Assign specific colours to data in Matplotlib pie chart

Question

I\'m trying to create pie charts with matplotlib in which the colour of each category is fixed.

I\'ve got a function which creates a pie chart from sets

Answer 1

Here's an idea you could try. Make a dictionary from your labels and colors, so each color is mapped to a label. Then, after making the pie chart, go in an assign the facecolor of the wedge using this dictionary.

Here's an untested bit of code which might do what you are looking for:

import numpy as np
import matplotlib.pyplot as plt

def mypie(slices,labels,colors):

    colordict={}
    for l,c in zip(labels,colors):
        print l,c
        colordict[l]=c

    fig = plt.figure(figsize=[10, 10])
    ax = fig.add_subplot(111)

    pie_wedge_collection = ax.pie(slices, labels=labels, labeldistance=1.05)#, autopct=make_autopct(slices))

    for pie_wedge in pie_wedge_collection[0]:
        pie_wedge.set_edgecolor('white')
        pie_wedge.set_facecolor(colordict[pie_wedge.get_label()])

    titlestring = 'Issues'

    ax.set_title(titlestring)

    return fig,ax,pie_wedge_collection

slices = [37, 39, 39, 38, 62, 21, 15,  9,  6,  7,  6,  5,  4, 3]
cmap = plt.cm.prism
colors = cmap(np.linspace(0., 1., len(slices)))
labels = [u'TI', u'Con', u'FR', u'TraI', u'Bug', u'Data', u'Int', u'KB', u'Other', u'Dep', u'PW', u'Uns', u'Perf', u'Dep']

fig,ax,pie_wedge_collection = mypie(slices,labels,colors)

plt.show()

Answer 2

Here is a simpler solution to @tmdavison's answer.

Let's first see the problem with an MWE:

import matplotlib.pyplot as plt

labels = ['Frogs', 'Hogs', 'Dogs', 'Logs']
sizes = [15, 30, 45, 10]

fig, ax = plt.subplots(1, 2)

ax[0].pie(sizes, labels=labels)
ax[1].pie(sizes[1:], labels=labels[1:])

This produces the problem plots:

The problem is that in the left-hand plot, Hogs is coloured in orange, but in the right-hand plot Hogs is coloured in blue (with a similar mix-up for Logs and Dogs).

We would like the colours for the labels to be the same across both plots. We can do this by specifying a dictionary of colours to use:

labels = ['Frogs', 'Hogs', 'Dogs', 'Logs']
sizes = [15, 30, 45, 10]
colours = {'Frogs': 'C0',
           'Hogs': 'C1',
           'Dogs': 'C2',
           'Logs': 'C3'}

fig, ax = plt.subplots(1, 2)

ax[0].pie(sizes,
          labels=labels,
          colors=[colours[key] for key in labels])

ax[1].pie(sizes[1:],
          labels=labels[1:],
          colors=[colours[key] for key in labels[1:]])

This works to create the plot:

Here we see that the labels are represented by the same colours across both plots, as desired.

If you have lots of categories it can be cumbersome to manually set a colour for each category. In this case you could construct the colours dictionary as:

colours = dict(zip(labels, plt.cm.tab10.colors[:len(labels)]))

If you have more than 10 categories you would instead use:

colours = dict(zip(labels, plt.cm.tab20.colors[:len(labels)]))