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Matplotlib: Draw pie chart with wedge breakdown into barchart

I've got a pie chart (example) with following fracs = [10, 20, 50, 30]. Drawing this with matplotlib is no problem. How do I get a breakdown of the first wedge (10) into 6 and 4? Ideally, I want a second wedge for the 20, to breakdown into 10, 3, 7. This would be displayed as a barchart near the specific wedge or a pie chart (which would make it a pie of pie chart similar to the ones in Excel).

like image 793
keynes Avatar asked Jan 01 '26 22:01

keynes


2 Answers

Here is one way of doing it (possibly not the best...). I've adapted some of the code found here, on the matplotlib site to make a little_pie function, that will draw small pie charts at arbitrary positions.

from pylab import *
import math
import numpy as np

def little_pie(breakdown,location,size):
    breakdown = [0] + list(np.cumsum(breakdown)* 1.0 / sum(breakdown))
    for i in xrange(len(breakdown)-1):
        x = [0] + np.cos(np.linspace(2 * math.pi * breakdown[i], 2 * math.pi *    
                          breakdown[i+1], 20)).tolist()
        y = [0] + np.sin(np.linspace(2 * math.pi * breakdown[i], 2 * math.pi * 
                          breakdown[i+1], 20)).tolist()
        xy = zip(x,y)
        scatter( location[0], location[1], marker=(xy,0), s=size, facecolor=
               ['gold','yellow', 'orange', 'red','purple','indigo','violet'][i%7])

figure(1, figsize=(6,6))

little_pie([10,3,7],(1,1),600)
little_pie([10,27,4,8,4,5,6,17,33],(-1,1),800)

fracs = [10, 8, 7, 10]
explode=(0, 0, 0.1, 0)
pie(fracs, explode=explode, autopct='%1.1f%%')
show()

enter image description here

like image 78
fraxel Avatar answered Jan 03 '26 12:01

fraxel


I couldn't find a solution for this, so I hacked my own. I used the ConnectionPatch object in the matplotlib.patches module. This allows you to draw lines between different axes in the same figure. The following creates a pie chart on the left and a stacked bar on the right:

import matplotlib.pyplot as plt
from matplotlib.patches import ConnectionPatch
import numpy as np
import math

# style choice
plt.style.use('fivethirtyeight')

# make figure and assign axis objects
fig = plt.figure(figsize=(15,7.5))
ax1 = fig.add_subplot(121)
ax2 = fig.add_subplot(122)

# pie chart parameters
ratios = [.4, .56, .04]
labels = ['Approve', 'Disapprove', 'Undecided']
explode=[0.1,0,0]
# rotate so that first wedge is split by the x-axis
angle = -180*ratios[0]
ax1.pie(ratios, autopct='%1.1f%%', startangle=angle,
        labels=labels,explode=explode )

# bar chart parameters

xpos = 0
bottom = 0
ratios = [.33, .54, .07, .06]
width = .2
colors = ['y','m','#99ff99','#ffcc99']

for j in range(len(ratios)):
    height = ratios[j]
    ax2.bar(xpos, height, width, bottom=bottom, color=colors[j])
    ypos = bottom + ax2.patches[j].get_height()/2
    bottom += height
    ax2.text(xpos,ypos, "%d%%" %
        (ax2.patches[j].get_height()*100), ha='center')

plt.title('Gender of approvers')
plt.legend(('Women', 'Men', 'Gender Neutral', 'Alien'))
plt.axis('off')
plt.xlim(-2.5*width, 2.5*width)

Then I add two lines connected the first wedge of the pie chart with the top and bottom, respectively, of the stacked bar plot:

# use ConnectionPatch to draw lines between the two plots
# get the wedge data for the first group
theta1, theta2 = ax1.patches[0].theta1, ax1.patches[0].theta2
center, r = ax1.patches[0].center, ax1.patches[0].r
bar_height = sum([item.get_height() for item in ax2.patches])
x = r*np.cos(math.pi/180*theta2)+center[0]
y = np.sin(math.pi/180*theta2)+center[1]
con = ConnectionPatch(xyA=(-width/2,bar_height), xyB=(x,y),
    coordsA="data", coordsB="data", axesA=ax2, axesB=ax1)
con.set_color([0,0,0])
con.set_linewidth(4)
ax2.add_artist(con)

x = r*np.cos(math.pi/180*theta1)+center[0]
y = np.sin(math.pi/180*theta1)+center[1]
con = ConnectionPatch(xyA=(-width/2,0), xyB=(x,y),
    coordsA="data", coordsB="data", axesA=ax2, axesB=ax1)
con.set_color([0,0,0])
ax2.add_artist(con)
con.set_linewidth(4)

plt.show()

Here is the plot: Bar in pie example

like image 37
mathisfun Avatar answered Jan 03 '26 11:01

mathisfun



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