prev_limit, height=15, color=palette[idx])
prev_limit = lim
# Draw the value we're measuring
ax.barh([1], data_to_plot[1], color='black', height=5)
Out[8]:
Now add on the target vertical line
In [9]:
fig, ax = plt.subplots()
ax.set_aspect('equal')
ax.set_yticks([1])
ax.set_yticklabels([data_to_plot[0]])
prev_limit = 0
for idx, lim in enumerate(limits):
ax.barh([1], lim-prev_limit, left=prev_limit, height=15, color=palette[idx])
prev_limit = lim
# Draw the value we're measuring
ax.barh([1], data_to_plot[1], color='black', height=5)
ax.axvline(data_to_plot[2], color="gray", ymin=0.10, ymax=0.9)
Out[9]:
Build out a full function
In [10]:
def bulletgraph(data=None, limits=None, labels=None, axis_label=None, title=None,
size=(5, 3), palette=None, formatter=None, target_color="gray",
bar_color="black", label_color="gray"):
""" Build out a bullet graph image
Args:
data = List of labels, measures and targets
limits = list of range valules
labels = list of descriptions of the limit ranges
axis_label = string describing x axis
title = string title of plot
size = tuple for plot size
palette = a seaborn palette
formatter = matplotlib formatter object for x axis
target_color = color string for the target line
bar_color = color string for the small bar
label_color = color string for the limit label text
Returns:
a matplotlib figure
"""
# Determine the max value for adjusting the bar height
# Dividing by 10 seems to work pretty well
h = limits[-1] / 10
# Use the green palette as a sensible default
if palette is None:
palette = sns.light_palette("green", len(limits), reverse=False)
# Must be able to handle one or many data sets via multiple subplots
if len(data) == 1:
fig, ax = plt.subplots(figsize=size, sharex=True)
else:
fig, axarr = plt.subplots(len(data), figsize=size, sharex=True)
# Add each bullet graph bar to a subplot
for idx, item in enumerate(data):
# Get the axis from the array of axes returned when the plot is created
if len(data) > 1:
ax = axarr[idx]
# Formatting to get rid of extra marking clutter
ax.set_aspect('equal')
ax.set_yticklabels([item[0]])
ax.set_yticks([1])
ax.spines['bottom'].set_visible(False)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(False)
prev_limit = 0
for idx2, lim in enumerate(limits):
# Draw the bar
ax.barh([1], lim - prev_limit, left=prev_limit, height=h,
color=palette[idx2])
prev_limit = lim
rects = ax.patches
# The last item in the list is the value we're measuring
# Draw the value we're measuring
ax.barh([1], item[1], height=(h / 3), color=bar_color)
# Need the ymin and max in order to make sure the target marker
# fits
ymin, ymax = ax.get_ylim()
ax.vlines(
item[2], ymin * .9, ymax * .9, linewidth=1.5, color=target_color)
# Now make some labels
if labels is not None:
for rect, label in zip(rects, labels):
height = rect.get_height()
ax.text(
rect.get_x() + rect.get_width() / 2,
-height * .4,
label,
ha='center',
va='bottom',
color=label_color)
if formatter:
ax.xaxis.set_major_formatter(formatter)
if axis_label:
ax.set_xlabel(axis_label)
if title:
fig.suptitle(title, fontsize=14)
fig.subplots_adjust(hspace=0)
In [11]:
data_to_plot2 = [("John Smith", 105, 120),
("Jane Jones", 99, 110),
("Fred Flintstone", 109, 125),
("Barney Rubble", 135, 123),
("Mr T", 45, 105)]
bulletgraph(data_to_plot2, limits=[20, 60, 100, 160], labels=["Poor", "OK", "Good", "Excellent"], size=(8,5),
axis_label="Performance Measure", label_color="black", bar_color="#252525", target_color='#f7f7f7',
title="Sales Rep Performance")
In [12]:
def money(x, pos):
'The two args are the value and tick position'
return "${:,.0f}".format(x)
In [13]:
money_fmt = FuncFormatter(money)
data_to_plot3 = [("Print", 50000, 60000),
("Billboards", 75000, 65000),
("Radio", 125000, 80000),
("Online", 195000, 115000)]
palette = sns.light_palette("grey", 3, reverse=False)
bulletgraph(data_to_plot3, limits=[50000, 125000, 200000], labels=["Below", "On Target", "Above"], size=(10,5),
axis_label="Annual Budget", label_color="black", bar_color="#252525", target_color='#f7f7f7', palette=palette,
title="Marketing Channel Budget Performance", formatter=money_fmt)