如何在python中做华夫饼图? (方形饼图)

问题描述：

类似这样的事情:

有一个非常好的软件包可以在R中完成.在python中，我能找出的最好的方法是使用squarify包(受):

There is a very good package to do it in R. In python, the best that I could figure out is this, using the squarify package (inspired by a post on how to do treemaps):

import numpy as np
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns # just to have better line color and width
import squarify
# for those using jupyter notebooks
%matplotlib inline 


df = pd.DataFrame({
                  'v1': np.ones(100), 
                  'v2': np.random.randint(1, 4, 100)})
df.sort_values(by='v2', inplace=True)

# color scale
cmap = mpl.cm.Accent
mini, maxi = df['v2'].min(), df['v2'].max()
norm = mpl.colors.Normalize(vmin=mini, vmax=maxi)
colors = [cmap(norm(value)) for value in df['v2']]

# figure
fig = plt.figure()
ax = fig.add_subplot(111, aspect="equal")
ax = squarify.plot(df['v1'], color=colors, ax=ax)
ax.set_xticks([])
ax.set_yticks([]);

但是当我创建的元素不是100个而是200个(或其他非正方形数字)时，正方形会错位.

But when I create not 100 but 200 elements (or other non-square numbers), the squares become misaligned.

另一个问题是，如果我将v2更改为某个类别变量(例如，一百个As，Bs，Cs和Ds)，则会出现此错误:

Another problem is that if I change v2 to some categorical variable (e.g., a hundred As, Bs, Cs and Ds), I get this error:

无法将字符串转换为浮点数:"a"

could not convert string to float: 'a'

所以，有人可以帮助我解决以下两个问题:

So, could anyone help me with these two questions:

如何解决非平方观测值的对齐问题?
如何在v2中使用分类变量?

除此之外，如果还有其他Python软件包可以更有效地创建华夫饼图，我真的很开放.

Beyond this, I am really open if there are any other python packages that can create waffle plots more efficiently.

答

我花了几天时间来构建更通用的解决方案PyWaffle.

I spent a few days to build a more general solution, PyWaffle.

您可以通过

pip install pywaffle

源代码: https://github.com/gyli/PyWaffle

PyWaffle不使用matshow()方法，而是一个一个地构建这些正方形.这样可以更轻松地进行自定义.此外，它提供了一个自定义的Figure类，该类返回一个Figure对象.通过更新图形的属性，您基本上可以控制图表中的所有内容.

PyWaffle does not use matshow() method, but builds those squares one by one. That makes it easier for customization. Besides, what it provides is a custom Figure class, which returns a figure object. By updating attributes of the figure, you can basically control everything in the chart.

一些例子:

彩色或透明背景

import matplotlib.pyplot as plt
from pywaffle import Waffle

data = {'Democratic': 48, 'Republican': 46, 'Libertarian': 3}
fig = plt.figure(
    FigureClass=Waffle, 
    rows=5, 
    values=data, 
    colors=("#983D3D", "#232066", "#DCB732"),
    title={'label': 'Vote Percentage in 2016 US Presidential Election', 'loc': 'left'},
    labels=["{0} ({1}%)".format(k, v) for k, v in data.items()],
    legend={'loc': 'lower left', 'bbox_to_anchor': (0, -0.4), 'ncol': len(data), 'framealpha': 0}
)
fig.gca().set_facecolor('#EEEEEE')
fig.set_facecolor('#EEEEEE')
plt.show()

使用图标代替正方形:

data = {'Democratic': 48, 'Republican': 46, 'Libertarian': 3}
fig = plt.figure(
    FigureClass=Waffle, 
    rows=5, 
    values=data, 
    colors=("#232066", "#983D3D", "#DCB732"),
    legend={'loc': 'upper left', 'bbox_to_anchor': (1, 1)},
    icons='child', icon_size=18, 
    icon_legend=True
)

一张图表中有多个子图:

import pandas as pd
data = pd.DataFrame(
    {
        'labels': ['Hillary Clinton', 'Donald Trump', 'Others'],
        'Virginia': [1981473, 1769443, 233715],
        'Maryland': [1677928, 943169, 160349],
        'West Virginia': [188794, 489371, 36258],
    },
).set_index('labels')

fig = plt.figure(
    FigureClass=Waffle,
    plots={
        '311': {
            'values': data['Virginia'] / 30000,
            'labels': ["{0} ({1})".format(n, v) for n, v in data['Virginia'].items()],
            'legend': {'loc': 'upper left', 'bbox_to_anchor': (1.05, 1), 'fontsize': 8},
            'title': {'label': '2016 Virginia Presidential Election Results', 'loc': 'left'}
        },
        '312': {
            'values': data['Maryland'] / 30000,
            'labels': ["{0} ({1})".format(n, v) for n, v in data['Maryland'].items()],
            'legend': {'loc': 'upper left', 'bbox_to_anchor': (1.2, 1), 'fontsize': 8},
            'title': {'label': '2016 Maryland Presidential Election Results', 'loc': 'left'}
        },
        '313': {
            'values': data['West Virginia'] / 30000,
            'labels': ["{0} ({1})".format(n, v) for n, v in data['West Virginia'].items()],
            'legend': {'loc': 'upper left', 'bbox_to_anchor': (1.3, 1), 'fontsize': 8},
            'title': {'label': '2016 West Virginia Presidential Election Results', 'loc': 'left'}
        },
    },
    rows=5,
    colors=("#2196f3", "#ff5252", "#999999"),  # Default argument values for subplots
    figsize=(9, 5)  # figsize is a parameter of plt.figure
)

如何在python中做华夫饼图? (方形饼图)

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