为 Matplotlib 饼图中的数据指定特定颜色 [英] Assign specific colours to data in Matplotlib pie chart

问题描述

我正在尝试使用 matplotlib 创建饼图，其中每个类别的颜色都是固定的.

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

我有一个函数可以根据值和类别数据集创建饼图.举个例子:

I've got a function which creates a pie chart from sets of value and category data. Here's one example:

Category     Value
TI           65
Con          43
FR           40
TraI         40
Bug          38
Data         22
Int          15
KB           12
Other        8
Dep          7
PW           6
Uns          5
Perf         4
Dep          3

问题是数据从一个实例到另一个实例不同，进而改变了类别的顺序.因此，每次我生成图表时，每个类别都会被标记为不同的颜色.我每次都可以按字母顺序对数据进行排序，但这会导致两个问题:某些数据集中缺少某些类别，而且我更喜欢按大小排序，以便最小的楔子水平定向.

The problem is that the data differs from one instance to another, and that in turn changes the order of the categories. Thus, each category gets labelled a different colour each time I generate a chart. I could sort the data alphabetically every time, but that causes two problems: some categories are missing from some datasets, and I'd prefer it sorted by size anyway so that the smallest wedges are oriented horizontally.

如何设置 matplotlib 以根据 pandas.Series 的索引分配颜色?

How can I set matplotlib to assign colours depending on, say, the index of a pandas.Series?

这是我用来生成饼图的代码:

Here's the code that I'm using to generate a pie chart:

import matplotlib.pyplot as plt

slices = [62, 39, 39, 38, 37, 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 = plt.figure(figsize=[10, 10])
ax = fig.add_subplot(111)

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

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

titlestring = 'Issues'

ax.set_title(titlestring)

我忘了解释 autopct 函数，它用于添加值和百分比标签:

I forgot to explain the autopct function, it's for adding value and percentage labels:

def make_autopct(values):
    def my_autopct(pct):
        total = sum(values)
        val = int(round(pct*total/100.0))
        return '{p:.2f}%  ({v:d})'.format(p=pct,v=val)
    return my_autopct

推荐答案

这里有一个你可以尝试的想法.根据您的标签和颜色制作字典，以便将每种颜色映射到一个标签.然后，在制作饼图后，使用此字典分配楔形的facecolor.

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.

这里有一段未经测试的代码，可以满足您的要求:

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()

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